A Mixed-Integer Linear Programming Approach for the Sustainable Design and Planning System of Marine Shrimp Aquaculture Supply Chain Network

Abstract

Pacific white shrimp (Litopenaeus vannamei) is a marine shrimp species introduced by the Department of Fisheries for experimental farming. It is currently being considered as a viable alternative to tiger prawn farming, which faces challenges such as slow growth rates. Concurrently, some farmers have independently adopted white shrimp aquaculture and reported notable success, including higher production rates compared to tiger prawns. As a result, many farmers have transitioned to white shrimp farming. However, given that white shrimp is a relatively new species in Thailand’s aquaculture sector, farmers continue to face significant challenges in farm management, fry hatchery procurement, pond rotation, feeding, production inputs, harvesting, and transportation. These difficulties are primarily due to the absence of a structured farm management plan, which hinders farmers from achieving consistent, high-quality yields. To address these challenges, this research employs a mixed-integer linear programming (MILP) model to design and optimize the white shrimp aquaculture supply chain network. The model targets key aspects such as selecting fry hatchery dealers, managing farms (including shrimp pond rotation for continuous production), streamlining aquaculture operations, and optimizing shrimp harvesting for sale at shrimp floating raft markets. The primary objective is to maximize farmers' profits from shrimp aquaculture. The results indicate that the proposed MILP model functions effectively as a decision-support tool, achieving an 11.52% increase in profit compared to traditional manual planning methods.