Evolution Algorithm On Truck Scheduling Optimization At A Cold-Chain Cross-Docking Terminal In The Floral Industry

Abstract

Flowers that deteriorate over time are handled by many supply systems. A significant number of flowers are wasted because of poor supply chain management, which causes significant financial losses. Although cross-docking terminals are often employed in cold supply chains for product distribution, they have not obtained sufficient interest in the research field. This study offers a mixed-integer mathematical model for truck scheduling optimization at a cold-chain cross-docking terminal to increase the effectiveness of flower delivery. This study focuses on the case of the Sinofar Flower Company with the aim to minimize the waiting cost and delayed cost during truck scheduling. A specialized Evolutionary Algorithm, which is inherited from the First come-first-served policy, was created to address the problem due to the suggested model's complexity. A thorough comparison with IBM Cplex Optimization is used to evaluate the created algorithm's computing performance throughout the numerical measurement. Additionally, the suggested approach exhibits a satisfactory steady state of its solution quality. The distribution of flowers in cold supply chains involves several supply chain stakeholders, hence extra sensitivity studies are conducted in order to draw some significant management implications that may be of interest to them.