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A new method coupling simulation and a hybrid metaheuristic to solve a multiobjective hybrid flowshop scheduling problem
2011
Proceedings of the 7th conference of the European Society for Fuzzy Logic and Technology (EUSFLAT-2011)
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The latter uses a fuzzy logic controller to adjust the crossover and the mutation probabilities, in order to enhance the research ability of the traditional NSGA-II algorithm. ...
The aim of our work is to optimize the makespan and the total tardiness of the whole production. A simulation based optimization algorithm is proposed here to solve this problem. ...
In our previous works [31] [32], we have developed FLC-NSGA-II and FLC-SPEA-II algorithms to solve a multiobjective parallel machines scheduling problem. ...
doi:10.2991/eusflat.2011.33
dblp:conf/eusflat/LiCYA11
fatcat:7okdhnvlxbgy7m6w2lkmoz2lza
A review on genetic algorithm: past, present, and future
2020
Multimedia tools and applications
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This review will help the new and demanding researchers to provide the wider vision of genetic algorithms. The well-known algorithms and their implementation are presented with their pros and cons. ...
[79] used MS-PGA for solving data mining problems. Fuzzy rules are used with parallel GA. The evaluation of fitness function was performed on slave machines. ...
They used thirty processors to solve this problem at National University of Singapore. Yang et al. [213] developed a web-based parallel GA. ...
doi:10.1007/s11042-020-10139-6
pmid:33162782
pmcid:PMC7599983
fatcat:bg6phhszfzfbrjwazncc5p34bi
Multiobjective Hybrid Genetic Algorithms for Manufacturing Scheduling: Part II Case Studies of HDD and TFT-LCD
[chapter]
2015
Advances in Intelligent Systems and Computing
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This paper introduces how to design Mo-HGAs for solving the practical multiobjective manufacturing scheduling problems expanded by a multiobjective flexible job-shop scheduling problem (Mo-FJSP; operation ...
In this paper, we introduce how to design hybrid genetic algorithms (HGA) and multiobjective hybrid genetic algorithms (Mo-HGA) for solving practical manufacturing scheduling problems for the hard disc ...
fuzzy logic controller (HGA.FLC). ...
doi:10.1007/978-3-662-47241-5_2
fatcat:cta4yo5jwfdgnm63iuynxe6d2u
Fuzzy Mixed Assembly Line Sequencing and Scheduling Optimization Model Using Multiobjective Dynamic Fuzzy GA
2014
The Scientific World Journal
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A new multiobjective dynamic fuzzy genetic algorithm is applied to solve a fuzzy mixed-model assembly line sequencing problem in which the primary goals are to minimize the total make-span and minimize ...
Verification and validation of the dynamic fuzzy GA are carried out by developing test-beds and testing using a multiobjective fuzzy mixed production assembly line sequencing optimization problem. ...
Acknowledgment The authors would like to acknowledge the Malaysian Ministry of Higher Education (MOHE) for their financial support under High Impact Research Grant (no. ...
doi:10.1155/2014/505207
pmid:24982962
pmcid:PMC3985312
fatcat:fmkyfvmgjfeyrg264slvy3v3si
Mathematical Tools of Soft Computing 2014
2015
Mathematical Problems in Engineering
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., a discrete bacterial colony chemotaxis algorithm is proposed to solve multiobjective optimization problems. ...
., the authors propose an expert performance evaluation system based on a fuzzy logic model, with competences 360 ∘ feedback oriented to human behavior. ...
Acknowledgments We wish to express our sincere appreciation to the authors for their excellent contributions. The hard work of all reviewers is greatly acknowledged. ...
doi:10.1155/2015/234176
fatcat:wswu5kwc35d3xedlkbtycstrum
A Systematic Review on Harmony Search Algorithm: Theory, Literature, and Applications
2021
Mathematical Problems in Engineering
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It has been used to solve the wide variety of real-life optimization problems due to its easy implementation over other metaheuristics. ...
Harmony search algorithm is the recently developed metaheuristic in the last decade. It mimics the behavior of a musician producing a perfect harmony. ...
Multiobjective HSA. ere are two approaches to solve the multiobjective problems. ese are weighted sum approach and Pareto-optimal front approaches. e former one tries to solve the multiobjective problem ...
doi:10.1155/2021/5594267
fatcat:dtpsvroglrf55mhgf4dypzbtki
Development of Multiobjective High-Level Synthesis for FPGAs
2020
Scientific Programming
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During the last two decades, several MOAs have been applied to solve this problem. This paper introduces a comprehensive analysis of different MOAs that are suitable to perform HLS for FPGA devices. ...
This process can be performed under a framework that is known as Design Space Exploration (DSE), which helps to determine the best design by addressing scheduling, allocation, and binding problems, all ...
Special thanks are due to Rogelio Valdez PhD student. We also thank Dr. Daniel E. ...
doi:10.1155/2020/7095048
fatcat:h3iow4op4ventnhcpvazze3p4e
A new multiobjective evolutionary algorithm
2002
European Journal of Operational Research
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ALSO D De, S Ray, A Konar, A Chatterjee (2005) A Fuzzy Logic Controller Based Dynamic Routing Algorithm with SPDE based Differential Evolution, GECCO 119. ...
S Agrawal, Y Dashora, MK Tiwari, YJ Son (2008) Interactive Particle Swarm: A Pareto-Adaptive Metaheuristic to Multiobjective Optimization, IEEE Transactions on Systems, Man, and Cybernetics-Part A: Systems ...
doi:10.1016/s0377-2217(01)00190-4
fatcat:kndbzvq6jrgnromsrtx2jc6mji
Sustainable Aviation Electrification: A Comprehensive Review of Electric Propulsion System Architectures, Energy Management, and Control
2022
Sustainability
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Then, the challenges and technical barriers of electrified aircraft propulsion control system design are discussed, followed by a summary of the control methods frequently used in aircraft propulsion systems ...
This review paper aims to provide a comprehensive and broad-scope survey of the recent progress and development trends in sustainable aviation electrification. ...
A fuzzy state machine (FSM)-based EMS has been proposed to control the power flow for a hybrid electric UAV for online application [117] . ...
doi:10.3390/su14105880
fatcat:3ympviy5k5faplzoi5qgwuz5bu
Bi-objective unrelated parallel machines scheduling problem with worker allocation and sequence dependent setup times considering machine eligibility and precedence constraints
2021
Journal of Industrial and Management Optimization
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In this study, a bi-objective unrelated parallel machine scheduling problem with worker allocation, sequence dependent setup times, precedence constraints, and machine eligibility is presented. ...
Because the problem is NP-hard, two metaheuristic algorithms, a multi-objective tabu search (MOTS) and a multi-objective simulated annealing (MOSA), are presented to tackle the problem. ...
A multi-objective parallel machine scheduling problem under fully fuzzy environment was investigated by Arık and Toksarı, in which fuzzy job deterioration effect, fuzzy learning effect and fuzzy processing ...
doi:10.3934/jimo.2021190
fatcat:et5rw3rd5fhwjan35qeqafzfuu
A Comprehensive Survey on Particle Swarm Optimization Algorithm and Its Applications
2015
Mathematical Problems in Engineering
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optimization), extensions (to multiobjective, constrained, discrete, and binary optimization), theoretical analysis (parameter selection and tuning, and convergence analysis), and parallel implementation ...
On the other hand, we offered a survey on applications of PSO to the following eight fields: electrical and electronic engineering, automation control systems, communication theory, operations research ...
coming from a fuzzy logic controller. ...
doi:10.1155/2015/931256
fatcat:ubc5eywnhzdjllxjaywe4czhnm
A New Imperialist Competitive Algorithm for Multiobjective Low Carbon Parallel Machines Scheduling
2018
Mathematical Problems in Engineering
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This paper considers low carbon parallel machines scheduling problem (PMSP), in which total tardiness is regarded as key objective and total energy consumption is a non-key one. ...
A lexicographical method is used to compare solutions and a novel imperialist competitive algorithm (ICA) is presented, in which a new strategy for initial empires is adopted. ...
However, as stated above, ICA is not used to solve the problem of low carbon parallel machine scheduling. ...
doi:10.1155/2018/5914360
fatcat:ekyjm6vchnaqldofmfn7ru6k3m
A multi objective volleyball premier league algorithm for green scheduling identical parallel machines with splitting jobs
2020
Applied intelligence (Boston)
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This paper proposes a mathematical model for scheduling parallel machines with splitting jobs and resource constraints. ...
AbstractParallel machine scheduling is one of the most common studied problems in recent years, however, this classic optimization problem has to achieve two conflicting objectives, i.e. minimizing the ...
Chen [15] developed a column generation based branch and bound method to solve simultaneous job scheduling and resource allocation problems. ...
doi:10.1007/s10489-020-02027-1
fatcat:5ptss32qkbetzich5j6cw7gu4m
Meta-heuristics for manufacturing scheduling and logistics problems
2013
International Journal of Production Economics
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In addition, the authors employed an extended priority-based encoding method, combining a local search (LS) technique and a new fuzzy logic control (FLC) to enhance the search ability of the hybrid evolutionary ...
Chen et al. (2013) proposed a hybrid approach based on the variable neighborhood search and particle swarm optimization for parallel machine scheduling problems. ...
doi:10.1016/j.ijpe.2012.09.004
fatcat:ri2ogbsa6rbqpi2s3vnkenhhz4
Learnheuristics: hybridizing metaheuristics with machine learning for optimization with dynamic inputs
2017
Open Mathematics
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Learnheuristics can be used to solve combinatorial optimization problems with dynamic inputs (COPDIs). ...
On the contrary, they might vary in a predictable (non-random) way as the solution is partially built according to some heuristic-based iterative process. ...
Likewise, we want to thank the support of the UOC doctoral programme. ...
doi:10.1515/math-2017-0029
fatcat:ktigbziemvel3a5mpxjfz6dsra
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