Green road–rail intermodal routing problem with improved pickup and delivery services integrating truck departure time planning under uncertainty: an interactive fuzzy programming approach

Abstract This paper addresses the multi-objective optimization for road–rail intermodal routing problem that aims to minimize total costs and carbon dioxide emissions of routes. To achieve high timeliness entire transportation process, pickup delivery services are simultaneously improved based on employment fuzzy soft time windows measure their service levels. The modeling considers fixed schedules rail flexibility road match real-world scenario, in which travel times emission factors considered be time-varying. improve feasibility routing, uncertainty capacities incorporated into problem. By applying trapezoidal numbers formulate uncertainty, we propose a nonlinear model integrates truck departure planning services. After processing with chance-constrained programming linearization, obtain an auxiliary equivalent crisp linear solve it by designing interactive approach Bounded Objective Function method. Based empirical case study, demonstrate validity proposed discuss effects improving confidence levels results. analysis reveals several managerial insights help realize efficient organization making effective trade-offs among lowering costs, reducing emissions, levels, enhancing feasibility.