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Industrial and Systems Engineering - Volume:13 Issue: 2, Spring 2021

Journal of Industrial and Systems Engineering
Volume:13 Issue: 2, Spring 2021

  • تاریخ انتشار: 1399/11/20
  • تعداد عناوین: 15
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  • Ehsan Moghimihadji * Pages 1-8
    Failure rate curve based on the failure rate function of many electrical and mechanical systems shows a bathtub-shape form. In the first phase of this curve, where the failure rate has a decreasing form with a high slope, manufacturers use the burn-in method to eliminate defective products before reaching the market. In this phase most of the failures are minor (since the component is completely new, this type of error generally takes happen because of bad assembling, displacement of a socket, and so on) or major type failures (for example because of wrong design, selecting unsuitable raw materials, and so on). In the second phase, where the failure rate curve shows a constant value, manufacturers offer warranty services to their customers to ensure them about the quality and performance of their products. In this paper, we investigate the total cost incurred during the burn-in and warranty periods from the manufacturer's point of view. We consider different types of repair services and obtain the expected total cost in each phase. We present an optimization example to illustrate the efficacy of the proposed model in finding optimal values for burn-in and warranty periods.
    Keywords: failure rate, burn-in, non-renewing warranty, minimal repair, general repair
  • Taha Keshavarz * Pages 9-26
    In this research, the problem of scheduling a single batch processing machine with non-identical job sizes is considered. The objective is to minimize the total earliness and tardiness of all the jobs. A batch processing machine can process a group of jobs simultaneously as a batch as long as its capacity is not violated. The processing time of a batch is equal to the maximum processing time of all the jobs in the batch. Since the problem under study is shown to be NP-hard, a lower bounding method based on column generation is proposed. The proposed lower bound can be used for evaluating the performance of the heuristic and metaheuristic algorithms developed for the research problem. The computational experiments are designed to analyze the performance of the proposed lower bound. The results show that the column generation approach can considerably generates better lower bound than the best known lower bounding method in the literature.
    Keywords: Batch processing machine, just-in-time, lower bound, column generation
  • Bahareh Shafipour Omran *, Kaveh Khalili Damghani, Peiman Ghasemi Pages 27-48

    Supply chain problems have many ambiguous parameters, and decisions about these types of problems, which are usually multi-objective, should be made according to the constraints and priorities of the objectives. In this paper, we will examine the integrated model of supply chain network with supply, production and distribution levels, considering the logistics costs and service level simultaneously under uncertainty. In multi-objective Mixed Integer Linear Programming (MILP) model, objectives are considered as fuzzy and with different priorities and to eliminate the ambiguity in membership values of fuzzy objectives, priorities are adjusted with fuzzy relations. The model is solved by two approaches of Fuzzy Goal Programming (FGP) and their results are compared. Presenting a multi-period multi-level multi-product multi-objective model in the field of designing and distribution of supply chains and presenting two methods of fuzzy goal programming and the results are compared to provide a suitable method to convert the proposed model into a fuzzy model are the contributions of this paper. The computational results show that the first method in the criterion of cumulative weight of fuzzy membership values ​​and the second method in determining the cumulative weight of ambiguous preferences of decision-maker have had a good performance. The results of ANOVA and Mann-Whitney tests, show that  of all three criteria is less than acceptable level (0.05) and e first method had a good performance in determining the criterion of membership value of cumulative weight of fuzzy objectives.

    Keywords: Supply chain, Uncertainty, fuzzy goal programming, fuzzy preference relations
  • Mahmoud Jangali *, Ahmad Makui, Ehsan Dehghani Pages 49-64

    The increase in demand for petroleum derivatives such as engine oil has contributed to not only the rapid and adequate response to them, but also attracting many managers and researchers to control their adverse environmental impacts. In this regard, this study unveils an optimization model to develop a closed loop supply chain network for engine oil in an uncertain environment. In the concerned model, in addition to addressing supply chain costs, adverse environmental effects are also minimized. To solve the proposed multi-objective model and acquire Pareto optimal solutions, the goal programming approach is deployed. The demand and amount of recyclable materials are considered to be imbued with uncertainty, which a robust optimization approach is devised to capture it. Likewise, new methods are taken into account to recycle engine oil, being capable of supporting both economic and environmental benefits. Lastly, a case study is utilized to evaluate and validate the presented model, through which outstanding management results are derived.

    Keywords: Closed loop supply chain, Environmental effects, Uncertainty, robust optimization, Goal Programming
  • Mahdi Hampaeyan, Vahidreza Ghezavati *, Davood Mohamaditabar Pages 65-83
    We aim to plan better scheduling for movement of shuttle trains on the single-line route of inter-city railway network to decrease the delays due to the trains blocking in successive crowded stations. A MINLP model is examined to increase capacity efficiency of the stations using the queuing theory considering blocking. We propose an optimal schedule for moving trains which minimizes the blocking probability to raise the profit gained on a two-way railway. The results show that we have achieved the best scheduling with lowest delays considering the constraints of the track number inside stations. Queuing models are applicable because the trains’ departure scheduling can be evaluated with the aid of the performance criteria obtained by the queuing model. To validate the model, an optimal schedule is proposed for a real case-study in Iran. Finally, the benefits of the model and sensitivity analysis are conducted using GAMS v24.9.1, with BARON solver.
    Keywords: Inter-city network of railway, trains departure scheduling, railway stations capacity, queuing theory approach, blocking, train prioritization
  • Maryam Ghobadi, Jamal Arkat *, Hiwa Farughi, Reza Tavakkoli Moghaddam Pages 84-104

    The hypercube queuing model is a descriptive model for emergency systems in which servers are mobile and serve customers at their locations. In emergency systems, the service time of each server includes the travel time from the server station to the customer's location, the on-scene time and the travel time from the customer's location to the server station. The on-scene service time depends on factors such as server expertise and the severity of the customer’s situation while the travel times depend on factors such as vehicle type, the path, and the traffic volume. Therefore, it is necessary to consider and analyze these two times separately. In the hypercube queuing model presented in this study, the service time is divided into two sections, the travel time and the on-scene service time, both of which follow independent exponential distributions with known rates. A new system state is defined in which the status of servers is classified into idle, serving at the customer's location and traveling. By solving the equilibrium equations with the Gaussian- Elimination method (for small size examples) and simulation (for larger examples), limiting probabilities are obtained, and performance measures (such as the ratio of the on-scene time to the total server busy time) are evaluated. A case study of the road emergency stations of the Red Crescent, which are based in Hamadan province, Iran, is also used to check the model's real-world performance.

    Keywords: Emergency systems, hypercube queuing model, Performance Measures, discrete event simulation
  • Masoud Rabani *, Elham Moazam, Niloufar Akbarian Saravi, Hamed FarrokhinAsl Pages 105-120

    Designing a biofuel supply chain plays an important role in the reduction of biomass transportation costs. This study aims to present a comprehensive decision support tool (DST) for designing of the integrated biodiesel supply chain (BSC). In addition, so far no research has been found that examined hybrid first/second generation of biodiesel with considering all economic, environmental and social costs. In achieving this goal, we developed a new optimization model using mixed integer linear programming with the objective of maximizing the total profits of BSC incorporating environmental and social costs.  To do so, practical constraints including the limit of biomass, the capacity of technologies, the land availability, and especially limited capacity of each transportation vehicles are applied to this mathematical model. The main purpose of this study is to develop a DST to evaluate the commercial feasibility of BSC with focusing on multimodal and reliable transport.  To illustrate the capability of the proposed model, Iran is considered as a real application. The findings of this study indicate that some factors such as biomass availability, transportation reliability, and biofuel price can play as a pivotal role in this supply chain design and optimization. All in all, 31% increase in amount of produced biodiesel leads a marginal increase in environmental-related costs.

    Keywords: Decision support tool, biodiesel supply chain, multimodal transport, mixed integer linear programming, hybrid first, second generation
  • Fatemeh Akbari, Elnaz Osgooei * Pages 121-133
    In real world, many decisions are made at any given moment, usually with uncertainty. Although there are many ways and tools to overcome these uncertainties, a powerful tool can be Z-numbers. In this study, inspiring Otadi-Mosleh and Big-M method, an extended model is proposed to solve the Z-number matrix equation. Also, numerical examples are provided to show the performance of this model.
    Keywords: Fuzzy concept, Z-number, Big-M method, matrix equation
  • Mahdieh Ghorbani Kuhbanani, Hossein Sayyadi Tooranloo *, Mostafa Hadavinejad Pages 134-154
    In today's world, considering the concept of e-government with the aim of increasing the efficiency of public management and the necessity of providing a foundation for balancing in the economic, social and environmental fields, presentation of a suitable model for the realization of a sustainable e-government in the context of the situation of a country's needs. In this regard, the purpose of this study was to identify the factors affecting the implementation of sustainable e-government in Iran, as well as designing an interpretive structural model based on the knowledge of experts on the phenomenon studied. To do this, after studying the literature and identifying the factors affecting the implementation of sustainable e-government, a matrix questionnaire was designed and distributed among 15 experts selected by targeted sampling. By analyzing the data, the factors affecting the implementation of sustainable e-government were classified in 7 levels (level one: legal requirements; second level: cultural management and strategic management; third level: financial management; fourth level: infrastructure management and human resource competence management; fifth Level: Service Management, Electronic Information Management and Event Management; Sixth Level: Citizenship e-Readiness; and Seventh Level: Citizens' Communication Management).
    Keywords: E-Government, Sustainability, sustainable e-government, structural-interpretive modeling
  • Ehsan Vaezi, Seyyed Esmaeil Najafi *, Seyed Mohammad Hajimolana, Farhad Hosseinzadeh Lotfi, Mahnaz Ahadzadeh Namin Pages 155-178
    In this paper, we investigate the production planning and warehouse layout for an authentic case, in which, a factory usually faces a challenge in the quest for sufficient space for produce and the management of warehouse items. We consider a network comprising of a production area, a warehouse area and a delivery point area and to solve this problem an integrated model for the produce and warehouse management has been rendered. We contemplate on a mixed integer, nonlinear model programming, targeting at minimizing total production costs, set-up costs, warehouse reservation and storage costs, transportation and delay penalty costs for this problem; besides which, the  issue of perishable goods is also under consideration. Morever, we utilized the data envelopment analysis (DEA) to measure the efficiency of the model results. This factory is taken into consideration as a dynamic network and a multiplicative DEA approaches are utilized to measure efficiency. Given the non-linearity of the models, a heuristic method is used to linearize the models. The ranking results of the dynamic network under study, demonstrated that, the time periods namely, (24) and (1) were the best and the poorest periods, respectively, in terms of efficiency.
    Keywords: Multi-product planning, multi-period planning, warehouse layout, Data Envelopment Analysis, three-stage process, cooperative approach
  • Tina Hadi, Majid Sheikhmohammady *, Seyed Kamal Chaharsooghi, Ashkan Hafezalkotob Pages 179-199
    Governments apply economic incentives and penalties to manage environmental effects of enterprises. Market demands is considered in this research such that non-green and green products can be substituted with each other. We study the competition between two supply chains (SCs) in the market which are called regular and closed-loop SCs. We then formulate a game theoretical model in two scenarios based on collaboration in closed-loop SC and the selling prices, prices of raw materials, and profit of SCs in each scenarios. Numerical examples are presented to make  results of the models more tangible. The effects of main parameters of the models are also evaluated through a sensitivity analysis. The results indicate that collaboration between recycler and retailer in the closed-loop SC has significant impact on the profits of the SC’s members. Moreover, the profits of SCs in collaboration between recycler and retailer is higher than non-collaboration scenario.
    Keywords: Closed-loop supply chain, Competition, game theory, government intervention, Recycling, Stackelberg game
  • Zahra Sadat Seyyedzadeh, MohammadSaeed Jabalameli *, Ehsan Dehghani Pages 200-222

    Emergency medical services (EMS) is responsible for pre-hospital care, playing a prominent role in saving lives from death as well as serious damage to their health. In view of the threat of disruptions to the network components and the risk of parameter uncertainties in the real world, it is incumbent upon render expedient EMS systems. In this regard, this paper unveils a two-phase approach based on data envelopment analyses and robust scenario-based mathematical model to design EMS network in an uncertain environment. The first phase applies a data envelopment analysis (DEA) to determine more valid and practical points for candidate locations. In the second phase, the strategic and tactical decisions of the concerned EMS is determined. Inasmuch as the marginal demand areas and patients with emergencies, the concerned model takes into account the location of air ambulance bases in such a way that for transferring patients by air ambulance to hospitals, hospitals are equipped with helipads. The unbiased considerations are also addressed by minimizing the transfer time to the farthest demand areas. Likewise, in a bid to better allocate emergency facilities to patients and the patients to appropriate hospitals with their physical condition, categorizing the type of disease for patients is carried out. Lastly, a real case study of the EMS system of Ahvaz city in Iran is exploited, via which outstanding managerial insights are attained.

    Keywords: Emergency Medical Services network design, robust optimization, transfer points location
  • Raheleh Moazami Goodarzi, Fardin Ahmadizar *, Hiwa Farughi Pages 223-244
    In this paper, a new integrated mathematical model for production and distribution planning is presented to minimize tardiness and transportation costs. A mixed-integer linear programming (MILP) formulation is developed for the problem which consists of two parts. First, the production scheduling in a hybrid flow shop (HFS) environment with identical machines in each stage, and then, the delivery of completed jobs with a fleet of vehicles that have the same capacity. Due to the NP-hard nature of the problem, a new metaheuristic approach based on Particle Swarm Optimization Algorithm (PSO) and Genetic Algorithm (GA) is presented to solve the integrated problem. GA’s operators are used to update the particle position of the PSO algorithm. The algorithm uses dispatching rules to represent the initial solution and searches in the solution space including active schedules. To investigate the efficiency and effectiveness of the proposed method, numerical studies are carried out with random problems. The computational results show that the proposed solution approach yields fairly good results in comparison with the PSO versions in the subject literature. The algorithm is capable of generating relatively good solutions for sample cases.
    Keywords: Integrated production, distribution scheduling, hybrid flow shop, vehicle routing problem, Particle Swarm Optimization Algorithm, Genetic Algorithm
  • Masoud Rabani *, Dorsa Abdolhamidi, Mahdi Mokhtarzadeh, Soroush Fatemi Anaraki Pages 245-263

    Proper transportation and distribution of commodities plays a pivotal role in the expenditures of supply chains. In this paper, a clustered vehicle routing problem with pick-up and delivery is studied. A fleet of distinct vehicles is concurrently responsible for distribution of medicines and collection of their wastes. Collected wastes should be sent to a waste center. To solve the problem, a bi-objective mathematical model is presented. Fairness of travelled distances among drivers and transportation expenses are two objective functions considered in the model. Since the proposed problem is NP-hard, a three-step hybrid approach is developed to solve the problem. First, K-medoids clustering algorithm allocates customers to subsets based on their coordinates. Second, a mathematical model is used for routing vehicles within each cluster. Third, NSGA-II is used to produce final result using the outcome of step 2. Extensive numerical results indicate the superiority of the proposed approach against the NSGA-II.

    Keywords: VRP, Fairness, delivery to disposal center, Clustering, NSGA-II
  • Arash Apornak *, Sadigh Raissi, MohammadReza Pourhassan Pages 264-276

    In this paper, an efficient approach for production line policy and planning problem is presented. Here, all of activities are simulated by incorporating learning effects using historical data. After validation process, “what if analysis” is carried out for different scenarios derived from the Taguchi method. Several performance measures estimated for all simulation runs. Then for such homogenized multi-criteria problem, data envelopment analysis (DEA) is used to select the preferred policy. In order to show the applicability of the proposed approach, the data for a series production line is used. Results show that the proposed approach could help managers to identify the preferred strategy considering and investigating various parameters and policies. Finally this study introduces an integrated multi-criteria approach for optimum maintenance policy and planning. In this algorithm, many relevant parameters cover any uncertainty using statistical distribution. We used DEA as a multi-criteria decision making techniques to seek more appropriate assignment. Therefore, using a combination of computer simulation model and an attribute-deductive tool such as DEA, a near optimal solution can be achieved.

    Keywords: Flexible flow-shop, Computer Simulation, Data envelopment analysis (DEA), Taguchi method