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Supply Chain Optimization Considering Sustainability Aspects
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- Beheshtinia, Mohammad Ali (author)
- Industrial Engineering Department, Semnan University, Semnan 3513119111, Iran
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- Feizollahy, Parisa (author)
- Industrial Engineering Department, Semnan University, Semnan 3513119111, Iran
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- Fathi, Masood (author)
- Uppsala universitet,Högskolan i Skövde,Institutionen för ingenjörsvetenskap,Forskningsmiljön Virtuell produkt- och produktionsutveckling,Division of Industrial Engineering and Management, Uppsala University, Sweden,Produktion och automatiseringsteknik, Production and Automation Engineering,Industriell teknik
- (creator_code:org_t)
- 2021-10-27
- 2021
- English.
- In: Sustainability. - : MDPI. - 2071-1050. ; 13:21, s. 1-23
- Journal article (peer-reviewed)
Abstract
Subject headings
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- Supply chain optimization concerns the improvement of the performance and efficiency of the manufacturing and distribution supply chain by making the best use of resources. In the context of supply chain optimization, scheduling has always been a challenging task for experts, especially when considering a distributed manufacturing system (DMS). The present study aims to tackle the supply chain scheduling problem in a DMS while considering two essential sustainability aspects, namely environmental and economic. The economic aspect is addressed by optimizing the total delivery time of order, transportation cost, and production cost while optimizing environmental pollution and the quality of products contribute to the environmental aspect. To cope with the problem, it is mathematically formulated as a mixed-integer linear programming (MILP) model. Due to the complexity of the problem, an improved genetic algorithm (GA) named GA-TOPKOR is proposed. The algorithm is a combination of GA and TOPKOR, which is one of the multi-criteria decision-making techniques. To assess the efficiency of GA-TOPKOR, it is applied to a real-life case study and a set of test problems. The solutions obtained by the algorithm are compared against the traditional GA and the optimum solutions obtained from the MILP model. The results of comparisons collectively show the efficiency of the GA-TOPKOR. Analysis of results also revealed that using the TOPKOR technique in the selection operator of GA significantly improves its performance.
Subject headings
- TEKNIK OCH TEKNOLOGIER -- Maskinteknik -- Produktionsteknik, arbetsvetenskap och ergonomi (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Mechanical Engineering -- Production Engineering, Human Work Science and Ergonomics (hsv//eng)
Keyword
- genetic algorithm
- supply chain
- scheduling
- sustainability
- multi-criteria decision-making
- mathematical model
- TOPKOR
- Production and Automation Engineering
- Produktion och automatiseringsteknik
Publication and Content Type
- ref (subject category)
- art (subject category)
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