Designing a Location-Allocation and Optimal Capacity Determination Model for Supply Chain Components under Uncertainty

Sinisaz Shahshahani, Hamid; Sharifi, Mohammad; Akram, Asadollah; Khanali, Majid

doi:10.22103/bbr.2026.27578.1162

Designing a Location-Allocation and Optimal Capacity Determination Model for Supply Chain Components under Uncertainty

Articles in Press

Document Type : Original Research

Authors

Hamid Sinisaz Shahshahani

Mohammad Sharifi

Asadollah Akram

Majid Khanali

Department of Agricultural Machinery Engineering, Faculty of Agricultural Engineering and Technology, College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran.

10.22103/bbr.2026.27578.1162

Abstract

This research aims to design an optimal and adaptive supply chain network for sea cage aquaculture in southern Iran. It implements the optimal location and capacity of production, processing and distribution facilities in 11 coastal nodes to create a balance in economic efficiency, social justice and environmental sustainability. A scenario-based multi-objective mixed integer linear programming model has been developed in Python using PuLP. Three objective functions minimize the total cost, maximize socio-spatial weighted employment in underdeveloped areas, and minimize energy emission of production and transportation. A robust minmax optimization approach investigates demand uncertainty as well as cost in optimistic, normal and pessimistic scenarios. The ϵ constraint method has created a Pareto frontier for trade-off analysis. Purely economic optimization has concentrated capacity in relatively developed areas such as Qeshm and has ultimately led to geographical imbalance (CV=49%). Accordingly, Pareto analysis has proposed point P3 as the most sustainable solution. In this solution, which has led to a 52% increase in employment in underdeveloped areas, regional equity has also improved significantly. At this point, CV has reduced capacity to 20% and ultimately 70% of employment is guaranteed in coastal areas. Integrated multi-objective planning can create a suitable framework for resilient industrial development as well as spatial equity in southern Iran in the supply chain under study.

Keywords

Marine Cage Aquaculture

Supply Chain Optimization

Multi-Objective Programming

Regional Development

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