13 October 1998 Evolutionary algorithms, simulated annealing, and Tabu search: a comparative study
Author Affiliations +
Evolutionary algorithms, simulated annealing (SA), and Tabu Search (TS) are general iterative algorithms for combinatorial optimization. The term evolutionary algorithm is used to refer to any probabilistic algorithm whose 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 from initial solution(s) until stopping criteria are met, (3) the progress of the cost of the best solution as a function of time, and (4) the number of solutions found at successive intervals of the cost function. The benchmark problem was is the floorplanning of very large scale integrated circuits. This is a hard multi-criteria optimization problem. Fuzzy logic is used to combine all objective criteria into a single fuzzy evaluation function, which is then used to rate competing solutions.
© (1998) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Habib Youssef, Habib Youssef, Sadiq M. Sait, Sadiq M. Sait, Hakim Adiche, Hakim Adiche, } "Evolutionary algorithms, simulated annealing, and Tabu search: a comparative study", Proc. SPIE 3455, Applications and Science of Neural Networks, Fuzzy Systems, and Evolutionary Computation, (13 October 1998); doi: 10.1117/12.326701; https://doi.org/10.1117/12.326701


Theoretical developments in evolutionary computation
Proceedings of SPIE (October 31 1999)
Revisiting evolutionary programming
Proceedings of SPIE (March 24 1998)
Step towards optimal topology of communication networks
Proceedings of SPIE (July 31 1991)
A new hybrid genetic algorithm and its application in the...
Proceedings of SPIE (January 13 2012)
Ameliorated GA approach for base station planning
Proceedings of SPIE (September 30 2011)

Back to Top