Three-stage location-routing programming for heavy-duty railway maintenance machinery maintenance base based on multi-factor combined weights

Abstract

An imperative shift towards a scientific and methodical approach has become increasingly essential when deliberating the placement of maintenance bases for robust railway machinery dedicated to heavy-duty tasks. This article addresses the need for a systematic approach to placing maintenance bases for robust heavy-duty railway machinery. It introduces a meticulously crafted three-stage location-routing paradigm that factors in both qualitative and quantitative determinants. This approach optimizes routing strategies for the machinery while constructing an evaluative framework for base placement. An evaluative index is created by merging relevant qualitative and quantitative elements, using an enhanced game theory methodology combined with the evidential analytic hierarchy process and the entropy weight method to balance subjective and objective considerations. The model’s complexity is handled with an improved genetic algorithm and a hybrid ant colony algorithm, effectively addressing location and routing interactions. Practical implementation and case studies validate the model’s and algorithm’s efficacy, confirming their applicability in real-world scenarios.