Production Planning System with Multi-Stages for Controlling Bullwhip Effect by Using Particle Swarm Optimization

Abstract

In a manufacturing industry, establishment of the mass customization which is the management system that produces a product efficiently with diversification of a customer's request is pressing need. When the demand quantity is known, the new production plan system which performs mass customization had already been presented. In this paper, when the demand quantity is unknown, we proposed the model of mass customization about production and inventory planning. A new model is formulated as a linear programming problem based on a MIN-MAX strategy. This model can be used when demand quantity is not given. In this paper, we use the particle swarm optimization which is one of the methods of optimization problem in order to solve this model.

Adaptive heterogeneous particle swarm optimization with comprehensive learning strategy

“…The PSO algorithm was firstly introduced by Kennedy and Eberhart in 1995. Since the PSO algorithm is easy to implement and has good performance on various problems, it has been applied to a wide range of fields, such as scheduling problems (Araki and Yoshitomi, 2016;Marichelvam et al, 2020;Ding and Gu, 2020), supply chain management (Mousavi et al, 2017;Patne et al, 2018;Zhang et al, 2020), robot path planning (Ayari and Bouamama, 2017;Li and Chou, 2018;Das and Jena, 2020) and many others (Domoto et al, 2007;Duan and Hao, 2014;Kawanishi et al, 2016;Liu and Nishi, 2020;Nonoyama et al, 2022).…”