Genetic Algorithm for Solving the Integrated Production-Distribution-Direct Transportation Planning

Santoso, Amelia and Bahagia, Senator Nur and Suprayogi, Suprayogi and Sasongko, Dwiwahju (2008) Genetic Algorithm for Solving the Integrated Production-Distribution-Direct Transportation Planning. In: APIEMS 2008: Proceedings of The 9th Asia Pasific Industrial Engineering & Management Systems Conference, December 3rd – 5th, 2008, Nusa Dua, Bali.

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Abstract

This paper proposes a model of integrated production, distribution and transportation planning for 4-echelon supply chain system that consists of a manufacturer using a continuous production process, a distribution center, distributors and retailers. By means of time-dependent demand at all retailers and direct transportation from one echelon to its successive echelons, the purpose of this paper is to determine production/replenishment and transportation policies at manufacturer, distribution center, distributors and retailers in order to minimize annually total system cost. Due to the proposed model is classified as a mixed integer non-linear programming so it is almost impossible to solve the model using the exact optimization methods and a lot of time is needed when the enumeration methods is applied to solve only a small scale problem. In this paper, we apply the genetic algorithm for solving the model. Using integer encoding for constructing the chromosome, the best solution is going to be searched. Compared with enumeration method, the difference of the result is only 0.0594% with the consumption time is only 0.5609% time that enumeration methods need.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Production, Distribution, Direct Transportation, Genetic Algorithm
Subjects: T Technology > T Technology (General)
Divisions: Faculty of Engineering > Department of Industrial Engineering
Depositing User: Ester Sri W. 196039
Date Deposited: 22 May 2021 04:46
Last Modified: 22 May 2021 04:46
URI: http://repository.ubaya.ac.id/id/eprint/39550

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