Journal ArticleDOI
An efficient genetic algorithm for hybrid flow shop scheduling with multiprocessor task problems
Orhan Engin,Gülşad Ceran,Mustafa Yilmaz +2 more
- Vol. 11, Iss: 3, pp 3056-3065
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TLDR
The computational results indicated that the proposed genetic algorithm approach is very effective in terms of reduced total completion time or makespan (C"m"a"x) for the attempted problems.Abstract:
The hybrid flow shop scheduling with multiprocessor task (HFSMT) problem is a substantial production scheduling problem for minimizing the makespan, and there exist many difficulties in solving large scale HFSMT problems which include many jobs, machines and tasks. The HFSMT problems known as NP-hard and the proposal of an efficient genetic algorithm (GA) were taken into consideration in this study. The numerical results prove that the computational performance of a GA depends on the factors of initial solution, reproduction, crossover, and mutation operators and probabilities. The implementation details, including a new mutation operator, were described and a full factorial experimental design was determined with our GA program by using the best values of the control parameters and the operators. After a comparison was made with the studies of Oguz [1], Oguz and Ercan [2] and Kahraman et al. [3] related to the HFSMT problems, the computational results indicated that the proposed genetic algorithm approach is very effective in terms of reduced total completion time or makespan (C"m"a"x) for the attempted problems.read more
Citations
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Journal ArticleDOI
Efficient multi-objective optimization algorithm for hybrid flow shop scheduling problems with setup energy consumptions
TL;DR: An energy-aware multi-objective optimization algorithm for solving the hybrid flow shop (HFS) scheduling problem with consideration of the setup energy consumptions with the highly effective proposed EA-MOA algorithm compared with several efficient algorithms from the literature.
Journal ArticleDOI
Improved cuckoo search algorithm for hybrid flow shop scheduling problems to minimize makespan
TL;DR: A recently developed cuckoo search (CS) metaheuristic algorithm is presented in this paper to minimize the makespan for the HFS scheduling problems and computational results show that the ICS algorithm outperforms many other metaheuristics.
Journal ArticleDOI
CLPS-GA: A case library and Pareto solution-based hybrid genetic algorithm for energy-aware cloud service scheduling
TL;DR: A more comprehensive and accurate model for OSCR is formulated and on the basis of classic multi-objective genetic algorithm, a case library and Pareto solution based hybrid Genetic Algorithm (CLPS-GA) is proposed to solve the model.
Journal ArticleDOI
A review of applications of genetic algorithms in operations management
TL;DR: A review of the literature on OM with GA-based solutions and possible gaps to suggest possible gaps from the point of view of researchers and practitioners to pave the path for future research to apply GAs to solve OM problems.
Journal ArticleDOI
A new hybrid ant colony optimization algorithm for solving the no-wait flow shop scheduling problems
Orhan Engin,Abdullah Güçlü +1 more
TL;DR: The computational experiments show that the proposed Hybrid Ant Colony algorithm provides better results relative to the other algorithms, compared to the Adaptive Learning Approach and Genetic Heuristic algorithm.
References
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Book
Genetic algorithms in search, optimization, and machine learning
TL;DR: In this article, the authors present the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields, including computer programming and mathematics.
Genetic algorithms in search, optimization and machine learning
TL;DR: This book brings together the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields.
MonographDOI
Genetic algorithms and engineering optimization
Mitsuo Gen,Runwei Cheng +1 more
TL;DR: This paper presents a meta-modelling framework that automates the very labor-intensive and therefore time-heavy and therefore expensive and labor-heavy process of designing and solving optimization problems.
Journal ArticleDOI
Evolutionary computation: comments on the history and current state
TL;DR: The purpose, the general structure, and the working principles of different approaches, including genetic algorithms (GA), evolution strategies (ES), and evolutionary programming (EP) are described by analysis and comparison of their most important constituents (i.e. representations, variation operators, reproduction, and selection mechanism).
Journal ArticleDOI
A Fast Taboo Search Algorithm for the Job Shop Problem
TL;DR: A fast and easily implementable approximation algorithm for the problem of finding a minimum makespan in a job shop is presented, based on a taboo search technique with a specific neighborhood definition which employs a critical path and blocks of operations notions.
Related Papers (5)
A Genetic Algorithm for Hybrid Flow-shop Scheduling with Multiprocessor Tasks
Ceyda Oĝuz,M. Fikret Ercan +1 more