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A multi-objective mathematical model for cellular manufacturing systems design with probabilistic demand and machine reliability analysis

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INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 2014年第5-8期75卷 755-770页

作者： Aghajani, Aydin Didehbani, Saeid Ahmadi Zadahmad, Manouchehr Seyedrezaei, Mir Hasan Mohsenian, Omid Islamic Azad Univ Ilkhchi Branch Dept Comp Engn Ilkhchi Iran Payame Noor Univ Dept Ind Engn Tehran Iran Univ Illinois Dept Mech & Ind Engn Chicago IL 60607 USA

This paper presents a dynamic multi-objective mixed integer mathematical model for cell formation problem with probabilistic demand and machine reliability analysis, where the total system costs, machine underutilization cost, and maximum system failure rate over the planning time periods are to be minimized simultaneously. The total system cost objective function calculates machine operating, internal part production, intercellular material handling, and subcontracting costs. Since in this type of problems, objectives are in conflict with each other, so finding an ideal solution (a solution that satisfies all objectives simultaneously) is not possible. Therefore, this study uses the augmented epsilon-constraint method (to solve small size problems) and a nondominated sorting genetic algorithm (NSGAII) (to solve large size problems) to find the Pareto optimal frontier that decision makers can select her/his preferred solution. Numerical examples will be solved to demonstrate the efficiency of the proposed algorithm.

关键词： Group technology Dynamic probabilistic demand multi-objective mathematical model Pareto optimal Exponential distribution Machine reliability Machine availability Poisson distribution multi-objective genetic algorithm

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multi-objective inventory routing problem: A stochastic model to consider profit, service level and green criteria

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TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW 2017年 101卷 59-83页

作者： Rahimi, Mohammad Baboli, Armand Rekik, Yacine Univ Lyon INSA Lyon DISP Lab EA4570 Villeurbanne France EMLYON Business Sch DISP Lab EA4570 Ecully France

The Inventory Routing Problem has been mainly studied in recent decades under an economic performance perspective. In this paper, we develop a multi-objective mathematical framework for the IRP to link: (i) the economic performance, (ii) the achieved server level in terms of shortage and delivery delays and (iii) the environmental footprint. The framework developed addresses the uncertainty by considering fuzzy distributions for certain problem inputs, such as the demand and the transportation costs. We show the negative impact on the economic performance when service level targets are exogenously chosen without coordination with the logistics components (inventory and distribution). (C) 2017 Elsevier Ltd. All rights reserved.

关键词： Inventory Routing Problem multi-objective mathematical model Perishable product Service level Green supply chain

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A multi-objective model for multi-production and multi-echelon closed-loop pharmaceutical supply chain considering quality concepts: NSGAII approach

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INTERNATIONAL JOURNAL OF SYSTEM ASSURANCE ENGINEERING AND MANAGEMENT 2017年第2期8卷 1717-1733页

作者： Moslemi, Shiva Sabegh, Mohammad Hossein Zavvar Mirzazadeh, Abolfazl Ozturkoglu, Yucel Maass, Eric Kharazmi Univ Fac Engn Dept Ind Engn Tehran Iran Yasar Univ Fac Econ & Adm Sci Int Logist Management Izmir Turkey DRM DFSS Medtron Inc 2343 W Medtron Way Tempe AZ 85281 USA

Quality of medical and pharmaceutical products has a key role in healthcare systems such as hospitals for better services to patients. This study proposes a comprehensive multi-objective mathematical model in healthcare supply chain considering quality and green concepts. The proposed model includes three objective functions. The first minimizes total manufacturing costs including transportation;purchasing maintenance, deterioration, setup, recycling, collecting and disposal costs. The second maximizes quality level of production. The third minimizes environmental effects of the products and transportations. The proposed model is complicated because of its nature and listed in the NP-hard. Hence, we use NSGAII approach for solving this model. The numerical example illustrates steps of the solution method. The solution representation for 4 suppliers, 2 recycling centers and 3 productions shows for supplier 1 (1100, 600, 1000) and supplier 2 (1000, 900, 400), recycling center 2 has a good performance and for supplier 3 (700, 500, 800) and supplier 4 (400, 950, 0), recycling center 1 has a good performance. Then, we need to improve the performance of the rest recycling centers per supplier. To measure the capabilities of multi-objective meta-heuristics, we used Number of Pareto solutions, spacing metric and quality metric criteria. Finally, the results show that the proposed algorithm has high quality to solve the model.

关键词： Healthcare supply chain Quality concepts multi-objective mathematical model NSGAII approach

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A robust multi-objective optimization model for project scheduling considering risk and sustainable development criteria

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ENVIRONMENT DEVELOPMENT AND SUSTAINABILITY 2021年第8期23卷 11494-11524页

作者： Askarifard, Majid Abbasianjahromi, Hamidreza Sepehri, Mehran Zeighami, Ehsanollah Islamic Azad Univ Dept Civil Engn Arak Branch Khomein St Arak Iran KN Toosi Univ Technol Dept Civil Engn Valiasr ST Tehran Iran Sharif Univ Technol Grad Sch Management Azadi St Tehran *** Iran

There is limited research that considers the sustainability aspect of the projects' schedule. The present study proposes a model to cover this gap by considering sustainable development criteria. A multi-objective model with four objective functions, including minimizing cost, risk, and socio-environmental impacts, has been presented to decrease the project's delay. Since some of the parameters are considered under conditions of uncertainty for the proximity of problems to real projects, the robust programming method is used to deal with the uncertainty, and the epsilon-constraint method was applied to solve the multi-objective model. Several scenarios are also defined to analyze the sensitivity of robust parameters in the generation of Pareto-based solutions, and the obtained results are also investigated. In addition, the design of experiments is applied for response surface methodology to determine the optimal levels of robust parameters that can generate solutions with greater variety. A real case study has been developed to implement different steps of the proposed model. Since the outcomes of the model determine the duration of each activity according to the objectives and different levels of robust parameters, managers and project owners can use this model as a tool to make appropriate decisions for their projects' schedules.

关键词： Project programming Sustainable development criteria Robust programming multi-objective mathematical model Response surface methodology

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Marrying supply chain sustainability and resilience: A match made in heaven

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TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW 2016年 91卷 306-324页

作者： Fahimnia, Behnam Jabbarzadeh, Armin Univ Sydney Sch Business ITLS Sydney NSW 2006 Australia Iran Univ Sci & Technol Dept Ind Engn Tehran 16846 Iran

Sustainable supply chain management has become an integral part of corporate strategy for virtually every industry. However, little is understood about the broader impacts of sustainability practices on the capacity of the supply chain to tolerate disruptions. This article aims to explore the sustainability-resilience relationship at the supply chain design level. A multi-objective optimization model featuring a sustainability performance scoring method and a stochastic fuzzy goal programming approach is developed that can be used to perform a dynamic sustainability tradeoff analysis and design a "resiliently sustainable" supply chain. Important managerial and practical insights are obtained from an empirical case study. (C) 2016 Published by Elsevier Ltd.

关键词： Sustainability Resilience Supply chain design multi-objective mathematical model Sustainability performance scoring Stochastic fuzzy goal programming Dynamic sustainability tradeoff analysis

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A novel optimization approach for rural development based on sustainable agriculture planning, considering the energy and water consumption nexus

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ENERGY EXPLORATION & EXPLOITATION 2023年第5期41卷 1724-1745页

作者： Luo, Jing Chang, Ya-Ping Kaliyaperumal, Karthikeyan Sichuan Univ Coll Marxism Chengdu Peoples R China Chinese Culture Univ Dept Tourism Management Taipei Taiwan Chinese Culture Univ Grad Sch Tourism Management Taipei Taiwan Ambo Univ Coll Nat & Computat Sci IT IoT HH Campus Ambo Ethiopia Ambo Univ Coll Nat & Computat Sci IT IoT HH Campus Ambo Oromia Ethiopia

In today's world, there are many changes and transformations in different sectors of the economy, and today's world economy has become more dependent on each other. The economy of many developing countries is highly dependent on agriculture. In addition, in developed countries, the agricultural sector is of special importance, so they are currently turning to the production of more organic and healthy products. One of the reasons that caused the agricultural sector to receive more attention in the economy is the existential importance of this sector in providing the raw materials of a part of the industry and the food industry needed in that country. Accordingly, in this research, the optimal cultivation pattern is determined using a linear multi-objective mathematical model, including economic, social, and environmental objectives. Moreover, the uncertainty in the input parameters of the proposed model is considered, and a robust optimization approach is applied to deal with this uncertainty. After collecting the research data for the crop year 2021-2022, the proposed robust counterpart formulation is optimized using GAMS software. The numerical results show that increasing the level of conservatism in the robust model cause to decrease in the profit of agriculture as well as increasing the total consumed water. Moreover, the results of the current research can help the decision-makers of the agricultural sector in achieving the goal of obtaining the highest profit.

关键词： Agriculture optimization multi-objective mathematical model uncertainty robust optimization cropping pattern

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A hybrid heuristic solution based on simulated annealing algorithm for energy efficient single machine scheduling problem with sequence dependent setup times

JOURNAL OF THE FACULTY OF ENGINEERING AND ARCHITECTURE OF GA...

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JOURNAL OF THE FACULTY OF ENGINEERING AND ARCHITECTURE OF GAZI UNIVERSITY 2021年第1期36卷 407-420页

作者： Bektur, Gulcin Iskenderun Tech Univ Ind Engn TR-31200 Antakya Turkey

Increased carbon dioxide emissions and energy consumption increase interest in energy efficient scheduling problems. In this study, speed scaling method is discussed in order to provide energy saving in multiobjective energy efficient single machine scheduling problem. In the literature with the speed scaling method, the energy consumption rate increases when the machine is operated at high speed, but the job is completed in a shorter time. When the machine is operate at low speed, the energy consumption rate decreases but the completion time of the jobs are prolonged. In the study, the objective functions are minimization of the total amount of energy consuption and the number of tardy jobs. The problem is defined by the scheduling problem in a manufacturing firm that produces plastic parts. Jobs have a sequence dependent setup times, and the setup time of a job depends on the job completed before it. A mathematical model is proposed for the problem. The epsilon-constraint method is used for the solution of the problem. All Pareto efficient solutions for small size problems are obtained by using the proposed heuristic method. However, as a result of the problem not being solved in polynomial time, a multi-objective heuristic algorithm is proposed for solving large-scale problems. The success of the proposed algorithm is shown by comparing with Non- dominated Sorting Genetic Algorithm II.

关键词： Energy efficient single machine scheduling epsilon-constraint method multi-objective heuristic algorithm sequence dependent setup times multi-objective mathematical model

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A two-stage mechanism as a decision support for marketing via customer satisfaction measures

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JOURNAL OF INDUSTRIAL AND PRODUCTION ENGINEERING 2012年第4期29卷 270-281页

作者： Fazlollahtabar, Hamed Aghasi, Ermia Iran Univ Sci & Technol Fac Ind Engn Tehran Iran Univ Guilan Fac Human Sci Dept Execut Management Rasht Iran

In this article, we propose a two stage decision model to aid the marketing team of a company. The decision is based on customers' satisfaction measures. These measures are related to the different services the company offers to its customers. Thus, they constitute a multi criteria evaluation of the company's performances. The first stage of our proposed mechanism is to purify the services with respect to the criteria. A stochastic multi-criteria acceptability analysis is employed to purify the services. Then a multi-objective mathematical model is utilized to determine the services with more profits. A fuzzy goal programming is applied to solve the multi-objective model. The applicability and validity of the proposed mechanism is illustrated in a case study.

关键词： decision support multi-objective mathematical model fuzzy goal programming

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multi-objective location-distribution optimization in blood supply chain: an application in Turkiye

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BMC PUBLIC HEALTH 2024年第1期24卷 1-15页

作者： Altunoglu, Burcu Sir, Gul Didem Batur Univ Turkish Aeronaut Assoc Dept Ind Engn TR-06790 Ankara Turkiye Gazi Univ Dept Ind Engn TR-06570 Ankara Turkiye

Purpose Blood donors are crucial in maintaining the blood supply chain. This study aims to improve the location and distribution of blood donation centers by focusing on two main objectives: minimizing costs and maximizing quality. Minimizing costs includes setting up and transporting blood efficiently while maximizing quality to ensure that blood products are delivered to hospitals promptly and in the right quantities. Methods A multi-objective mathematical model is proposed to address the placement of both fixed and mobile blood donation centers. The first objective focuses on minimizing the costs of setting up centers and transporting blood. The second objective aims to maximize quality by ensuring timely deliveries and meeting hospitals' blood demand. The model utilizes real-world traffic and blood donation data from urban settings to simulate its effectiveness and applicability in practice. The model uses the epsilon constraint method to optimize both objectives simultaneously. Results The model was tested in various scenarios, optimizing cost and quality separately. The algorithm determined the ideal locations for blood donation centers to meet demand by exploring different options. It also accounted for factors that reduce quality, such as delayed deliveries and product returns, and showed that these issues could be minimized. Conclusion This study highlights the need to balance cost and quality when determining the locations of blood donation centers. Using the epsilon constraint method, the model successfully optimized both objectives, offering valuable insights for improving the efficiency and effectiveness of blood donation operations.

关键词： Health systems Blood donation multi-objective mathematical model epsilon constraint method Location problem Distribution problem

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Designing a virtual cellular manufacturing system with route selection and workers' considerations: A multi-objective robust possibilistic model

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EXPERT SYSTEMS WITH APPLICATIONS 2024年第PartF期238卷

作者： Farboodi, Sadaf Paydar, Mohammad Mahdi Nemati, Arash Babol Noshirvani Univ Technol Dept Ind Engn Babol Iran

In today's economy, the necessity for responsiveness to variations in customers' permanent requirements is increasing significantly. Achieving immediate response or success in the competitive market requires boosting flexibility, agility, and efficiency in utilizing available production equipment and workforce. Implementing a Virtual Cellular Manufacturing System (VCSM) prevents the reconfiguration costs and is suitable for many systems where the machines are not removable. Owing to the significant role of human resources in VCMS, this paper assigns the workers based on their skills, interest in cooperation, and workload balancing among cells. The considerable novelty is balancing physical and time workloads simultaneously. Another strength of this research is the consideration of various routes to process each part. A comprehensive linear multi-objective mathematical model is developed for a virtual cellular manufacturing system. This paper develops the model by stating social and technical dimensions, which minimize exceptional elements and voids, maximize the workers' interest in cooperation, and minimize workload deviation. Stemming from uncertain parameters, a robust possibilistic approach is addressed. Due to the multi-objective model, the multi-choice meta-goal programming with the utility function is applied. Afterward, a real-case study is presented to validate the model. Eventually, the outcomes and sensitivity analysis are brought up.

关键词： Cell formation Workforce allocation Workload balancing multi-objective mathematical model Uncertainty modeling multi-choice meta-goal programming Utility function

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