Solving a Location-Allocation Problem with Logic-Based Benders' Decomposition

نویسندگان

  • Mohammad M. Fazel-Zarandi
  • J. Christopher Beck
چکیده

We address a location-allocation problem that requires deciding the location of a set of facilities, the allocation of customers to those facilities under facility capacity constraints, and the allocation of the customers to trucks at those facilities under per truck traveldistance constraints. We present a hybrid approach that combines integer programming and constraint programming using logic-based Benders’ decomposition. Computational performance against an existing integer programming model and a tabu search approach demonstrates that the Benders’ model is able to find and prove optimal solutions an order of magnitude faster than an integer programming model while also finding better feasible solutions in less time for the majority of problem instances when compared to the tabu search.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Scenario-based modeling for multiple allocation hub location problem under disruption risk: multiple cuts Benders decomposition approach

The hub location problem arises in a variety of domains such as transportation and telecommunication systems. In many real-world situations, hub facilities are subject to disruption. This paper deals with the multiple allocation hub location problem in the presence of facilities failure. To model the problem, a two-stage stochastic formulation is developed. In the proposed model, the number of ...

متن کامل

Robust uncapacitated multiple allocation hub location problem under demand uncertainty: minimization of cost deviations

The hub location–allocation problem under uncertainty is a real-world task arising in the areas such as public and freight transportation and telecommunication systems. In many applications, the demand is considered as inexact because of the forecasting inaccuracies or human’s unpredictability. This study addresses the robust uncapacitated multiple allocation hub location problem with a set of ...

متن کامل

A Benders\' Decomposition Based Solution Method for Solving User Equilibrium Problem: Deterministic and Stochastic Cases

The traffic assignment problem is one of the most important problems for analyzing and optimizing the transportation network to find optimal flows. This study presented a new formulation based on a generalized Benders' decomposition approach to solve its important part, i.e. user equilibrium problems, in deterministic and stochastic cases. The new approach decomposed the problem into a master p...

متن کامل

Reliable location-allocation model for congested systems under disruptions using accelerated Benders decomposition

This paper aims to propose a reliable location-allocation model where facilities are subject to the risk of disruptions. Since service facilities are expected to satisfy random and heavy demands, we model the congested situations in the system within a queuing framework which handles two sources of uncertainty associated with demand and service. To insure the service quality, a minimum limit re...

متن کامل

Evaluating the Effectiveness of Integrated Benders Decomposition Algorithm and Epsilon Constraint Method for Multi-Objective Facility Location Problem under Demand Uncertainty

One of the most challenging issues in multi-objective problems is finding Pareto optimal points. This paper describes an algorithm based on Benders Decomposition Algorithm (BDA) which tries to find Pareto solutions. For this aim, a multi-objective facility location allocation model is proposed. In this case, an integrated BDA and epsilon constraint method are proposed and it is shown that how P...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2009