Artificial Bee Colony for Quadratic Assignment Problem: A Hospital Case Study

The problem of locating hospital departments so as to minimize the total distance travelled by patients can be formulated as a Quadratic Assignment Problem (QAP).In general, (QAP) is one of the Combinatorial Optimization Problems and always high dimensional. Therefore, the use of meta-heuristics that generates good solutions in reasonable computer time becomes an attractive alternative. In this paper, a proposed artificial bee colony (ABC) algorithm is used to optimize QAP. The main idea is to use different crossover techniques for employee and onlooker bee stages and use exchange position operator for scout bee stage. The results of ABC algorithm show the efficiency and capabilities of proposed algorithm in finding the optimum solutions, compared with results of GA and SA in all test problems. The purpose of this paper is to apply the QAP in Azadi hospital in Kirkuk city to minimize the total distance travelled by patients. The application involves determine the flow matrix and the distance matrix to solve the problem. The results related that QAP model was presented suitable framework for clinics allocation and optimum use.

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Automated Parameter Tuning Framework for Heterogeneous and Large Instances: Case Study in Quadratic Assignment Problem

Lecture Notes in Computer Science - Learning and Intelligent Optimization ◽

10.1007/978-3-642-44973-4_45 ◽

2013 ◽

pp. 423-437 ◽

Cited By ~ 2

Author(s):

Lindawati ◽

Zhi Yuan ◽

Hoong Chuin Lau ◽

Feida Zhu

Keyword(s):

Assignment Problem ◽

Quadratic Assignment Problem ◽

Parameter Tuning ◽

Quadratic Assignment

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AUTOMATIC VERIFICATION OF OPTIMIZATION ALGORITHMS: A CASE STUDY OF A QUADRATIC ASSIGNMENT PROBLEM SOLVER

International Journal of Software Engineering and Knowledge Engineering ◽

10.1142/s021819401100527x ◽

2011 ◽

Vol 21 (02) ◽

pp. 289-307 ◽

Cited By ~ 3

Author(s):

ROBERT MERKEL ◽

DAOMING WANG ◽

HUIMIN LIN ◽

TSONG YUEH CHEN

Keyword(s):

Assignment Problem ◽

Optimization Problem ◽

Quadratic Assignment Problem ◽

Relative Effectiveness ◽

Mathematical Optimization ◽

Quadratic Assignment ◽

Problem Solver ◽

Metamorphic Testing ◽

Single Relation

Metamorphic testing is a technique for the verification of software output without a complete testing oracle. Mathematical optimization, implemented in software, is a problem for which verification can often be challenging. In this paper, we apply metamorphic testing to one such optimization problem, the quadratic assignment problem (QAP). From simple observations of the properties of the QAP, we describe how to derive a number of metamorphic relations useful for verifying the correctness of a QAP solver. We then compare the effectiveness of these metamorphic relations, in "killing" mutant versions of an exact QAP solver, to a simulated oracle. We show that metamorphic testing can be as effective as the simulated oracle for killing mutants. We examine the relative effectiveness of different metamorphic relations, both singly and in combination, and conclude that combining metamorphic relations can be significantly more effective than using a single relation.

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