Distribution logistics network optimization with a multi-distribution center considering carbon emission: A case study in the petrochemical industry in Thailand

Abstract

The study explores the optimization of the distribution network for a petrochemical business in Thailand, facing intense competition and market share loss to foreign competitors. Aiming to expand its domestic market, the business seeks to enhance its distribution network by adding a new distribution center (DC). Given the industry’s environmental impact concerns, the study also focuses on reducing the environmental footprint of its supply chain and logistics activities. Despite extensive research on distribution network optimization, there remains a gap in understanding the integrated approach that simultaneously address economic efficiency, customer responsiveness, and environmental sustainability within the petrochemical sector in Thailand. This research proposes various scenarios for the distribution network, considering candidate DC locations based on current customer distributions, particularly in the Bangkok Metropolitan Area and Laem Chabang (LCB) port, along with potential hinterland arears. The analysis evaluates key performance metrics, including responsiveness, economic efficiency, and environmental impact. The findings indicate that the optimal scenario involves operating two DCs: the existing DC and a new DC in Samut Prakarn Province, significantly improving customer responsiveness. However, the results reveal that cost reduction does not directly correlate with decreased GHG emissions. The study underscores the need for businesses to define clear objectives, such as cost reduction, improved customer service, market expansion, or environmental sustainability, before redesigning distribution networks. A comprehensive evaluation of criteria, including social, opportunities, infrastructure, accessibility, resilience, and cybersecurity, is essential for informed decision-making, leading to improved cost efficiency, customer service, and operational agility.