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Meta-heuristics algorithm for two-machine no-wait flow-shop scheduling problem with the effects of learning

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In this research, we put the development of a no-wait flow-shop scheduling model alongside with the effect of learning into consideration to minimize the cost of consumption of resources. | Meta-heuristics algorithm for two-machine no-wait flow-shop scheduling problem with the effects of learning Uncertain Supply Chain Management 7 2019 599 618 Contents lists available at GrowingScience Uncertain Supply Chain Management homepage www.GrowingScience.com uscm Meta-heuristics algorithm for two-machine no-wait flow-shop scheduling problem with the effects of learning Faramarz Nouria Saeede Samadzada and Javid Ghahremani Nahra a Faculty member of Development and Planning Institute of ACECR Iran CHRONICLE ABSTRACT Article history In today s world due to rapid changes in the market scheduling as one of the most fundamental Received April 6 2019 issues of competitive production plays a very important role in maintaining the competitive Received in revised format May position and survival of manufacturing organizations therefore development of scheduling 10 2019 models in order to improve the timing criteria is of great importance. In this research we put Accepted May 18 2019 Available online the development of a no-wait flow-shop scheduling model alongside with the effect of learning May 18 2019 into consideration to minimize the cost of consumption of resources. Finding the correct Keywords sequence of two machines performance and optimized allocation of the resources for any Uninterrupted flow-shop performance on each machine were considered as the main goal in this study. To solve the scheduling problem metaheuristic genetic algorithms particle swarm optimization imperialist Learning effect competitive algorithms optimization of the whale and the League Champions algorithms have Metaheuristic algorithms been used. The statistical comparisons and also using of TOPSIS Multi-Criteria Decision Intermittent tasks Making method indicate high level of efficiency of the League Champions algorithm with the utility weight of 0.9516. 2019 by the authors licensee Growing Science Canada. 1. Introduction Determining the program of priority and operation sequence in .