Meta-heuristic methods to solve the problem of subway station facilities in urban management

We consider several location inventory optimization models for the supply chain configuration of subway facilities. It includes several distribution centers and several retailers. Customer demand and redelivery time are considered random. The goal is to find the optimal locations for facilities and their inventory policy simultaneously. For this purpose, a two-phase approach based on queuing theory and stochastic optimization was developed. Today, meta-heuristic methods are often used to solve optimization problems such as facility design. in this study; The design of different units, stores, and rooms of a real large-scale subway was organized using three meta-heuristic methods: Migratory Bird Optimization (MBO), Taboo Search (TS), and Simulated Simulation (SA). The results were compared with the existing subway design. As a result, the meta-heuristic methods of MBO and SA have provided the best results that improve the efficiency of the existing subway design to an acceptable level.

Keywords:

Subway facilities problem , Migrating bird optimization , Optimization problem , Tabu search , Simulated Annealing