A Matheuristic Approach Combining Local Search and Mathematical Programming

Carolina Lagos,Stefanie Niklander,Guillermo Guerrero,Fernando Paredes,Jorge Vega,Franklin Johnson,Enrique Cabrera

doi:10.1155/2016/1506084

Abstract

A novel matheuristic approach is presented and tested on a well-known optimisation problem, namely, capacitated facility location problem (CFLP). The algorithm combines local search and mathematical programming. While the local search algorithm is used to select a subset of promising facilities, mathematical programming strategies are used to solve the subproblem to optimality. Proposed local search is influenced by instance-specific information such as installation cost and the distance between customers and facilities. The algorithm is tested on large instances of the CFLP, where neither local search nor mathematical programming is able to find good quality solutions within acceptable computational times. Our approach is shown to be a very competitive alternative to solve large-scale instances for the CFLP.

Highlights

The capacitated facility location problem (CFLP) is one of the most important problems for companies which distribute products to their customers
In this subsection we present a summary of the obtained results
Column Time corresponds to average time the algorithm takes to find the best solution, while k column shows the iteration where the best solution was found by each algorithm

Summary

Introduction

The capacitated facility location problem (CFLP) is one of the most important problems for companies which distribute products to their customers. The problem consists of selecting specific sites at which to install plants, warehouses, and distribution centres while assigning customers to service facilities and interconnecting facilities using flow assignment decisions. This paper considers a two-level supply chain in which a single plant serves a set of warehouses, which in turn serve a set of end customers or retailers. We aim to solve this problem by finding a set of locations that allows us to serve the entire set of customers in an optimal way.

Objectives

Results

Conclusion