Application of chicken swarm optimization algorithm for multi objective scheduling problems in FMS

Scheduling plays an important role in Flexible Manufacturing System (FMS).Various Evolutionary Algorithms are used by different researchers to solve the multi objective scheduling problems. However, solutions obtained by some of these algorithms suffer from various issues such as struck in local opt...

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Vydáno v:Materials today : proceedings Ročník 72; s. 1457 - 1461
Hlavní autor: Satish Kumar, B.
Médium: Journal Article
Jazyk:angličtina
Vydáno: Elsevier Ltd 2023
Témata:
Chicken swarm optimization algorithm
Combined objective function
Genetic algorithms
Jaya algorithm
Multi objective scheduling
Jaya algorithm
Multi objective scheduling
Combined objective function
Chicken swarm optimization algorithm
Genetic algorithms
ISSN:2214-7853, 2214-7853
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Shrnutí:Scheduling plays an important role in Flexible Manufacturing System (FMS).Various Evolutionary Algorithms are used by different researchers to solve the multi objective scheduling problems. However, solutions obtained by some of these algorithms suffer from various issues such as struck in local optima, not support deadline constraint, poor convergence speed etc. In this paper, a new optimization technique called Chicken Swarm Optimization (CSO) algorithm is implemented for optimum scheduling of Multi objective Scheduling problems considered from the literature. The Combined Objective Function (COF) is formulated by considering two objectives such as Minimization of machine idle time and Penalty cost minimization with equal weight-ages. MATLAB code has developed to determine the COF values and also for implementing CSO to obtain the optimum solution. It is observed that, the results obtained by CSO algorithm are very competitive when compared with other well-known algorithms like Genetic Algorithms (GA), Cuckoos Search Algorithm (CSA), Modified Cuckoos Search Algorithm (MCSA) & Jaya Algorithm (JA)
ISSN:2214-7853
2214-7853
DOI:10.1016/j.matpr.2022.09.345