Genetic Algorithm and Particle Swarm Optimization on Fertilizer Production Planning Optimization

Anshori, Mohamad Yusak and Herlambang, Teguh and Rahmalia, Dinita (2019) Genetic Algorithm and Particle Swarm Optimization on Fertilizer Production Planning Optimization. Proceedings of the 1st International Conference on Business, Law And Pedagogy, ICBLP. ISSN 978-1-63190-199-7

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Official URL: https://eudl.eu/doi/10.4108/eai.13-2-2019.2286495

Abstract

Production planning is the important part of controlling the cost spent by the company. In this research, production planning model is linear integer programming model with constraints : production, worker, and inventory. Linear integer programming as optimization problem can be solved by exact method like branch and bound, cutting plane or heuristic method. In this paper, we use heurisitic like Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) for solving production planning optimization in approaching. GA uses natural selection process of chromosomes while PSO is inspired by the behavior of flocks of birds, swarm of insects, or school of fish. The simulations show that both GA and PSO can find optimal solution of fertilizer production planning in approaching.

Item Type: Article
Uncontrolled Keywords: Linear Integer Programming, Constrained Optimization, Genetic Algorithm, Particle Swarm Optimization, Production Planning Optimization
Subjects: T Technology > TA Engineering (General). Civil engineering (General)
Divisions: Faculty of Economics and Business > Program Study of Management
Depositing User: Mr. . Aji
Date Deposited: 17 Jun 2020 04:00
Last Modified: 24 Sep 2020 01:31
URI: http://repository.unusa.ac.id/id/eprint/6123

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