Enhancing Economic and Operational Efficiency in Engineering Logistics: A Cost‐Optimization Model for Multimodal Transportation of Multi‐Commodity Materials

ABSTRACT

Efficient transportation of engineering materials is critical to the timely execution of large‐scale infrastructure projects, yet it is often challenged by heterogeneous material demand, multimodal transitions, dual‐layer capacity limitations (transport arcs and transshipment nodes), and schedule‐dependent time‐window requirements. To address these coupled decision features, this paper formulates an Engineering Material Multimodal Transport Path Planning model with Multi‐Commodity Flow under Time Window and Network Capacity (EM‐CMTP3MCTW), which minimizes a weighted‐sum objective of total transportation cost and total transportation time (including time‐window‐related penalties). To solve this NP‐hard problem at practical scales, we develop an improved parallel adaptive large neighbourhood search algorithm (GA‐PALNS) equipped with problem‐specific destroy‐and‐repair operators and a parallel evaluation mechanism. Computational experiments on randomly generated instances show that GA‐PALNS achieves lower objective values than representative single‐objective baselines (average improvement approximately 0.48%) while reducing runtime by roughly one order of magnitude. A real‐world case study from a major infrastructure project in Western China further demonstrates that the proposed framework can generate feasible and economically competitive multimodal transportation plans under complex capacity and time‐window constraints.