Research on an Optimization Model for Logistics Nodes System Layout and Its Solution Algorithm

Dezhi Zhang,Shuangyan Li

doi:10.5539/ijbm.v4n11p38

Abstract

Based on the logistics nodes system consisting of first-degree logistics node (logistics park) secondary logistics nodes (including logistics center and distribution center), a dynamic logistics nodes location model of multi-period , multi-type cargo flow and multiple logistics nodes is given. The optimization model considers the factors including fixed cost for logistics opening, handling cost and economic of scale of different type logistics nodes. An effective algorithm based on the improved minimum cost-maximal flow algorithm and genetic algorithm is presented according to the characteristic of optimization problem. Finally, a numerical example is provided to validate the proposed model and solution algorithm. The findings indicate that the model proposed in this paper is a useful tool for the investigation of the Multi-period and Multiple Logistics Node Dynamic Location Problem.

Highlights

The logistics network design of a city is very important to reduce the social distribution costs and improve the efficiency of distribution
Denis (1976) investigated the multi-commodity and multi-period e facility location problem, and gave the heuristics algorithm based on dynamic programming
Step 8: Calculating and sorting ascend the ratio of the using of all logistics nodes opening of the optimal solution under T=1, and closing the logistics nodes with less ratio of the using according to the above opening rule

Summary

Introduction

The logistics network design of a city is very important to reduce the social distribution costs and improve the efficiency of distribution. Ballou (1968) was the first to address the dynamic location problem and suggested a heuristic algorithm for its solution. Denis (1976) investigated the multi-commodity and multi-period e facility location problem, and gave the heuristics algorithm based on dynamic programming. Alexander (1991) studied the multi-period and multi-stages location problem, and solves the model by the Lagrangian heuristics combined with dynamic programming. John (1997) proposed a dynamic location model with uncertain quantity facilities by applying the heuristics based on decision criteria: the minimization of expected opportunity loss and the minimization of maximum regret. We present an optimization model to solve the capacitated, multi-commodity, multi-period, multi-class logistics node location problem. The fourth section presents an illustrated application, while the last section presents conclusions and suggestions for further research

Model formulation

Solution algorithm

A Numerical example

Conclusions