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Industrial and Systems Engineering - Volume:11 Issue: 1, Winter 2018

Journal of Industrial and Systems Engineering
Volume:11 Issue: 1, Winter 2018

  • تاریخ انتشار: 1396/12/20
  • تعداد عناوین: 16
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  • Asefeh Hasani Goodarzi, Nasim Nahavandi *, Seyed Hessameddin Zegordi Pages 1-23
    This study addresses the pickup and delivery problem for cross-docking strategy, in which shipments are allowed to be transferred from suppliers to retailers directly as well as through cross-docks. Usual models that investigate vehicle routing in cross-docking networks force all vehicles to stop at the cross-dock even if a shipment is about to a full truckload or the vehicle collects and delivers the same set of products. In order to eliminate unnecessary stops at the dock, and thus reduce transportation costs, the designed model tries to decide about the best approach to deliver orders to retailers in a tailored network. In such a system, two objectives are taken into account: minimization of the total transportation cost and minimization of the total earliness and tardiness of visiting retailers. In order to deal with this problem, three multi-objective algorithms are developed. An evolutionary algorithm based on multi objective imperialist competitive algorithm (MOICA) is proposed, and the associated results are compared with the results obtained by non-dominated sorting genetic algorithm (NSGA-II) and Pareto archived evolution strategy (PAES) in terms of some metrics. The computational results show the superiority of the proposed algorithm compared to other algorithms in some metrics.
    Keywords: cross-docking, vehicle routing problem, Bi-objective mathematical model, time windows
  • Ata Allah Taleizadeh *, Naghmeh Rabie Pages 24-49
    The members of a chain always try to find new ways in order to raise their profit. Hence we intend to study two different scenarios in a single item two-echelon green supply chain including two manufacturers and one retailer to study the effects of two effective contracts on members’ profit. Two scenarios are discussed and in first one, first manufacturer proposes quantity discount contract to retailer and in second scenario retailer proposes cost sharing contract to second manufacturer. Then a numerical example and sensitivity analysis is implemented to review the mathematical relations in detail and assess the effect of some parameters on our decision variables and profits. The results show that cost sharing contract is more beneficial for retailer and second manufacturer than quantity discount contract.
    Keywords: Green supply chain, greening level, quantity discount, cost sharing
  • Mehran Abbasi, Mir Saman Pishvaee * Pages 50-73
    This article aims to investigate the location of dry ports by providing a two-stage GIS-optimization model. At the first stage, the appropriate points for establishing dry ports were identified using GIS and hierarchical analysis process; then, the suitable points were introduced as the potential points to the second stage model. At the second stage, by providing a multi-objective integer model, the location of the port and the transportation modes used to transship the goods from/to the dry port are investigated. Finally, the model is linearized using a heuristic method and, then, is developed using its robust counterpart in order to deal with the uncertainty in the model parameters. To investigate the performance of the model, the problem was solved using GAMS software for the case study of Iran. The obtained numerical results indicated that the use of the developed model and establishment of the dry port led to the reduced costs, reduced variable environmental effects of the seaport, improved accountability to the customers of these ports, and consequently increased competitiveness.
    Keywords: dry port, multi-modal transportation, Geographic information system (GIS), robust optimization, logistics planning
  • Hamid Tikani, Mahboubeh Honarvar *, Yahya Zare Mehrjerdi Pages 74-96
    In this paper, a stochastic programming approach is applied to the airline network revenue management problem. The airline network with the arc capacitated single hub location problem based on complete–star p-hub network is considered. We try to maximize the profit of the transportation company by choosing the best hub locations and network topology, applying revenue management techniques to allocate limited perishable capacity and provide booking limits for all itineraries and fare classes. In order to characterize the uncertainty of demand in the airline market, we introduce stochastic variations caused by seasonally passengers’ demands through a number of scenarios. The proposed model deals with finding the location of hub facilities, the assignment of demand nodes to these located hub facilities and allocating the limited capacity of aircraft seats on each rout to different customer classes in order to maximize the profit. Due to the computational complexity of the resulted model, a hybrid algorithm improved by a caching technique based on standard genetic operators is used to find a near optimal solution of the problem. Numerical experiments are carried out on the Turkish network data set. The performance of the solutions obtained by the proposed algorithm is compared with the pure GA and Imperialist Competitive Algorithm in terms of the computational time requirements and solution quality.
    Keywords: Revenue Management, scenario generation methods, Stochastic programming, Hub Location, seat inventory control, evolutionary algorithms
  • Majid Soolaki, Jamal Arkat* Pages 97-112
    Nowadays, in highly competitive global markets and constant pressure to reduce total costs, enterprises consider group technology and Supply Chain Management (SCM) accordingly and usually separately as the key elements for intra and inter facilities improvement. Simultaneous consideration of the elements of these two disciplines in an integrated design can result in higher efficiency and effectiveness. A three-echelon supply chain that has several markets, production sites, and suppliers is designed again in this paper as a Cellular Manufacturing System (CMS). Every product can be manufactured in the CMS through alternative process routings, in which machines are likely to fail. A linear integer programming model is presented here that seeks to minimize the intercellular movement, procurement, production, and machine breakdown costs. We present a number of illustrative examples to demonstrate the effectiveness of the integrated design. The proposed examples reveal that although the procurement and logistics costs increase slightly in the integrated design, the total cost is dropped considerably.
    Keywords: Supply chain management, location allocation problem, cell formation problem, alternative process routing
  • Ali Ghavamifar, Fatemeh Sabouhi, Ahmad Makui * Pages 113-126
    Due to occurrence of unexpected disruptions,a resilient supply chain design is important. In this paper, a bi-objective model is proposed for designing a resilient supply chain including suppliers, distribution centers (DCs), and retailers under disruption risks.The first objective function minimizes total costs. The second objective function maximizes satisfied demands. We use the augmented e-constraint method to solve the bi-objective problem. In the proposed model, the possibility of partial disruptions of DCs as well as complete disruptions of connection links between distribution centers and retailers is considered. In order to reduce risk, resilience strategies including, using multiple sourcing, direct shipment of products from suppliers to retailers, and lateral transshipment between distribution centers are used.We utilize a two-stage stochastic programming method to deal with disruption risks. The decisions of the first stage of the method consist selection of suppliers and location of DCs while the decisions of the second stage include integrated programs for supply and distribution of products. The validity of the proposed model is then evaluated by introducing a numerical example and performing different sensitivity analyses on it.
    Keywords: resilient supply chain, Supplier selection, Two-stage stochastic programming, Lateral transshipment, multiple sourcing
  • Sayeh Foladi-Mahani, Saeed Yaghoubi *, Seyyed-Mahdi Hosseini-Motlagh, Mohammadreza Nematollahi Pages 127-146
    Drug has a great and crucial role inboth the health systems and the quality of life, and thereforeits shortage can cause death.In order to the important role of drugs,pharmaceutical supply chain(PSC) shouldensure that drugs are delivered to people in the right time with the best quality.On the other hand, thesupply chain (SC) members depend on each other for resources and information, and it has increased in recent times due to outsourcing, globalization and rapid innovations in information technologies. This increase brings some extent of risk and uncertainty along with benefits for them and so, SC coordinationis a crucial issue. Thispaper studies a PSCmodel witha single active pharmaceutical ingredientsand a single finish pharmaceutical product. For this purpose, decentralized and centralized structures are investigated. Then,a coordination mechanism is developed based on the buyback contract in order to encouragethe SC members to make decision by considering each other's profit to simulate the condition of decentralized SC versus centralized one.In order to demonstrate the effect of the proposed coordination model, numerical examples and sensitivity analysis are provided. The results show that by applying buy back contract, in coordination structure the order amount of raw material and the profits of the pharmaceutical supply chain will increaseso it can effect on the amount of manufacturing orders.By using buy back contract, the profit of each SC member increasesin comparison with the decentralized decision-making structure.
    Keywords: Supply chain coordination, buy back contract, pharmaceutical products
  • Hamidreza Feili *, Reihaneh Besharat, Mohammadreza Chitsaz, Shahrzad Abbasi Pages 147-162
    Wheat is one of the most strategic agricultural products, which has always been a significant issue for the government. The main purpose of this study is to review the policy of purchasing wheat on the welfare of producers and customers in Iran. Due to the significance of wheat in consuming model of Iranian families, this product has been permanently under consideration. The government grants a subsidy to wheat consumption within the framework of inexpensive food policy and implements price setting support policies, a subsidy to products and insurance for wheat production. Furthermore, it is the exclusive buyer and seller of wheat in the country. Considering endurance of performance and ever-increasing expenses for the supporting plans for wheat producers and consumers, our goal in this paper is to evaluate and study the impact of such policies on the welfare of producers and consumers. To gain such objective, a mathematical model has been developed. The fulfilled policies in the period from 2005 to 2016 were the basis of the present study. The results of this study demonstrate that less role of government in the arrangement and context of wheat supply chain and broader support for production may lead to more solidarity of wheat production. Therefore, we should move toward privatization and liberate wheat market. However, this point should be regarded that it is better to conduct market to the more dynamic condition by appropriate policies rather than consuming energy and resources of the government. For instance, the government should forecast price of wheat in the next year by making use of comments and researchers of experienced economists instead of specifying the price of wheat for trades, and announce a price slightly less than this price as a guaranteed price.
    Keywords: Wheat, Policy of Purchasing, Welfare, Producers, Consumers of wheat, Pricing
  • Ehsan Dehghani, Mohammad Saeed Jabalameli *, Mir Saman Pishvaee, Armin Jabarzadeh Pages 163-179
    The solar photovoltaic (PV) energy is one of the most promising sources of energy, which has attracted many interests. Itis potentially the largest source of energy in the world and is capable to mitigategreenhouse gas (GHG) emissions significantly in comparison with fossil fuels.Location optimization of solar plants can play a vital role to rise the efficiency and performance of the solar PV systems. In this regard, this study aims at evaluating different areas for solar plants according to a set of social, geographical and technical criteria through adata envelopment analysis (DEA) model. The proposed DEA model considers both information of the efficient and anti-efficient frontiers in order to rise discrimination power in DEA analysis. The proposed approach is evaluated and validated via studying a real case study in Iran. The extracted results reveal the usefulness and applicability of the proposed DEA model in choosing appropriate locations for solar plants.
    Keywords: data envelopment analysis, Efficient frontier, anti-efficient frontier, photovoltaic, solar plant
  • Ali Asghar Miri, Hamideh Razavi * Pages 180-204
    Facility layout problems have been generally solved either hierarchically or integrated into other phases of plant design. In this paper, a hybrid method is introduced so that clustering and facilities layout can be simultaneously optimized. Each cluster is formed by a group of connected facilities and selection of the most appropriate cluster configuration is aimed. Since exact method by MIP is limited to small problems, a heuristic algorithm including constructive and improving phases is developed. In order to enhance the performance of the algorithm, systematic generation of intersection points inside available area together with shaking, split groups and Tabu list techniques are used.Then, two different examples are presented and the comparison of the results supports the merit of the proposed algorithm. For further validation, 18 test problems are solved both by the proposed algorithm and MIP by CPLEX. Comparison of the results reveals that for up to 13 facilities, the best solutions of the algorithm are equal to optimum solution of MIP but achieved in shorter times. For larger problems with higher number of facilities, even though processing times for MIP is much longer, in almost all cases, it cannot produce the best solutions of the proposed algorithm.
    Keywords: Facility layout problem, Heuristic Algorithm, cluster configuration, unequal facility sizes
  • Kaveh Khalili-Damghani *, Mahboobeh Molayee Pages 205-222
    The detection and governmental punitive agency is responsible for supervision on correct implementation of the business laws in Iran. Several criteria are involved in performance assessment of detection and governmental punitive agency. The interaction between criteria and sub-criteria may occur in real situations. Moreover, the performance measurement should be accomplished in a multi-period horizon in order to detect the correct perception of the functionality of the organization. So, in this paper a hybrid approach based on DEMATEL, ANP, and DEA-based Malmquist Productivity Index is proposed measure the performance of detection and governmental punitive agency. First, DEMATEL is used to detect the network of interactive criteria through cause and effect relations. Then, the relative importance of the criteria is calculated using ANP method. Finally, a DEA approach is used to evaluate the productivity of alternatives with multiple inputs and outputs during several planning periods while the relative importance achieved from ANP are also considered as constraints of the system. The proposed approach is used at Detection and Governmental Punitive Agency in all provinces in Iran. The results show that the proposed method is able to assess the performance of a service organization while the assessment is accomplished during multiple periods and the organization is compared with technological progress of the industry as well as its historical technical performance. The proposed method is able to identify the complex relations of criteria, prioritizing the criteria, and assess the performance of service organizations due to technical change and technological change during multiple periods.
    Keywords: data envelopment analysis, DEMATEL, Analytical network process, Malmquist productivity index
  • Hasan Bagheri, Samaneh Babaei Morad Babaei Morad, Javad Behnamian * Pages 223-243
    In this paper, a model is presented to locate ambulances, considering backup facility (to increase reliability) and the restriction of ambulance capacity. This model is designed for emergencies. In this model the covered demand for each demand point depends on the number of coverage times and the amount of demand. The demand amount and ambulance coverage radius are consideredfuzzy in various periods, with respect to the conditions and application of the model. Ambulances have the ability to be relocated in different periods. In this model we have considered two types of ambulances to locate: ground and air ambulance. Air ambulances are considered as backup facilities. It is assumed that ground ambulances are major facilities, taking into account capacity limitations. To solve this model, making chromosomes (initial solution) is presented in such a way that location chromosome for both ground and air ambulances are appears as a general chromosome. Since this is a complicated model, apopulation-based simulated annealing algorithm (MultipleSimulated Annealing) with a chromosome combinatorial approach is used to solve it. Finally, the results of the algorithm presented to solve the model are compared with the simulated annealing (SA) algorithm. The results showed that the quality of the presented algorithm (MSA) is better than the SA algorithm.
    Keywords: Backup covering location, fuzzy dynamic location, Ambulance location, Reliability, Capacity constraints, Multiple simulated annealing
  • Reza Eshtehadi, Mohammad Fathian*, Mir Saman Pishvaee, Emrah Demir Pages 244-257
    Emissions resulted from transportation activities may lead to dangerous effects on the whole environment and human health. According to sustainability principles, in recent years researchers attempt to consider the environmental burden of logistics activities in traditional logistics problems such as vehicle routing problems (VRPs). The pollution-routing problem (PRP) is an extension of the VRP which consists of routing a number of vehicles to serve a set of customers and determining their speed on each route segment so as to minimize a function of comprising fuel, emissions and driver costs. This paper proposes an adaptive large neighborhood search for the robust PRP (RPRP) under demand uncertainty. The achieved results indicate a premium performance of the solutions obtained by the proposed robust models.
    Keywords: Green vehicle routing, pollution-routing problem, robust optimization, Metaheuristic Algorithm
  • Donya Rahmani *, Morteza Hajipour, Naser Safaie Pages 258-269
    In this paper, the optimizations problems to seek robust solutions under uncertainty are considered. The light robust approach is one of the strong and new methods to achieve robust solutions under conditions of uncertainty. In this paper, we tried to improve the quality of the solutions obtained from the Light Robust method by introducing a revised approach. Considering the problem concerned, an algorithm was also developed to properly choose the weight parameter in the proposed approach presented as much as possible. In addition, the data obtained from the proposed approach were investigated using the regression analysis. The results indicate that increased ratio of the number of constraints to the number of variables is directly correlated with increased likelihood of improving the quality of the solution. In conditions where the proposed approach has provided a solution better than the solution presented by the simple Light Robust approach, the mean value of the improvement accounts for about 9%.
    Keywords: robust optimization, light robust, uncertainty
  • Neda Manavizadeh *, Iman Moayedi Pages 270-286
    Industrial hazardous materials (hazmat) are byproduct of industrial production and include hazardous goods, such as flammable, toxic and corrosive materials that pose a risk to the environment.Hazardous waste management includes collection, transportation, treatment, recycling and disposal of industrial hazardous material in an organized manner. With the increasing industrialization of countries, the issue of waste management is more important than before. Therefore, the main purpose of this research is to optimize locations of recycling centers and routing hazardous. The methods used to solve the mathematical model include the ε-constraint method and the NSGA II algorithm.First, we examine the validation of proposed model. Then, the optimal values of the parameters of multi-objective meta-heuristic algorithm are determined by Taguchi approach and the proposed algorithms are used to solve the given problem for 19 examples with different sizes. Finally, two algorithms are compared based on the fiveidentified criteria. In addition, the run time for both methods was calculated and large-scale results were presented based on the multi-objective genetic algorithm. The results show the efficiencyofmulti-objective genetic algorithm in solving given problem, and in particular for problems with larger sizes.
    Keywords: Multi-objective location-routing, hazardous waste management, multi-objective model
  • Reza Yazdanparast *, Mahdi Hamid, Mohammad Ali Azadeh, Abbas Keramati Pages 287-309
    Human error is a significant and ever-growing problem in the healthcare sector. In this study, resource allocation problem is considered along with human errors to optimize utilization of resources in an emergency department. The algorithm is composed of simulation, artificial neural network (ANN), design of experiment (DOE) and fuzzy data envelopment analysis (FDEA). It is a multi-response optimization approach to optimize human error, cost, wait time, and patient safety, and productivity. Skill, rule, and knowledge (SRK) based approach is used to model human error. Simulation is applied to determine the relationship between human resource utilization and human error. It is also used to model SRK behavior. ANN is utilized to predict response variables. FDEA is used to identify the optimum scenario. This is the first study that considers human errors along with resource allocation in the emergency department (ED). Second, it is equipped with verification and validation at each phase. Third, it is a practical approach for emergency departments (EDs).
    Keywords: Human error, Resource Allocation, skill, rule, knowledge-based approach, multi-response optimization, Discrete-event simulation