Title: A multi-objective optimisation model for production and transportation planning in a marine shrimp farming supply chain network

Authors: Chaimongkol Limpianchob; Masahiro Sasabe; Shoji Kasahara

Addresses: Graduate School of Information Science, Nara Institute of Science and Technology, 8916-5 Takayama-cho, Ikoma, Nara, Japan; Faculty of Engineering at Kamphaeng Saen, Kasetsart University, 1 Moo 6, Kamphaeng Saen, Nakhon Pathom, Thailand ' Division of Information Science, Nara Institute of Science and Technology, 8916-5 Takayama-cho, Ikoma, Nara, Japan ' Division of Information Science, Nara Institute of Science and Technology, 8916-5 Takayama-cho, Ikoma, Nara, Japan

Abstract: The traditional operation of marine shrimp farming is widely practiced in Southeast Asia. Giant freshwater prawn farming is one of the main types of marine shrimp farming that also still operates traditionally. Many of these farms operate without advanced techniques for production planning, inventory control, and transportation strategic decisions throughout the supply chain network which are among the most important managerial activities in commercial farming. Maintaining product freshness is of vital importance for aquaculture product. Therefore, this paper develops a multi-objective mixed-integer linear programming model for a marine shrimp farming supply chain network design problem. The problem is to plan production and control inventory according to constraints while maximise total profit surplus and minimise shortest route. A multi-echelon, multi-facility, and multi-period mathematical model is proposed such that real conditions are considered. In the end, some numerical illustrations are provided to show the proper Pareto solutions considering all of the objectives for the decision maker.

Keywords: supply chain network; SCN; mixed-integer linear programming; marine shrimp farming; giant freshwater prawns; multi-objective optimisation.

DOI: 10.1504/IJOR.2022.125727

International Journal of Operational Research, 2022 Vol.45 No.1, pp.1 - 28

Received: 01 Aug 2019
Accepted: 21 Dec 2019
Published online: 27 Sep 2022 *

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