Route-Constrained Optimization Models for Electric School Bus Allocation and Stop Sequencing

This study underscores the growing need to transition from conventional school buses powered by internal combustion engines to electric school buses (ESBs). We propose mixed integer programming (MIP)-based approaches to optimize the allocation of ESBs to predetermined routes while determining their travel paths and bus stop sequences. The problem formulation incorporates heterogeneous ESBs with mixed student loading. Essential factors such as bus seating capacity, battery capacity, energy consumption cost, and procurement cost are considered to determine optimal bus selection and allocation strategies that minimize total expenses. To address this challenge, we introduced two methodologies: a MIP-based optimization model and a two-stage hybrid model that integrates optimization with heuristic approaches. We evaluate the efficiency of the proposed approaches through nineteen computational scenarios and compare their performance. The results indicate that the hybrid model significantly improves computational efficiency for large-scale problem instances, demonstrating its potential as a scalable tool for strategic planning.