Multi-objective evolutionary algorithm for solving energy-aware fuzzy job shop problems
Inés González-Rodríguez,Jorge Puente,Juan José Palacios,Camino R. Vela +3 more
- 01 Nov 2020
- Vol. 24, Iss: 21, pp 16291-16302
TL;DR: In this paper, a multi-objective problem is solved using an evolutionary algorithm based on the NSGA-II procedure, where the decoding operator incorporates a new heuristic procedure in order to improve the solutions' energy consumption.
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Abstract: A growing concern about the environmental impact of manufacturing processes and in particular the associated energy consumption has recently driven some researchers within the scheduling community to consider energy costs in addition to more traditional performance-related measures, such as satisfaction of due-date commitments. Recent research is also devoted to narrowing the gap between real-world applications and academic problems by handling uncertainty in some input data. In this paper, we address the job shop scheduling problem, a well-known hard problem with many applications, using fuzzy sets to model uncertainty in processing times and with the target of finding solutions that perform well with respect to both due-date fulfilment and energy efficiency. The resulting multi-objective problem is solved using an evolutionary algorithm based on the NSGA-II procedure, where the decoding operator incorporates a new heuristic procedure in order to improve the solutions’ energy consumption. This heuristic is based on a theoretical analysis of the changes in energy consumption when a solution is subject to slight changes, referred to as local right shifts. The experimental results support the theoretical study and show the potential of the proposal.
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Figures
Fig. 2: Decoding procedure HREC to generate a schedule from a chromosome 
Fig. 4: EAF plots comparing NSGA-II using HREC and SA on instance FTF10 (MO-SA - MO-HREC on the left and MO-HREC - MO-SA on the right). 
Fig. 5: EAF plots comparing NSGA-II using HREC and SA on instance FTF20 (MO-SA - MO-HREC on the left and MO-HREC - MO-SA on the right). 
Table 1: Comparison, in terms of HV and the I + values, between MO-SA and MO-HREC. 
Fig. 3: EAF plots comparing NSGA-II using HREC and SA on instance FTF06 (MO-SA - MO-HREC on the left and MO-HREC - MO-SA on the right).
Citations
Self-adaptive multi-objective evolutionary algorithm for flexible job shop scheduling with fuzzy processing time
Rui Li,Wenyin Gong,Chao Lu +2 more
TL;DR: In this article , a hybrid self-adaptive multi-objective evolutionary algorithm based on decomposition (HPEA) is proposed to solve the problem of flexible job shop scheduling with fuzzy processing time.
78
Multi-objective Q-learning-based hyper-heuristic with Bi-criteria selection for energy-aware mixed shop scheduling
01 Mar 2022
TL;DR: In this paper , a mixed-shop and flow-shop production scheduling problem with a speed-scaling policy and no-idle time strategy is formulated, and a multi-objective Q-learning-based hyper-heuristic with bi-criteria selection (QHH-BS) is developed to obtain a set of high-quality Pareto frontier solutions.
43
Energy-Efficient Scheduling in Job Shop Manufacturing Systems: A Literature Review
TL;DR: In this article , the authors reviewed the recent literature on energy-efficient scheduling in job shop manufacturing systems, with a particular focus on metaheuristics, and pointed out potential directions for future research, namely developing integrated scheduling approaches for interconnected problems, fast metaheuristic methods to respond to dynamic scheduling problems, and hybrid meta-heuristic and big data methods for cyber-physical production systems.
27
Multi-objective enhanced memetic algorithm for green job shop scheduling with uncertain times
01 Feb 2022
TL;DR: In this article , a job shop scheduling problem with the double goal of minimising energy consumption during machine idle time and minimising the project makespan is considered. But the problem is not solved by a single memetic algorithm.
17
An enhanced memetic algorithm with hierarchical heuristic neighborhood search for type-2 green fuzzy flexible job shop scheduling
Kanglin Huang,Wenyin Gong,Chao Lu +2 more
TL;DR: This study proposes an enhanced memetic algorithm (EMAH) with hierarchical heuristic neighborhood search for type-2 green fuzzy flexible job shop scheduling, minimizing total energy consumption and makespan, outperforming state-of-the-art algorithms in a benchmark.
14
References
•Book
Computers and Intractability: A Guide to the Theory of NP-Completeness
Michael Randolph Garey,David S. Johnson +1 more
- 01 Jan 1979
TL;DR: The second edition of a quarterly column as discussed by the authors provides a continuing update to the list of problems (NP-complete and harder) presented by M. R. Garey and myself in our book "Computers and Intractability: A Guide to the Theory of NP-Completeness,” W. H. Freeman & Co., San Francisco, 1979.
A fast and elitist multiobjective genetic algorithm: NSGA-II
TL;DR: This paper suggests a non-dominated sorting-based MOEA, called NSGA-II (Non-dominated Sorting Genetic Algorithm II), which alleviates all of the above three difficulties, and modify the definition of dominance in order to solve constrained multi-objective problems efficiently.
•Book
Scheduling: Theory, Algorithms, and Systems
Michael Pinedo
- 15 Jul 1994
TL;DR: Scheduling will serve as an essential reference for professionals working on scheduling problems in manufacturing and computing environments and Graduate students in operations management, operations research, industrial engineering and computer science will find the book to be an accessible and invaluable resource.
7.2K
Optimization and Approximation in Deterministic Sequencing and Scheduling: a Survey
TL;DR: In this article, the authors survey the state of the art with respect to optimization and approximation algorithms and interpret these in terms of computational complexity theory, and indicate some problems for future research and include a selective bibliography.
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