A hybrid differential evolution algorithm for multiple container loading problem with heterogeneous containers |
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| Affiliation: | 1. School of Management Science and Engineering, Dongbei University of Finance and Economics, Dalian, Liaoning, 116025, People’s Republic of China;2. School of Business Administration, South China University of Technology, Guangzhou, 510640, Peoples Republic of China;3. Department of Management Sciences, College of Business, City University of Hong Kong, Tat Chee Ave, Kowloon Tong, Hong Kong S.A.R;4. School of Physical & Mathematical Sciences, Nanyang Technological University, 637371, Singapore;5. School of Information Technology, Jiangxi University of Finance and Economics, Nanchang, Jiangxi, 330013, People’s Republic of China;1. CIDEM, School of Engineering, Polytechnic of Porto, Portugal;2. INESC TEC, Portugal;3. Faculty of Engineering, University of Porto, Portugal |
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| Abstract: | We consider a multiple container loading problem, commonly known as the three-dimensional bin packing problem (3D-BPP), which deals with maximizing container space utilization while the containers available for packing are heterogeneous, i.e., varying in size. The problem has wide applications in cargo transportation, warehouse management, medical packaging, and so on. We develop a differential evolution (DE) algorithm hybridized with a novel packing heuristic strategy, best-match-first (BMF), which generates a compact packing solution based on a given box packing sequence and a container loading sequence. The effectiveness of the proposed algorithm is evaluated on a set of industrial instances and randomly generated instances. The results show that the proposed algorithm outperforms existing solution approaches in terms of solution quality. |
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| Keywords: | Three-dimensional bin packing (3D-BPP) Differential evolution (DE) Mathematical programming Evolutionary algorithms (EAs) |
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