Journal of Optimization in Industrial Engineering
Volume:15 Issue: 33, Summer and Autumn 2022

Risk management improves and increases the speed of development and optimal implementation of the company's strategy to achieve a competitive advantage. Risk identification and assessment are known as one of the main tools of safety management, which helps the safety manager better select risk reduction measures and standardization of automobile oil filter by creating a suitable information platform. In this regard, evaluating and analyzing failure modes and their effects is an appropriate tool for risk management and improving product quality. Due to the weaknesses of the traditional method the complexities of the fuzzy method, a new type of risk non-priority is presented by assigning different weights to each of the risk factors under uncertainty and the proposed method is compared with the traditional and fuzzy methods simultaneously. The purpose of this study is to analyze the failure mode and risks in operation and various stages of manufacturing automobile oil filter, then to prioritize and compare risks by applying the fuzzy theory method and robust data envelopment analysis. Oil filter is an essential part of the automobile that its standardization reduces fuel consumption, improves engine performance and consequently decreases environmental pollution. This research has used the combination of Failure Mode and Effect Analysis( FMEA) method for analyzing the reliability of the oil filter and fuzzy theory has been used to record experts' opinions on failure modes and calculate the risk priority of each subsystem under uncertainty. In order to eliminate the existing defects, a new method is introduced for calculating the risk priority number in the failure mode and effect analysis based on the data envelopment analysis method. In this research, the robust optimization method covers the results of the data envelopment analysis (DEA) and is less complex than the fuzzy method has been used. The results of the case study indicate that the proposed model is more effective and reliable than the traditional and fuzzy Risk Priority Number (RPN) and also the proposed method has less has complexity than the fuzzy method. This method provides a complete ranking and convincing prioritization of failure modes. After calculating the RPNs, the operations related to the spiral tube, fiber folding, ring bending and cutting, and fiber folding are the highest number of RPNs, respectively, and their corrective actions were also determined.

More than 90% of companies in Iran construction Industry are small and medium sized contractors. Only 5% of them are using the electronic commerce services and facilities for their businesses. SMCs must re-evaluate every aspect of their strategies and quickly move to a working model where the e-commerce is essential for their success. The concept of electronic readiness assessment for SMCs has received limited attention in the literature. This paper proposed developing a valid model for assessing the capacity and capability of SMCs to adopt e-commerce in Iran construction industry. The research involved a comprehensive review of related literature and the collection of data to identify the indicators and criteria by means of documentary analysis and using a combination of more frequent e-readiness factors in current models and SMCs obstacles in e-commerce implementation. Focus discussion group was conducted by using interviews with SMCs’ stakeholders for e-commerce to understand the contextual factors that influence the norms and attitudes prevailing in SMCs that affect their adoption of e-commerce. To test the conceptual model, a questionnaire was used to collect data from larger sample of SMCs in Iran. The collected data were analysed using a combination of “hermeneutical analysis” and Structured Equation Modelling. The findings confirmed that IT infrastructure, human resources, financial investment, owners or top management attitudes and cultural issues were the most important indicators that measure in detail the level of the e-readiness of SMCs to adopt e-commerce in Iran construction industry.

In this paper, the mitigating subsynchronous resonance (SSR) phenomenon has been designed in modified IEEE- first bench mark including DFIG-based wind farms connected compensated transmission lines that includes a series capacitor with fuzzy controller. In addition, wide- area measurement systems have been used in the fuzzy controller. This paper designs a fuzzy logic wide-area damping controller to mitigate SSR by considering the time delay caused by the (Phasor Measurement Unit) PMU measurement. The fuzzy controller is a supplementary signal at the stator voltage of the gird-side converter (GSC) of DFIG-primarily based wind farms. This controller is executed by including voltage and capacitor voltage variations of series capacitive compensated. The effectiveness and validity of the proposed auxiliary damping control had been verified on a modified scheme of the IEEE- first benchmark model via time area simulation analysis by using MATLAB/Simulink.

P3 Sweetener is categorized as a nanomaterial-based health and wellness product. It is also known as a nanofood product, used to intensify the nutritional content, quality, and flavor of food. However, minimal research, interest, and engagement have led to limited knowledge discovery, uncertainty, and lack of understanding on this matter. Thus, the present study is intended to investigate the relationship between adoption factors of P3 Sweetener towards the purchase behavior of the consumers. A conceptual framework was constructed based on the Stimulus Organism Response (SOR) model developed by Mehrabian and Russell in 1974. An online questionnaire was distributed online via Google Forms for data collection. This quantitative study involved 390 P3 Sweetener users who responded to the questionnaire distributed in Johor, Malaysia, based upon the purposive sampling plan (homogenous sampling). After discarding the incomplete questionnaires, approximately 365 samples were considered suitable for further analysis, which was performed using Partial Least Squares Structural Equation Modelling (PLS-SEM). Research result indicated that perceived benefit, motivation, and trust have significant relationships with purchase behavior. Also, it postulated that motivation was the most significant predictor for purchase behavior, affecting the psychological processes of the human mind and led to the willingness to purchase the P3 Sweetener. Despite the substantial contributions generated from the current study, limitations do exist. Firstly, the number of food industries related to nanofood in Malaysia is limited. Secondly, the data collection process was time-consuming. The appropriate samples and data collection took approximately six months to be completed due to their confidentiality. Lastly, this research was confined to Johoreans in the state of Johor, Malaysia. Finally, it indicated that this study is among the first to investigate the adoption factor of the P3 Sweetener product from the behavioral perspective. It also helps to comprehensively understand the adoption process of P3 Sweetener among users, especially in health and wellness industries in Malaysia. Lastly, this study helps to enrich the literature by identifying the adoption factors of P3 Sweetener in the health and wellness managerial context and provide recommendations for future studies.

Electricity theft and fraud in billing are the primary concerns for Distribution System Operators (DSO). It is estimated that billions of dollars are lost each year due to these illegal activities. DSOs around the world, especially in underdeveloped countries, are still utilizing conventional time consuming and inefficient methods for Non-Technical Loss (NTL) detection. This research work attempts to solve the mentioned problems by developing an efficient energy theft detection model to identify the fraudster customers in a power distribution system. The key motivation for the current study is to assist the DSOs for their campaign against energy theft. The proposed method initially utilizes the monthly consumption data of energy customers, obtained from Multan Electric Power Company (MEPCO) Pakistan, to segregate the honest and the fraudulent customers. The Bagged Chi-square Automatic Interaction Detection (CHAID) Decision Tree (DT) algorithm is used to classify the honest and fraudster consumers. Furthermore, based on the mentioned metrics, the performance superiority of the Bagged CHAID-based NTL detection method is validated by comparing its efficacy with that of few well-known state-of-the-art machine learning algorithms such as Support Vector Machine (SVM), Artificial Neural Network (ANN) Logistic Regression (LR), Bayesian Network (BN) and Discriminant Analysis. The proposed NTL detection method provides an Accuracy of 86.35% and Area Under Curve (AUC) of 0.927, respectively, which are significantly higher than that of the same for the mentioned algorithms.

The aim of this study was to investigate the effect three factors (inspection & grading, sourcing policies and resource policies) on the cycle-time performance of a remanufacturing system under three different quality scenarios. The objectives were to analyse (i) the main effect of factors on the remanufacturing cycle-time under the given three quality scenarios, (ii) the interaction effect between these factors on the remanufacturing cycle-time under the given three quality scenarios; and (iii) the factors and corresponding levels that lead to shortest remanufacturing cycle-time. Simulation technique was used to model and simulate the remanufacturing system. Design of experiment method was used to design a mixed two-level and three-level full factorial for running the simulation experiments. Analysis of variance (ANOVA) was used to analyse the output results from the simulation experiments. The ANOVA results show all three factors have significant effect on the remanufacturing cycle-time, regardless of the quality scenarios. The ANOVA results also suggest that sourcing policies has the most predominant effect when the quality scenario is average. Despite the different quality scenarios, the interaction between sourcing policies and resource policies have significant effects on the remanufacturing cycle-time, with predominant effect when the quality scenario is average. The implications for remanufacturing industry are there must be (i) inspection & grading policies, (ii) sourcing policies and (iii) resource policies, as these factors affect the remanuafacturing cycle-time. This work is novel because it considers three factors simultaneously and carries out the research by using simulation, design of experiment and ANOVA.

In this paper, a preliminary study of industrial steam system reveals that most of the industrial steam user especially the palm oil mill did not bother to save energy as long as the mill meets their productions target and is getting profits for the company. The management is not aware that a huge amount of energy is being wasted during the processes of extracting oil from the fresh fruit bunch (FFB). To embark this study, Steam System Scoping Tool (SSST), Steam System Assessment Tool (SSAT) and 3E Plus: Insulation Program Software, provided by the United Nations Industrial Development Organization (UNIDO) are used to assess the efficiency of steam system operations. The tools also assist in preliminary assessments of how efficiently the steam system is operating. After analyses are conducted, the proposed improvement project is recommended to modify the system back to its initial designed best efficiency. The results also show that there were various losses that are contributing to the energy waste and its cost impact to the mill. Meanwhile, the boiler efficiency was only about 68.6%. The findings proposed steam system optimization (SSO) opportunities by installing the feedwater economizer and reducing the blowdown rate of the boiler. The efficiency of the boiler was increased to 77% from its current operating condition. This also improved the steam quality and production output of the mill. Through these SSO, the annual demand saving is around 4.9 MW, with an energy saving of 75,276 GJ/yr., capable of reducing 13,002 metric tons of carbon dioxide emissions per annum and save 598.3 Tph/yr of biomass fuel. Thus, through this steam system optimization the estimated annual net cost savings are around USD 100,000.00. This paper aims at promoting similar system optimization projects at other plants throughout Malaysia, as it benefits to all industrial steam user especially the palm oil mill industries in Malaysia.

Hydraulic flushing using flushing device is cost effective in removing sediment deposition in sewer system. This technique is especially popular in European countries in controlling sedimentation in closed conduit system. The quick release of large water volume leads to a flush wave under high turbulent flow mimicking dam break phenomenon to flush out the sediment accumulated in sewer. A brief discussion on the factors affecting the efficiency of hydraulic flushing are presented in this paper. These factors can be divided into sewer characteristics, sediment characteristics, flushing device characteristics and environmental factors. Each factor will determine the design of the flush device system. Recommendations of risk assessment techniques that help to establish the failure modes in the sediment flushing system for possible practices, assessing the impact, and planning for corrective actions were also presented. This review would be helpful to support project managers and engineers to establish control plan on the design of hydraulic flushing device for sewer system.

The present study aimed to investigate and prioritize the impact of word of mouth advertising on customer experience in the dental equipment industry. The conceptual model of the research was developed through interviews with fourteen marketing experts. Then, the categories related to word of mouth advertising including 5 categories of credibility, transparency, brand personality, relationship quality and positive and negative advertising were identified. Also, the categories related to customer experience including 4 main categories of satisfaction with sales staff, satisfaction with environment of sales center, customers’ experience of sales centers and diversity of services were identified through interviews and specialized questionnaires and through AHP technique in the form of a questionnaire distributed among the managers of a dental clinic in Tehran. the results of hierarchical analysis showed that among the main categories, satisfaction with sales staff with a weight of 0.302 was ranked first, customers’ experience of sales centers with a weight of 0.244 was ranked second, diversity of services with a weight of 0.229 was ranked third and satisfaction with the environment of sales centers with a weight of 0.225 was ranked fourth. The results of research on the subcategories showed that in the category of customer satisfaction with the sales unit staff, interaction with the weight of 0.219, in the category of satisfaction with environment of sales center, place of sales centers with a weight of 0.228, in the category of customers’ experience of sales centers, customer emotional experience with a weight of 0.251, and in the category of service diversity, after-sales service with a weight of 0.237 had the highest priority from the respondents’ point of view. The results showed that dental equipment sales centers should prioritize categories such as interaction, store place, customers' emotional experience, and after-sales service in their programs.

Any production process should be adjusted based on a target value. The problem of process mean determination in a production system with two markets is investigated. An absorbing Markov chain is employed to formulate the flow of items. All items are inspected and if the value of the quality characteristic falls below a lower limit then the item is scrapped and when it falls above an upper limit then the item is reworked. Since some items are reworked thus the cycle time of production is computed in the presence of the inspection errors. Numerical studies are performed to analyze the results

In this research, the problem of combined transportation in the supply chain of fruits and vegetables under uncertainty has been modeled. The designed model includes 4 levels consisting of cultivation, packaging, distribution and customer centers that aim to meet customer demand for perishable products (fruits and vegetables) under conditions of uncertainty in different scenarios. The presence of multiple vehicles in the supply chain network at different costs has led to the model showing the most suitable combined transport based on the results of the model solution by CPLEX method. Data, and as the probability increases or decreases, the amount of transfer time decreases. The result of changes in uncertainty rates also shows that with increasing uncertainty rates, the amount of demand increases and as a result, more transportation options are used for transportation. This has led to an increase in product transfer time. In the most important sensitivity analysis regarding the time of corruption, it was found that with the increase of corruption time, due to the possibility of storing perishable products and avoiding unwanted transportation, the possibility of using high speed vehicles has been provided and transfer time has decreased. Also, by analyzing the objective function and computational time in larger sizes with SCA and GA algorithms, it was observed that there is no significant difference between the mean indices and the SCA algorithm has a higher efficiency than the GA algorithm in obtaining the value of the objective function in acceptable time.

Today, attention to the social and environmental aspects in addition to the economic aspect has become one of the main concerns of global organizations defending the environment and human societies, and urbanization. Also, profitability is raised as a key component in the robustness of various sectors including agricultural production. In this research, we investigate the impact of some policies and environmental aspects such as land use, pruning decisions, and research and development (R&D) on the profitability of citrus production, in the long run, using the system dynamics (SDs) model. The main contribution of this study is considering several key assumptions simultaneously in an integrated dynamics model such as the solar effect, R&D policy, pesticide effect, harvesting condition, and prune effect which is neglected or less noticed in the literature. For validation, the model’s behavior is compared with collected historical observations. Statistical analysis shows that the simulated model is consistent with historical patterns. To further investigate, the Monte Carlo simulation for sensitive variables of the proposed model is implemented and finally, the model under different scenarios is examined. Various simulations have shown that changes in maximum economic yield, citrus price, and R&D policy are three important and effective agents to achieve the best performance in this sector. Also, the obtained results can help agricultural managers and the application of these interventionist policies can lead to an increase in producers’ income and citrus production.

A Crew Scheduling Problem (CSP) is a highly complex airline optimization problem, which includes two sub-problems, namely Crew Rostering Problem (CRP) and Crew Pairing Problem (CPP). Solving these problems sequentially may not lead to an optimal solution. To overcome this shortcoming, the present study introduces a new bi-objective formulation for the integrating CPP and CRP by considering the reserve crew with the objectives of crew cost minimization and crew reserve maximization. The integrated model generates and assigns pairings to a group of crew members by taking into account the rules and regulations about employing the manpower (i.e., crew member) and crew reservation in order to reduce flight delays or even cancellations due to the unexpected disruptions. An Ant Colony Optimization (ACO) algorithm is used to solve the considered problem. To justify the efficiency of this proposed algorithm in solving the presented model, different test problems are generated and solved by ACO and GAMS. The computational results indicate that solutions obtained by the proposed ACO algorithm have a 2.57% gap with the optimal solutions reported by GAMS as optimization software on average and significantly less CPU time for small-sized problems. Also, ACO obtains better solutions in significantly shorter CPU time for large-sized problems. The results indicate the efficient performance of the proposed algorithm in solving the given problems.

 Using the reliability index to express a system’s safety, reliability theory is applied to study a structure’s failure probability due to the uncertainty (i.e., randomness) of design and production parameters with (a) variability in working conditions and the environment and (b) direct interaction with the soil, the conventional approach has been based on deterministic design methods. In contrast, using the concept of reliability as a new and useful approach, we develop the industry of design and manufacture of agricultural machinery. In this study, the first-order reliability method (FORM) was used to analyze the reliability of a plow bottom standard. To perform the reliability analysis, the required forces on the standard were determined by simulating the interaction of the plow with the soil using finite element method by Abaqus software. Random variables were considered as longitudinal and vertical forces on the bottom standard, radius of the standard arc, plastic cross-section modulus, and yield stress. The reliability index (β) as a measure of the system’s safety of was determined using reliability analysis whose value was found to be 2.569 for the bottom's standard. Moreover, the failure probability (Pf) of the bottom's standard was calculated as 0.005. In the final step, the results of FORM reliability analysis were compared with the reliability results of the Monte Carlo simulation of the plow bottom’s standard. The results showed that the bottom standard’s probability of failure in the FORM and Monte Carlo methods for the conditions considered—i.e., very compacted soil, plowing depth of 30 cm, and velocity of 3 m s-1—are low and almost low, respectively. Also due to the lack of lateral force FX in the limit state function, the FORM analysis indicated sufficient uncertainty of the bottom standard design; therefore, strengthening or optimizing this part of the moldboard plow chassis seems necessary.

In this study, a mathematical programming model is developed for a single round-robin tournament problem to provide a schedule for the preliminary round of the Volleyball Nations League. In this setting, the aim is to assign the teams to the pools at each week as well as to specify the host teams of the pools. This schedule is obtained by minimizing the sum of the differences between the total distance traveled by every team and the average of the total distances traveled by all teams. Then, to evaluate the performance of the developed model, it is applied to obtain the optimal schedule for the preliminary round of the Volleyball Men’s Nations League in year 2018. The results indicate that the sum of the travel distance deviations from the average of the total travel distances of all teams obtained from the schedule provided by the mathematical model is significantly lower than that calculated from the schedule presented by the International Volleyball Federation. Moreover, the schedule presented by the International Volleyball Federation leads to a percentage gap of 449.92% in comparison with the optimal schedule provided by the developed model.

Concerning global warming and the Greenhouse gas (GHG) effect, clean energy resources have captured researchers' interest recently. Biomass materials are among important biofuels and bioenergy production resources that have the potential to replace fossil fuels. Using biomass materials leads to a decline in GHG emission and air pollution levels, not being dependent on fossil fuels, and provide energy security. Due to the importance of bioenergy and biofuels, a multi-product, multi-period, and green mathematical model has been developed to improve economic and environmental objectives for bioethanol and the electricity supply chain. It includes the following decisions: determining production centers' location and capacity, technology selection, determining inventory holding level, biomass type selection, allocation, amount of material flow, and determining transportation modes. In this study, a scenario-based robust compromise programming approach (SRCP) is developed for the bi-objective solution of the provided mathematical model and determining Pareto optimal points under uncertain conditions. Finally, the performance and effectiveness of SRCP are provided, and the results obtained from the case study in Iran are analyzed. According to the results, Annual electricity and bioethanol production capacity are at least 8000 million kWh and 1250 kton, respectively, satisfying 10% of electricity and 5% of gasoline demand in 6 provinces of Iran. The sensitivity analysis also shows that equal weight for both objectives can be more logical for decision makers.

Due to an increase in the number of the aging population in Malaysia, the need for retirement homes to cater to the demands of the aging population has become very challenging. Hence, the aim of this paper is to scrutinize the association between retirement home internal environment (RHIE), basic requirement regulations (BRR) of retirement homes, and retirement home performance (RHP). For the pilot study, 50 subjects were selected to fill out the questionnaire and reliability analysis of the items in the questionnaire was run. The findings of the pilot study depicted that the items were highly reliable. Following this, 400 questionnaires were distributed equally to four retirement homes in Selangor, Johor, Kelantan, and Kuala Lumpur (with 100 questionnaires to each retirement home). Out of this figure, 210 subjects responded to the survey; however, only 205 were complete and used for the study. The findings indicated that there was a significant association a) between RHIE with RHP; b) between BRR with RHP; and c) between RHIE and BRR. Most of the tenants agreed that RHIE should have elderly-centric treatment, good relationship between the elderly and professionals, and adequate daily activities. The tenants also agreed that BRR should ensure that transport and medical assistance, a multi-purpose card for the elderly, and a supply of food bank be provided for the elderly. The retirement home tenants agreed that RHP depends on the increase in the number of tenants and check-in, food quality as well as facilities, and availability of equipment for basic health screening. The findings of this study have implications for enhancement of government-operated or privately-owned retirement homes.

Plastic bags have become synonymous with the culture of our society today. The use of plastic bags is very widespread and facilitates the consumers especially in facilitating them to carry goods such as supermarkets, retail stores, and others. Every year nearly 1 trillion shopping plastic bags have been used, as they are easy to carry, cheap, and convenient to use. But with constant use, it has had a negative impact not only on the environment but also on the logistics perspective. In response, the Malaysian government has launched a campaign to discourage the use of plastic bags known as a 'No Plastic Bag Day''. The objective of the program is to educate the consumer on the impact of plastic bags on the environment. However, this campaign has drawn a mixed response from the customer which is against the traditional practice of using a plastic bag as many of the customers still fail to bring their bag for packing their purchased items. As such, this study aims to investigate the impact of the campaign from the logistics perspective by examining the relationship between logistics challenges and customer awareness on the implementation of the campaign. This research used a quantitative method by distributing a questionnaire to understand the customer perspective toward the logistics challenges on the elimination of plastic packaging. A total of 132 questionnaires were completed and returned for analysis by SPSS. The findings of this study, contribute a significant impact on logistical challenges in terms of the safety of goods, material handling, and customer readiness on the implementation of the campaign. According to the inferential analysis that was conducted from the data collected, customer readiness was the best factor that influenced the level of customer awareness on the elimination of plastic usage for shopping. Whereas the variable of customer readiness and safety & security which are less than 0.05 shows a unique contribution to the dependent variable. Based on the current research, the recommendations that can be made for future research are by doing a mixed-method and expand the scope of the study to get a better understanding of the localized perception before developing the mass survey.

This study investigates the factors that influence customers' purchase intention among Bateriku.com customers. Through a self-administered questionnaire, data were collected from eighty-eight (88) customers who had experience using the service of on-site delivery of a car battery. This study is aimed to investigate perceptions of the customer on a new business model introduced by Bateriku.com for the purchase of the car battery and how this perception impacts the actual purchase that the customers make. This study will turn out to be a benchmark in comparing with the traditional purchase processes of the car battery and to understand the factors influencing the customers towards their purchase of the car battery using a new business process. Three (3) independent variables were identified namely technology, service marketing, and people to investigate its impact on actual purchase by employing multiple regression analysis. The results of the study indicated that service marketing has a significant influence on customer purchase intention for the car battery on-site delivery. The results also showed the impact of technology in improving customer confidence towards the new business model. The recommendations are also provided to Bateriku.com to exploit the advancement in technology to minimize further human interaction during the inquiry process to introduce process standardization for efficient operation. This study presents a foundational framework for future researchers to embark on new avenues in producing in-depth insights about new business models in acquiring car batteries and related services.

Supply Chain Performance refers to the extended supply chain's activities in meeting end-customer requirements, including product availability, on-time delivery, and all the necessary inventory and capacity in the supply chain to deliver performance responsively. The issue of inequality and extended consumption in supply and demand become crucial since the pandemic COVID-19. Plus, the increase of population enforces manufacturing to examine the sustainable effect to overcome the business impact. Therefore, anticipated with Sustainable Supply Chain Performance (SSCP) to plan an initiative of material scarcity to have a better performance in the supply chain to contribute to economic and social advantage. The objectives of this study; to investigate the level of SSCP in Material Scarcity Resources, to explore the implications of material scarcity resources for companies in structural scarcity towards sustainable supply chain performance and finally to investigate the impact of material scarcity resources in SSCP in environmental, economic and social in Malaysia. A total of 101 respondents among manager level from the southern region of Malaysia’s manufacturing industry was collected. The result showed that Material Structural Scarcity Resource has a positive effect on environmental, economic, and social performance in a sustainable supply chain. Thus, sustainable supply chain performance showed consistency in the performance into the material scarcity overcomes, reducing inventory which enhances the productivity, environmental initiatives advance into product innovation and cut costs reductions. As a result of the factor analysis in the components environmental legislation demand with 89.7% showed that the sustainable supply chain performance significantly improved on the stages of manufacturing, increase diversity of products, lowering manufacturing price, increasing market share, introducing new products rapidly and be the forefront of the future legislation demands. So, it is beneficial to the manufacturing industry companies in improving their performance and stabilizing the economic condition indirectly.

Process performance measurement is a significant and crucial activity carried out by organizations aiming at controlling their processes. Most of the traditional performance indicators do not include important factors such as the effects of the external constraints on the process and do not emphasize the economic aspects influencing an organization. An organization’s performance evaluation should measure both its efficiency and effectiveness, and not one or the other. The newly developed Total Process Performance (TPP) indicator is an integrated indicator that takes into account the process efficiency and effectiveness. This study modifies and integrates the efficiency and effectiveness of original formulae to create -for the first time- a customized new formula that includes important techno-economic factors representing a holistic overview of the process/organization performance. The study developed two indicators, a High (H) frequency indicator (early alarm), TPP|H which is calculated on hourly bases and intended for use by the floor managers, and a Low (L) frequency indicator, TPP|L that can be calculated for a longer period and intended to be used by top management. TPP|H reflects the shop floor’s real-time performance based on internal factors, while TPP|L reflects the company performance based on internal and external factors. The differences between the newly developed indicators and the traditional indicators are illustrated. A real-time performance monitoring system is also developed. A case study for applying the new indicators in an iron-making plant is introduced.

In healthcare, the Patient Appointment Scheduling (PAS) problem is one of the critical issues in Outpatient Chemotherapy Clinics (OCC). In the wake of this, this paper proposes a novel bi-objective mathematical programming model for solving the PAS problem in OCC. The developed mathematical model is inspired by cellular manufacturing. The first objective function minimizes the completion time of all treatments, and the second objective function maximizes the use of nurses' skills while considering clustered patients about their characteristics. To solve the bi-objective mathematical model, for the first time a hybrid approach based on Torabi-Hassini (TH) and Lagrange method is utilized. The results indicate that an increase in the number of nurses will enhance the treatment completion speed and allocation of nurses’ work skill. On the other hand, an increase in the number of chairs in clinics will decrease the assignments of nurses’ skills priority. The study supports decision makers in considering nurses' skills for the PAS problem. The results also denote the desirability of the proposed model. To validate the proposed model, OCC in Tehran is considered as a case study. Computational results reveal that considering nurses' skills in OCC and using the fuzzy clustering model, as a new method in patient clustering, lead to achieving a desirable and more realistic outcome.

Copula is a favored method used to measure dependency for financial data due to its flexibility. Yet, studies about dependence structure between bivariate data especially by using time-varying copula approach is very limited. Hence, this paper will examine the dependency between KLCI-FBMHS pair by considering static and time-varying copula. Traditionally, ARCH model is used to measure the volatility. However, it failed to capture stylized facts that usually exist in financial data such as the volatility clustering and leverage effect. Thus, the study also investigates the effect of different marginal models (GARCH and EGARCH) towards dependence structure and parameter estimations. Generally, the findings reveal that KCLI-FBMHS pair have strong dependency. In addition, this study highlight that ARMA(1,0)-GARCH(1,1) and ARMA(1,0)-EGARCH(1,1) with student t distribution are well-fitted to both (KLCI and FBMHS) series, the KLCI-FBMHS pair have similar dependence structure for both static and dynamic copula models.

Land administrators play a significant role in enabling sustainable development; however, there is a scarcity of debates concerning soft skills competency in relation to the systems, laws and procedures. Moreover, insufficient information has been provided through past research that has targeted the development and validation of the core competencies of land administrators. The purpose of this study was to develop a land administrator personal competency model to measure the skills, attitudes and abilities involved in the performance of land administration. Land administrators’ competencies were assessed in terms of how reliable and valid they were through reliability analysis and exploratory factor analysis (EFA). Via a questionnaire distributed online, descriptive research of the Johor Land Administration, Malaysia, was undertaken between May and July 2021. Forty-two items from three competencies – skill competencies, attitude competencies and ability competencies – were designated as the initial instrument for a new conceptual model based on the Land Administrator Personal Competency Model. The results showed that all three competencies of the instrument had high reliabilities (all had Cronbach’s alpha values ± > .907). EFA revealed that the three factor-structures of skills, the three factor-structures of attitudes as well as the two factor-structures of abilities explained 63.828%, 63.074% and 62.364%, respectively, of the variance in the pattern of relationships among the items. All the factor-structures of the land administrator personal competencies instrument were confirmed through this study. With this information, the model developed might be useful for obtaining further information about land administrators’ levels of performance through measurements of competencies involving the skills, mental approach and capability they display.

This manuscript examines the two-machine open shop scheduling problem where the latter a job is scheduled the longer it takes to process this job. The performance is measured by minimizing the makespan. By modifying existing algorithms for the corresponding problem with fixed processing times, two new algorithms are developed for the problem under consideration. The proofs of optimality of both algorithms are presented. The execution of these algorithms is illustrated by two numerical examples. Finally, both algorithms are further modified to solve a more generalized problem where the time demanded to process a job is a general linear function of its beginning time.

Stable economy status has made many foreign investors invested in various industries sectors in Malaysia. Therefore, rapid development of industrial sector has caused the energy demand to increase tremendously year by year. To continue attract foreign investors, Malaysia has taken various efforts to maintain economic stability by developing a sustainable energy sector to ensure electricity demand is sufficient for industries with less cost, reliable supply, and also less impact to the environment. However, over dependence on fossil fuels as the main energy source could not guarantee the energy security and also could evoke issues of environmental problem mainly the increase in carbon dioxide (CO2) emission in the atmosphere. In this study, a linear programming model and mixed integer linear programming optimization model under carbon constraints was developed to address issue of rising atmospheric concentrations of CO2 from energy sector. The developed model was able to determine the optimum energy sources mix which is most economical and to satisfy the forecasted electricity demand at Tanjung Bin Power Station (TBPS) in Iskandar Malaysia region. The model includes energy source switching and analyzing different renewable energy technologies such as biomass system, biogas system, solar thermal and photovoltaic (PV) plant in power generation. The applicability of the model was tested on various CO2 emission reduction targets which is at 6, 25, 40 and 50 % under several scenarios either without or with government subsidy. The results in this study indicated that the optimum energy source mix for TBPS is the mix of coal and solar energy (mainly solar thermal for without government subsidy and solar PV for with government subsidy). The results show that with government subsidy, the electricity tariff was acceptable for the consumers. The average electricity tariff at 6, 25, 40 and 50 % CO2 emission reduction is RM 0.35, RM 0.44, RM 0.51 and RM 0.57 per kWh, respectively. Increase of CO2 emission reduction show increase in electricity tariff compared to current tariff at RM 0.21 per kWh. Finally, by applying energy source switching, TBPS can significantly reduce CO2 emission by avoiding 1.00 Mt of CO2 emission at 6 % of CO2 emission reduction, 4.14 Mt of CO2 emission at 25 % of CO2 emission reduction, 6.63 Mt of CO2 emission at 40 % of CO2 emission reduction, and 8.28 Mt of CO2 emission at 50 % of CO2 emission reduction by 2030.