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Optimization for a Sustainable Supply Chain Using Fuzzy VIKOR method: An Application on a Real Dataset

IEEE ACCESS 2024年 12卷 131882-131891页

作者： Abhilasha, Anshu Danish, Faizan VIT AP Univ Sch Adv Sci Dept Math Amaravati 522237 Andhra Pradesh India

One of the main themes leading to a green economy is the sustainable supply chain, which creates the chance to lower carbon emissions all the way up the product value chain. Using a pharmaceutical company as a case study, this investigation explores optimized sourcing practices and proposes a methodology to help in selecting the best green supplier and place orders with potential suppliers. There is a two-phase hybrid method in the suggested model. The Fuzzy VIKOR (Fuzzy VIseKriterijumska Optimizacija I Kompromisno Resenje) methodology is used in the first phase to rate and select possible suppliers based on social, environmental, and economic factors (such as late delivery times and freight costs). The second phase describes an order allocation procedure based on (MOLP) multi-objective linear programming that aims to minimize costs, delivery delays, and greenhouse gas emissions during transportation. Using epsilon-constraint method we apply MOLP model to optimize more than one objective in order to convert two objectives into single objective function. Forming such a model is helpful for the manufacturing unit to evaluate green supplier and allocate order, as illustrated by a case study of a pharmaceutical manufacturing facility. Three suppliers are evaluated who used ocean, air and truck as their mode of transportation. Using Fuzzy VIKOR technique suppliers are evaluated and it is observed that the 'suppliers who supply medicines through ship is the best supplier. It is observed that transportation via ocean is more environment friendly in comparison of truck and airplane.

关键词： Pharmaceuticals Green products Resource management Carbon dioxide Supply chains Linear programming Transportation Fuzzy systems Sustainable development & varepsilon -constraint method fuzzy VIKOR multi objective linear programming sustainable supplier selection

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DESIGNING A MULTI-ECHELON CLOSED-LOOP SUPPLY CHAIN WITH DISRUPTION IN THE DISTRIBUTION CENTERS UNDER UNCERTAINTY

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JOURNAL OF INDUSTRIAL AND MANAGEMENT OPTIMIZATION 2023年第4期19卷 2582-2615页

作者： Zadeh, Kaveh Keshmiry Harsej, Fatemeh Sadeghpour, Mahboubeh Aghdam, Mohammad Molani Islamic Azad Univ Dept Ind Engn Nour Branch Nour Iran Islamic Azad Univ Qual Res Ctr Nour Branch Nour Iran Islamic Azad Univ Dept Ind Engn Qaemshahr Branch Qaemshahr Iran Islamic Azad Univ Innovat & Management Res Ctr Ayatollah Amoli Branch Amol Iran

According to the need for further cost reduction and improving the process of the organization in the direction of customer demand, the concept of the supply chain has become increasingly significant and the organizations seek to expand this concept within their organizational framework. In this regard, efficient planning of distribution of products in the supply chain by considering disruption has received more attention recently. In this study a multi-objective mixed-integer linear programming model is developed for a green multi-echelon closed-loop supply chain network design under uncertainty. Moreover, a partial disruption is considered for distribution centers where has not been studied enough in previous works. The fuzzy credibility constraint approach is applied to cover uncertainty. In the following, the -constraint method is presented to solve and validate the model in small-sized instances. Moreover, a Non-dominated Sorting Genetic Algorithm is developed for solving the large-sized problems. Results show that uncertainty has a crucial impact on objective functions where the increase of objective functions by increasing the level of uncertainty, which was observed in all categories. Furthermore, the proposed NSGA-II is the best tool to deal with large-size problems where the EC method lacks the necessary efficiency.

关键词： Closed-loop supply chain green supply chain customer satisfaction -constraint method NSGA-II algorithm

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Proposal and assessment of a sustainable method for urban waste transportation and selling: real-life case study

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EMERGENT MATERIALS 2023年第4期6卷 1383-1391页

作者： Zheng, Qinghua Jinling Inst Technol Sch Business Nanjing 211169 Jiangsu Peoples R China

Increasing municipal solid waste (MSW) has caused severe environmental pollution and social problems, which require effective treatment and resource utilization. Therefore, combined with a sustainable approach, an urban vacuum waste collection (VWC) system was established in this study. To optimize VWC management, a bi-objective model is created to address the issue of waste management in this work in an environmentally friendly way. This model evaluates the economic benefits, social benefits, and environmental costs of reducing greenhouse gas emissions (GHGs). The proposed model is solved using the augmented e-constraint method. Numeric results show the efficiency of the mentioned method. A sensitivity analysis is conducted to verify the model. The results depict that the VWC model is sensitive to parameters such as budget, transfer station capacity, treatment facilities' capacity, and infrastructure costs.{GRAPHIACAL ABSTRACT}

关键词： Sustainable waste management Vacuum waste collection Bi-objective optimization Augmented & epsilon -constraint method

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Investigating of transportation systems development for urban districts, costs and social equity: a case of Sanandaj, Kurdistan

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OPSEARCH 2024年第1期61卷 373-398页

作者： Dastgoshade, Sohaib Hosseini-Nasab, Hassan Mehrjerdi, Yahia Zare Yazd Univ Dept Ind Engn Univ BlvdPOB *** Yazd Iran

The transportation system is one of the essential subjects for any country because it directly concerns the daily costs and social problems. Researchers have proposed different methods to develop transportation systems, each with its strengths and weaknesses. This paper has proposed a new bi-objective mathematical model based on three social equity theories, the first of which considers infrastructure development costs for a transportation system and includes operational, environmental, and pollution costs. The second objective focuses on enhancing social equity in investment distributions in the transportation system for a long time. Three theories, including Utilitarianism, Rawl's, and Sadr's, were modeled and used to assess social equity. The model was examined for an original case of data in Sanandaj city, and an improved version of the augmented e-constraint method was developed to solve it. According to the general results, each social equity theory has its own merits. The results show that Rawls' theory, with minimum infrastructure costs, establishes the best social equity (70%) after 5 years of application;therefore, the Sanandaj city would be a sustainable city based on Rawls' theory which enhances region 1, and the three regions would be in balance after 5 years. Urban planners and transport network managers can use the developed model for equitable investment in an urban transportation system.

关键词： Allocation & epsilon -constraint method Social equity theories Sustainable investment Sustainable cities Transportation systems Urban planinng

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Integrating lean, resilient, and sustainable practices in supply chain network: mathematical modelling and the AUGMECON2 approach

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INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE-OPERATIONS & LOGISTICS 2022年第4期9卷 451-471页

作者： Shafiee, Mohammad Mehrjerdi, Yahia Zare Keshavarz, Marzieh Yazd Univ Dept Ind Engn Yazd Iran

Nowadays, organisations try to find a proper method to increase their competitiveness. Lean, resilient, and sustainable are top-hole managerial practices in supply chain management. This paper tries to study the effects of integrating lean, resilient, and sustainable practices in the supply chain network (SCN). To this end, a new multi-objective mixed-integer programming is developed in such a way that lean manufacturing is implemented in a resilient-sustainable SCN. The objective functions try to maximise job opportunities and minimise costs, environmental effects, and delivery time. Resilience has been taken into account to tackle the lack of raw materials during disruptions by implementing multiple sourcing in the model. Besides, to devote more attention to sustainable practices, backup suppliers have been prioritised based on sustainability criteria. The academics were enquired to rate sustainability criteria for selecting a backup supplier. Finally, a fuzzy TOPSIS method was used to rank the backup suppliers based on sustainability criteria. The improved version of augmented epsilon-constraint (AUGMECON2) was applied to cope with multi-objectivity of the problem. The results indicated a synergistic effect among leanness, resilience, and sustainability in the supply chain. Also, it turned out that sustainable backup supplier selection boosts the synergistic effect among these three concepts.

关键词： Lean supply chain resilience sustainability stochastic programming supplier selection ε -constraint method

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A ROBUST MULTI-OBJECTIVE MODEL FOR MANAGING THE DISTRIBUTION OF PERISHABLE PRODUCTS WITHIN A GREEN CLOSED-LOOP SUPPLY CHAIN

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JOURNAL OF INDUSTRIAL AND MANAGEMENT OPTIMIZATION 2021年第5期18卷 3155-3186页

作者： Gerdrodbari, Maedeh Agahgolnezhad Harsej, Fatemeh Sadeghpour, Mahboubeh Aghdam, Mohammad Molani Islamic Azad Univ Dept Ind Engn Nour Branch Nour Iran Islamic Azad Univ Qual Res Ctr Nour Branch Nour Iran Islamic Azad Univ Qaemshahr Branch Dept Ind Engn Qaemshahr Iran Islamic Azad Univ Innovat & Management Res Ctr Ayatollah Amoli Branch Amol Iran

The required processes of supply chain management include opti-mal strategic, tactical, and operational decisions, all of which have important economic and environmental effects. In this regard, efficient supply chain plan-ning for the production and distribution of perishable productsis of particular importance due to its leading role in the human food pyramid. One of the main challenges facing this chain is the time when products and goods are de-livered to the customers and customer satisfaction will increase through *** this research, a bi-objective mixed-integer linear programming (MILP)model is proposedto design a multi-level, multi-period, multi-pro duct closed-loop supply chain (CLSC) for timely production and distribution of perishable products, taking into account the uncertainty of demand. To face the model uncertainty, the robust optimization (RO) method is utilized. Moreover, to solve and val-idate the bi-objective model in small-size problems, the -constraint method (EC) is presented. On the other hand, a Non-dominated Sorting Genetic Al-gorithm (NSGA-II) is developed for solving large-size problems. First, the deterministic and robust models are compared by applying the suggested solu-tions methods in a small-size problem, and then,the proposed solution methods are compared in large-size problems in terms of different well-known metrics. According to the comparison, the proposed model has an acceptable perfor-mance in providing the optimal solutions and the proposed algorithm obtains efficient ***, managerial insights are proposed using sensitivity analysis of important parameters of the problem.

关键词： Perishable supply chain closed-loop supply chain customer satisfac-tion NSGA-II -constraint method

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Multiobjective Optimal Power Flow Using a Semidefinite Programming-Based Model

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IEEE SYSTEMS JOURNAL 2021年第1期15卷 158-169页

作者： Davoodi, Elnaz Babaei, Ebrahim Mohammadi-Ivatloo, Behnam Shafie-Khah, Miadreza Catalao, Joao P. S. Univ Tabriz Fac Elect & Comp Engn Tabriz 51666 Iran Near East Univ Engn Fac Mersin 10 TR-99138 Nicosia North Cyprus Turkey Duy Tan Univ Inst Res & Dev Da Nang 550000 Vietnam Univ Vaasa Sch Technol & Innovat Vaasa 65200 Finland Univ Porto Inst Syst & Comp Engn Technol & Sci Fac Engn P-4200465 Porto Portugal

In spite of the significant advance achieved in the development of optimal power flow (OPF) programs, most of the solution methods reported in the literature have considerable difficulties in dealing with different-nature objective functions simultaneously. By leveraging recent progress on the semidefinite programming (SDP) relaxations of OPF, in the present article, attention is focused on modeling a new SDP-based multiobjective OPF (MO-OPF) problem. The proposed OPF model incorporates the classical epsilon-constraint approach through a parameterization strategy to handle the multiple objective functions and produce Pareto front. This article emphasizes the extension of the SDP-based model for MO-OPF problems to generate globally nondominated Pareto optimal solutions with uniform distribution. Numerical results on IEEE 30-, 57-, 118-bus, and Indian utility 62-bus test systems with all security and operating constraints show that the proposed convex model can produce the nondominated solutions with no duality gap in polynomial time, generate efficient Pareto set, and outperform the well-known heuristic methods generally used for the solution of MO-OPF. For instance, in comparison with the obtained results of NSGA-II for the 57-bus test system, the best compromise solution obtained by SDP has 1.55% and 7.42% less fuel cost and transmission losses, respectively.

关键词： Linear programming Fuels Propagation losses Power systems Pareto optimization Minimization Convexification multiobjective OPF (MO-OPF) optimal power flow (OPF) semidefinite programming (SDP) ϵ -constraint method

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Robust multimodal hub network design for hazmat considering a detour strategy

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JOURNAL OF LOSS PREVENTION IN THE PROCESS INDUSTRIES 2023年第1期85卷

作者： Han, Wanke Fan, Tijun Li, Shuxia Liu, Liping East China Univ Sci & Technol Sch Business Shanghai 200237 Peoples R China

Most traditional hub networks focus on ordinary cargo transportation and usually limit the number of transshipment occurrences to minimise costs. However, this limitation is not conducive to the transportation of hazmat, which often requires detours to avoid high risks. Therefore, this paper proposes a new multimodal network model considering a detour strategy and discusses the uncertainty in the network from the demand point of view. The method of robust optimisation is used to address the uncertainty in the proposed model, and the Lagrange relaxation algorithm and augmented e-constraint method are used to transform and simplify the model. In addition, simulated data of hazmat transportation in the Yangtze River Delta urban agglomeration are used for a case study. The results show that under the consideration of uncertain demand, changes in the demand uncertainty degree and transit discount factor cause changes in the total cost and risk of the multimodal hub network, thus affecting the carrier's location and route decisions;the new model can better control and mitigate risk, which is more suitable for hazmat transportation. This study provides a reference for multimodal transport carriers in hazmat transportation decision making.

关键词： Multimodal transportation Hub network design Hazardous materials Uncertainty & epsilon -constraint method

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Routing optimization for medical waste collection considering infectious risk and multiple disposal centers

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EXPERT SYSTEMS WITH APPLICATIONS 2023年第1期234卷

作者： Wang, Nengmin Cui, Wei Zhang, Meng Jiang, Qi Xi An Jiao Tong Univ Sch Management Xian 710049 Shaanxi Peoples R China ERC Proc Min Mfg Serv Shaanxi Prov Xian 710049 Shaanxi Peoples R China Xian Technol Univ Sch Econ & Management Xian 710021 Shaanxi Peoples R China Soft Sci Base Ordnance Ind Innovat & Dev Shaanxi P Xian 710021 Shaanxi Peoples R China Shaanxis Coll & Univ Civil Mil Integrat Sci & Technol Innovat Res Ctr Xian 710021 Shaanxi Peoples R China Xian Technol Univ 2 Xuefuzhonglu Rd Xian 710021 Shaanxi Peoples R China

The routing optimization for medical waste collection severely affects the efficiency and safety of medical waste disposal. The infectivity of medical waste exacerbates the potential impact of incidents, and the large amount of medical waste has given birth to the practical operation of multiple disposal centers. A definition of infectious risk related to the infectious process after an incident and the final infected population is proposed. With the consideration of multiple disposal centers and catastrophe avoidance, a bi-objective routing optimization model for medical waste collection is developed based on two-commodity formulation, minimizing the maximum infectious risk and transport cost simultaneously. An e-constraint method incorporating weighting is proposed, which can obtain the entire Pareto front and incorporates an improved solution process. A fast approximation approach is proposed for solving large-scale instances efficiently. Finally, the proposed solution method is tested by numerical instance, and some managerial insights are given through sensitivity analysis.

关键词： Medical waste collection Routing optimization Infectious risk Multiple disposal centers & epsilon -constraint method

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Bi-objective optimization of retailer's profit and customer surplus in assortment and pricing planning

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ANNALS OF OPERATIONS RESEARCH 2021年第1-2期296卷 195-210页

作者： Maddah, Bacel Ben Abdelaziz, Fouad Tarhini, Hussein Amer Univ Beirut Maroun Semaan Fac Engn & Architecture Dept Ind Engn & Management Beirut Lebanon Neoma Business Sch Mont St Aignan France

We develop a bi-objective optimization for a retailer product line, composed of substitutable variants, that seeks to maximize the retailer's profit and consumer surplus concurrently, where the surplus is measured as a utility scaled in dollars. With fast-moving consumer goods in mind, we utilize a deterministic, price-dependent, utility model to develop the demand function. The problem is then formulated as a bi-objective mixed-integer nonlinear program. The epsilon-constraint method is used to fully develop the set of Pareto optimal solutions for this problem. Specifically, we derive analytical bounds on the values of epsilon that lead to Pareto optimal solutions. We then propose a scheme with simple steps that allows developing as many efficient solutions, as needed. To overcome the computational burden, we adopt a linearization scheme, which recast the problem into an integer-linear program that proves to be solvable within couple CPU seconds for large, industry-size, instances with tens of products and numerous consumer segments. Numerical examples on small- and large-size instances indicate that providing the customer with a high surplus level typically requires low prices and, surprisingly, small assortments (to reduce fixed costs). Another counter-intuitive observation that we make is that the price of a product sometimes raises when the required customer surplus level in the market is increased. This is due to cannibalization among products and change in the optimal assortment structure.

关键词： Multi-objective optimization Assortment planning Pricing Retail management ε -constraint method

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