A Particle Swarm Optimization and Golden Section Search Based Hybridization Scheme to Solve Economic Lot Scheduling Problem Using Basic Period Approach

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Abstract: In this paper we suggest a hybridization scheme to solve Economic Lot Scheduling Problem (ELSP) using basic period approach. We proposed a hybrid approach based on Particle Swarm Optimization(PSO)to find the optimum value of ki’s and Golden Section Search (GSS) to find the optimum value of basic period T. The proposed hybridized scheme is compared with the best known Genetic Algorithm (GA) on Bomberger’sdataset. This hybridapproach is found competitive and efficient in solving Economic Lot Scheduling Problem and outperform the Genetic Algorithm on problems with lower machine utilization as well as higher machine utilization.

International Journal of Electrical Engineering and Computer Science, E-ISSN: 2769-2507, Volume 2, 2020, Art. #4

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Syed Hasan Adil, Kamran Raza, Syed Saad Azhar Ali, "A Particle Swarm Optimization and Golden Section Search Based Hybridization Scheme to Solve Economic Lot Scheduling Problem Using Basic Period Approach," International Journal of Electrical Engineering and Computer Science, vol. 2, pp. 20-25, 2020, DOI:
Syed Hasan Adil, Kamran Raza, Syed Saad Azhar Ali. A Particle Swarm Optimization and Golden Section Search Based Hybridization Scheme to Solve Economic Lot Scheduling Problem Using Basic Period Approach. International Journal of Electrical Engineering and Computer Science. 2020;2:20-25.
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