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International Journal of Engineering، جلد ۳۰، شماره ۲، صفحات ۲۲۴-۲۳۳
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| عنوان فارسی |
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| چکیده فارسی مقاله |
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| کلیدواژه‌های فارسی مقاله |
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| عنوان انگلیسی |
Solving a New Multi-objective Unrelated Parallel Machines Scheduling Problem by Hybrid Teaching-learning Based Optimization |
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| چکیده انگلیسی مقاله |
This paper considers a scheduling problem of a set of independent jobs on unrelated parallel machines (UPMs) that minimizesthe maximum completion time (i.e., makespan or ), maximum earliness ( ), and maximum tardiness ( ) simultaneously. Jobs have non-identical due dates, sequence-dependent setup times and machine-dependentprocessing times. A multi-objective mixed-integer linear programming (MILP) is considered then solved with the ε-constraint method in small-sized problems.The related results are compared with the results obtained by meta-heuristic algorithms.Furthermore, an effectivehybrid multi-objective teaching–learningbased optimization (HMOTLBO) algorithm is proposed, whose performance is compared with a non-dominated sorting genetic algorithm (NSGA-II) fortest problems generated at random. The associated results show that the proposed HMOTLBO outperformsthe NSGA-II in terms of different metrics. |
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| کلیدواژه‌های انگلیسی مقاله |
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| نویسندگان مقاله |
Bahman Naderi |
industrial engineering department, kharazmi university
Reza Tavakkoli-Moghaddam |
Industrial Engineering, University of Tehran
Azam Sadati |
Department of Industrial Engineering, Islamic Azad University
Mohammad Mohammadi |
Department of Industrial Engineering, Kharazmi University
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| نشانی اینترنتی |
http://www.ije.ir/article_72880_fb404fe60084150a810e6ae2fa7a3d0e.pdf |
| فایل مقاله |
اشکال در دسترسی به فایل - ./files/site1/rds_journals/409/article-409-2062151.pdf |
| کد مقاله (doi) |
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| زبان مقاله منتشر شده |
en |
| موضوعات مقاله منتشر شده |
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