Volumetric optimization of freight cargo loading: Case study of a SMU forwarder

• Main Authors: LIM, Tristan, PING, Michael Ser Chong, GOH, Mark, TAN, Shi Ying Jacelyn
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2019
• Subjects: Case study; Fleet management; Genetic algorithm; Bin packing; Freight; Singapore; MITB student; Asian Studies; Numerical Analysis and Scientific Computing; Theory and Algorithms; Transportation
• Online Access: https://ink.library.smu.edu.sg/sis_research/5990; https://ink.library.smu.edu.sg/context/sis_research/article/6993/viewcontent/Proceeding2019Wurzburg___Paper_Only.pdf
• Institution: Singapore Management University

Purpose: Freight forwarders faces a challenging environment of high market volatility and margin compression risks. Hence, strategic consideration is given to undertaking capacity management and transport asset ownership to achieve longer term cost leadership. Doing so will also help to address management issues, such as better control of potential transport disruptions, improve scheduling flexibility and efficiency, and provide service level enhancement.Design/methodology/approach: The case company currently hastruck resource which is unprofitable, and the firm’s schedulers are having difficulty optimizing the loading capacity. We apply Genetic Algorithm (GA) to undertake volumetric optimization of truckcapacity and to build an easy-to-use platform to help determine potential costing savings that can be attained, and whether if the business should expand its internal truck fleet.Findings: Our analysis suggests that the case company’s truck resource is underutilized by about two-thirds of capacity. Through a proposed mathematical model and GA heuristic, the case company can potentially save up to S$567K per annum.Value: By using a simple GA and incorporating a visually appealing user interface, we have helped a freight forwarder improve her financial and operational efficiency. The game changer is the scalability of the solution to include more resource optimization across the fleet and across more freight forwarding firms.