A memetic algorithm for energy-efficient scheduling of integrated production and shipping
Energy-efficient manufacturing is critical as the industrial sector accounts for a substantial portion of global energy consumption. This research aims to address an energy-efficient scheduling problem of production and shipping for minimizing both makespan and energy consumption. It contributes to...
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| Vydané v: | International journal of computer integrated manufacturing Ročník 35; číslo 10-11; s. 1246 - 1268 |
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| Hlavní autori: | , , , |
| Médium: | Journal Article |
| Jazyk: | English |
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Taylor & Francis
02.11.2022
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| ISSN: | 0951-192X, 1362-3052, 1362-3052 |
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| Abstract | Energy-efficient manufacturing is critical as the industrial sector accounts for a substantial portion of global energy consumption. This research aims to address an energy-efficient scheduling problem of production and shipping for minimizing both makespan and energy consumption. It contributes to an integrated energy-efficient production and shipping system, which is separately studied in most existing research. The production stage allocates jobs onto unrelated parallel machines that can be shut off and adjust their cutting speed to save energy. The shipping stage aims to allocate jobs to vehicles of various sizes with varied unit energy consumption. The problem is modelled as a mixed-integer quadratic program. Considering its complexity, a memetic algorithm (MA) is proposed to incorporate a knowledge-driven local search strategy considering the balance between exploration and exploitation. Two dominance rules are derived from the characteristics of the specific problem and embedded into the proposed MA to enhance its performance. Experimental results demonstrate that the proposed MA outperforms two other population-based algorithms, genetic algorithm and traditional MA, in terms of performance and computing time. This research practically contributes to improving productivity and energy efficiency for the production-shipping supply chain of make-to-order products. |
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| AbstractList | Energy-efficient manufacturing is critical as the industrial sector accounts for a substantial portion of global energy consumption. This research aims to address an energy-efficient scheduling problem of production and shipping for minimizing both makespan and energy consumption. It contributes to an integrated energy-efficient production and shipping system, which is separately studied in most existing research. The production stage allocates jobs onto unrelated parallel machines that can be shut off and adjust their cutting speed to save energy. The shipping stage aims to allocate jobs to vehicles of various sizes with varied unit energy consumption. The problem is modelled as a mixed-integer quadratic program. Considering its complexity, a memetic algorithm (MA) is proposed to incorporate a knowledge-driven local search strategy considering the balance between exploration and exploitation. Two dominance rules are derived from the characteristics of the specific problem and embedded into the proposed MA to enhance its performance. Experimental results demonstrate that the proposed MA outperforms two other population-based algorithms, genetic algorithm and traditional MA, in terms of performance and computing time. This research practically contributes to improving productivity and energy efficiency for the production-shipping supply chain of make-to-order products. |
| Author | Ning, Tong Liu, Yang Chen, Jian Xu, Gangyan |
| Author_xml | – sequence: 1 givenname: Jian orcidid: 0000-0001-8882-0000 surname: Chen fullname: Chen, Jian organization: Nanjing University of Aeronautics and Astronautics – sequence: 2 givenname: Tong surname: Ning fullname: Ning, Tong organization: Nanjing University of Aeronautics and Astronautics – sequence: 3 givenname: Gangyan orcidid: 0000-0001-9537-9006 surname: Xu fullname: Xu, Gangyan organization: The Hong Kong Polytechnic University – sequence: 4 givenname: Yang orcidid: 0000-0001-8006-3236 surname: Liu fullname: Liu, Yang email: yang.liu@liu.se organization: University of Vaasa |
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| Title | A memetic algorithm for energy-efficient scheduling of integrated production and shipping |
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