SeJoon Park, NagYoon Song, Wooyeon Yu, and Dohyun Kim. IJFIS 2019;19:307-14. https://doi.org/10.5391/IJFIS.2019.19.4.307

In this research, a truck scheduling problem for a cross-docking system with multiple receiving and shipping docks is studied. Until recently, single-dock cross-docking problems are studied mostly. This research is focused on the multiple-dock problems. The objective of the problem is to determine the best docking sequences of inbound and outbound trucks to the receiving and shipping docks, respectively, which minimize the maximal completion time. We propose a new hybrid genetic algorithm to solve this problem. This genetic algorithm improves the solution quality through the population scheme of the nested structure and the new product routing heuristic. To avoid unnecessary infeasible solutions, a linked-chromosome representation is used to link the inbound and outbound truck sequences, and locus-pairing crossovers and mutations for this representation are proposed. As a result of the evaluation of the benchmark problems, it shows that the proposed hybrid GA provides a superior solution compared to the existing heuristics.

Recently, carsharing has emerged as an alternative to vehicle ownership in many countries worldwide. This study examines the system parameters of one-way carsharing systems to determine a trade-off between the lost sales rate and system parameters. Four system parameters are considered in this study, namely average number of vehicles per station, rate of one-way trip, average number of staffs per station, and relocation policy. The performance of round-trip carsharing systems is also compared to that of one-way carsharing systems. A regression model is developed to predict the lost sales rate based on the various operational conditions for a one-way carsharing system. The findings of the study provide tools to understand the impact of carsharing system parameters on the efficiency of carsharing operations and predict the performance of such systems when any modifications occur.