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Evolutionary algorithms, simulated annealing and tabu search: a comparative study

Youssef, H. and Sait, Sadiq M. and Adiche, Hakim Evolutionary algorithms, simulated annealing and tabu search: a comparative study. ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE 14 (2): 167-181 APR 2001.



Abstract Evolutionary algorithms, simulated annealing (SA), and tabu search (TS) are general iterative algorithms for combinatorial optimization. The termevolutionary algorithmis used to refer to any probabilistic algorithmwhose design is inspired by evolutionary mechanisms found in biological species. Most widely known algorithms of this category are genetic algorithms (GA). GA, SA, and TS have been found to be very effective and robust in solving numerous problems from a wide range of application domains. Furthermore, they are even suitable for ill-posed problems where some of the parameters are not known before hand. These properties are lacking in all traditional optimization techniques. In this paper we perform a comparative study among GA, SA, and TS. These algorithms have many similarities, but they also possess distinctive features, mainly in their strategies for searching the solution state space. The three heuristics are applied on the same optimization problem and compared with respect to (1) quality of the best solution identified by each heuristic, (2) progress of the search frominitial solution(s) until stopping criteria are met, (3) the progress of the cost of the best solution as a function of time (iteration count), and (4) the number of solutions found at successive intervals of the cost function. The benchmark problem used is the floorplanning of very large scale integrated (VLSI) circuits. This is a hard multi-criteria optimization problem. Fuzzy logic is used to combine all objective criteria into a single fuzzy evaluation (cost) function, which is then used to rate competing solutions. # 2001 Elsevier Science Ltd. All rights reserved. Keywords: Genetic algorithms; Simulated annealing; Tabu search; Fuzzy logic; Floorplanning; Combinatorial optimization; VLSI

Item Type:Article
Divisions:College Of Computer Sciences and Engineering > Computer Engineering Dept
Creators:Youssef, H. and Sait, Sadiq M. and Adiche, Hakim
Email:youssef@kfupm.edu.sa, sadiq@kfupm.edu.sa, UNSPECIFIED
ID Code:276
Deposited By:AbdulRahman
Deposited On:09 Mar 2008 16:26
Last Modified:12 Apr 2011 13:08

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