Integrating car path optimization with train formation plan: a non-linear binary programming model and simulated annealing based heuristics

TL;DR

This paper presents a non-linear binary programming model and a simulated annealing heuristic to optimize freight transportation by integrating car path and train formation planning, considering operational constraints and costs.

Contribution

It introduces an integrated optimization model for railcar routing and train formation, addressing operational constraints and proposing a heuristic solution approach.

Findings

The model effectively minimizes total transportation and reclassification costs.

The simulated annealing heuristic provides high-quality solutions efficiently.

The approach handles complex capacity constraints successfully.

Abstract

An essential issue that a freight transportation system faced is how to deliver shipments (OD pairs) on a capacitated physical network optimally; that is, to determine the best physical path for each OD pair and assign each OD pair into the most reasonable freight train service sequence. Instead of pre-specifying or pre-solving the railcar routing beforehand and optimizing the train formation plan subsequently, which is a standard practice in China railway system and a widely used method in existing literature to reduce the problem complexity, this paper proposes a non-linear binary programming model to address the integrated railcar itinerary and train formation plan optimization problem. The model comprehensively considers various operational requirements and a set of capacity constraints, including link capacity, yard reclassification capacity and the maximal number of blocks a yard can be formed, while trying to minimize the total costs of accumulation, reclassification and transportation. An efficient simulated annealing based heuristic solution approach is developed to solve the mathematical model. To tackle the difficult capacity constraints, we use a penalty function method. Furthermore, a customized heuristics for satisfying the operational requirements is designed as well.