QAPLIB - A Quadratic Assignment Problem Library

نویسندگان

  • Rainer E. Burkard
  • Stefan E. Karisch
  • Franz Rendl
چکیده

The Quadratic Assignment Problem (QAP) has remained one of the great challenges in combinatorial optimization. It is still considered a computationally nontrivial task to solve modest size problems, say of size n = 20: The QAPLIB was rst published in 1991, in order to provide a uni ed testbed for QAP, accessible to the scienti c community. It consisted of virtually all QAP instances that were accessible to us at that time. Due to the continuing demand for these instances, and the strong feedback from many researchers, we provided a major update in 1994, which was also accessible through anonymous ftp. In this update we also included many new problem instances, generated by several researchers for their own testing purposes. Moreover, we included a list of current champions, i.e. best known feasible solutions, and best lower bounds. The current update re ects on one hand the big changes in electronic communication. It has become a World Wide Web site, the QAPLIB Home Page. The online version will be updated on a regular basis and also contains most of the currently best known permutations. On the other hand, we feel the update was necessary, due to the increased research activities around the QAP, carried out in the last years. Therefore we also include a short list of dissertations concerning QAP, which were written in the last few years.

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

Exploiting group symmetry in semidefinite programming relaxations of the quadratic assignment problem

We consider semidefinite programming relaxations of the quadratic assignment problem, and show how to exploit group symmetry in the problem data. Thus we are able to compute the best known lower bounds for several instances of quadratic assignment problems from the problem library: [R.E. Burkard, S.E. Karisch, F. Rendl. QAPLIB — a quadratic assignment problem library. Journal on Global Optimiza...

متن کامل

Solving the Quadratic Assignment Problems by a Genetic Algorithm with a New Replacement Strategy

This paper proposes a genetic algorithm based on a new replacement strategy to solve the quadratic assignment problems, which are NP-hard. The new replacement strategy aims to improve the performance of the genetic algorithm through well balancing the convergence of the searching process and the diversity of the population. In order to test the performance of the algorithm, the instances in QAP...

متن کامل

Tightening a Discrete Formulation of the Quadratic Assignment Problem

The quadratic assignment problem is a well studied and notoriously difficult combinatorial problem. Recently, a discrete linear formulation of the quadratic assignment problem was presented that solved five previously unsolved instances from the quadratic assignment library, QAPLIB, to optimality. That formulation worked especially well on sparse instances. In this paper we show how to tighten ...

متن کامل

A linear formulation with O(n) variables for the quadratic assignment problem

We present an integer linear formulation that uses the so-called “distance variables” to solve the quadratic assignment problem (QAP). The model involves O(n) variables. Valid equalities and inequalities are additionally proposed. We further improved the model by using metric properties as well as an algebraic characterization of the Manhattan distance matrices that Mittelman and Peng [28] rece...

متن کامل

Defining Tabu Tenure for the Quadratic Assignment Problem

Tabu search (TS) algorithms are among the most efficient heuristic techniques in combinatorial optimization. Within these algorithms, it is important that the proper policies for maintaining the tabu tenure (tabu list size) are applied. In this paper, we discuss the mechanisms of defining the tabu tenure for the famous combinatorial optimization problem − the quadratic assignment problem (QAP)....

متن کامل

An Intensive Search Algorithm for the Quadratic Assignment Problem

Many heuristics, such as simulated annealing, genetic algorithms, greedy randomized adaptive search procedures are stochastic. In this paper, we propose a deterministic heuristic algorithm, which is applied to the quadratic assignment problem. We refer this algorithm to as intensive search algorithm (or briefly intensive search). We tested our algorithm on the various instances from the library...

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:
  • J. Global Optimization

دوره 10  شماره 

صفحات  -

تاریخ انتشار 1997