A Two-Phase Meta-Heuristic for Multiobjective Flexible Job Shop Scheduling Problem With Total Energy Consumption Threshold

Flexible job shop scheduling problem (FJSP) has been extensively considered; however, multiobjective FJSP with energy consumption threshold is seldom investigated, the goal of which is to minimize makespan and total tardiness under the constraint that total energy consumption does not exceed a given...

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Vydáno v:IEEE transactions on cybernetics Ročník 49; číslo 3; s. 1097 - 1109
Hlavní autoři: Lei, Deming, Li, Ming, Wang, Ling
Médium: Journal Article
Jazyk:angličtina
Vydáno: United States IEEE 01.03.2019
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:
Energy conservation
Energy consumption
Energy consumption threshold
Evolutionary algorithms
flexible job shop scheduling problem (FJSP)
Genetic algorithms
Heuristic job shop scheduling
Heuristic methods
imperialist competitive algorithm (ICA)
Job shop scheduling
Job shops
Multiple objective analysis
Optimization
Production scheduling
Schedules
Sociology
Statistics
two-phase meta-heuristic (TPM)
variable neighborhood search (VNS)
ISSN:2168-2267, 2168-2275, 2168-2275
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Shrnutí:Flexible job shop scheduling problem (FJSP) has been extensively considered; however, multiobjective FJSP with energy consumption threshold is seldom investigated, the goal of which is to minimize makespan and total tardiness under the constraint that total energy consumption does not exceed a given threshold. Energy constraint is not always met and the threshold is difficult to be decided in advance. These features make it more difficult to solve the problem. In this paper, a two-phase meta-heuristic (TPM) based on imperialist competitive algorithm (ICA) and variable neighborhood search (VNS) is proposed. In the first phase, the problem is converted into FJSP with makespan, total tardiness and total energy consumption and the new FJSP is solved by an ICA, which uses some new methods to build initial empires and do imperialist competition. In the second phase, new strategies are provided for comparing solutions and updating the nondominated set of the first phase and a VNS is used for the original problem. The current solution of VNS is periodically replaced with member of the set <inline-formula> <tex-math notation="LaTeX">\Omega </tex-math></inline-formula> to improve solution quality. An energy consumption threshold is obtained by optimization. Extensive experiments are conducted to test the performance of TPM finally. The computational results show that TPM is a very competitive algorithm for the considered FJSP.
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ISSN:2168-2267
2168-2275
2168-2275
DOI:10.1109/TCYB.2018.2796119