EURO 2024 Copenhagen
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4378. Simulation-based Multi-objective Optimization for Fleet Resource Planning in a Convenience Store Supply Chain

Invited abstract in session WB-50: Retail Distribution II, stream Retail Operations.

Wednesday, 10:30-12:00
Room: M2 (building: 101)

Authors (first author is the speaker)

1. Thai-Young Kim
International Logistics, Chung-Ang University
2. Benjawan Sopun
International Logistics, Chung-Ang University

Abstract

Fleet planning is a key success factor of retail management in the convenience store industry where a wide range of goods are replenished on a daily basis. The operational challenge in this industry is to decide the size of transport equipment – reefer truck and dry truck in an optimized manner. The idea to get some flexibility in the fleet pool decision is that the reefer truck can be used as a dry truck if the temperature control is disabled with limited cost increases. In this study, a simulation approach categorized as Digital SC twins is selected to demonstrate the benefits of increasing compatibility by opting for a mixed-truck policy including the optimal fleet size and timeline. The study optimizes the mixed vehicle in terms of fleet maximizing the service level while minimizing costs by applying the proposed policy. To set up a real-life simulation baseline, a convenience store supply chain in South Korea was modeled with some operation parameters. Initial simulation revealed the impact of time windows on reducing the number of vehicles used in standard operation. The second experiment investigated the effect of reefer trucks ratio to dry trucks under each time window standard operation. The finding is that the optimized fleet planning enables the supply chain to maintain the same level of on-time delivery even with fewer vehicles. It can effectively resolve the issue of delayed delivery due to insufficient capacity while reducing total costs and travel distances.

Keywords

Status: accepted

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