Preference-Based Multi-Objective Optimization for Synchromodal Transport Using Adaptive Large Neighborhood Search

Decision-makers in synchromodal transport (ST) have different preferences toward objectives, such as cost, time, and emissions. To solve the conflicts among objectives obtain preferred solutions, a preference-based multi-objective optimization model is developed. In ST, containers need to be transferred across modes, therefore problem formulated pickup delivery with transshipment. The of decision-makers are usually expressed linguistic terms, so weight intervals, that is, minimum maximum weights, assigned represent vague preferences. An adaptive large neighborhood search developed used non-dominated solutions construct Pareto frontier. Moreover, synchronization an important feature ST it makes available resources fully utilized. Therefore, four cases identified studied make outgoing vehicles cooperate changes incoming vehicles’ schedules at transshipment terminals. Case studies Rhine-Alpine corridor designed results show proposed approach provides which line mode share under analyzed, signals sustainability policies transportation will influence share.