Research on Multi-Objective Optimization-Based Planning Model for Energy Supplement Stations of Electric Ships

Electric ships have emerged as a key direction for the green transformation of inland waterway transportation due to their zero-emission and low-noise advantages. Rational planning of electric ship stations is crucial to ensuring efficient operation, directly influencing operational efficiency, service quality, and investment returns. Against the backdrop of the dual-carbon goals and the upgrading of inland waterway transportation infrastructure, the scientific layout of charging stations has become an urgent practical demand to break through the bottlenecks of electric ship development. Addressing the station planning problem, this study constructs a multi-objective optimization model integrating four core objectives: demand coverage, construction and operation costs, charging service efficiency, and environmental impact. An improved Non-dominated Sorting Genetic Algorithm III (NSGA-III) is employed to solve the model, generating a Pareto optimal solution set. The entropy weight-TOPSIS method is further adopted for optimal scheme selection. A case study of an inland waterway transportation demonstration area validates the model, showing its ability to produce reasonable planning schemes under multi-objective constraints and providing decision support for electric ship infrastructure planning.