MARS - A MULTISTART ADAPTIVE RANDOM SEARCH METHOD FOR GLOBAL CONSTRAINED OPTIMIZATION IN ENGINEERING APPLICATIONS
- 1 February 1998
- journal article
- research article
- Published by Informa UK Limited in Engineering Optimization
- Vol. 30 (2), 125-154
- https://doi.org/10.1080/03052159808941241
Abstract
A multistart, step-controlled random search algorithm for global, constrained optimization is proposed. The method is found to be very efficient for solving a variety of constrained nonlinear optimization problems. The performance of the method and its comparison with another stochastic search algorithm, simulating annealing, are demonstrated through a number of standard test problems involving multimodal objective functions with continuous and mixed-discrete variables. The applications of the method to a number of practical engineering optimization cases in the field of turbine design and compact heat exchangers are discussed.Keywords
This publication has 14 references indexed in Scilit:
- DISCRETE AND CONTINUOUS VARIABLE STRUCTURAL OPTIMIZATION USING TABU SEARCHEngineering Optimization, 1995
- GENETIC ALGORITHMS FOR NONLINEAR MIXED DISCRETE-INTEGER OPTIMIZATION PROBLEMS VIA META-GENETIC PARAMETER OPTIMIZATIONEngineering Optimization, 1995
- ON MIXED-DISCRETE NONLINEAR OPTIMIZATION PROBLEMS: A COMPARATIVE STUDYEngineering Optimization, 1995
- MIXED-DISCRETE NONLINEAR OPTIMIZATION WITH SIMULATED ANNEALINGEngineering Optimization, 1993
- Tabu search method with random moves for globally optimal designInternational Journal for Numerical Methods in Engineering, 1992
- Computational Experience with Generalized Simulated Annealing Over Continuous VariablesAmerican Journal of Mathematical and Management Sciences, 1988
- Stochastic global optimization methods part I: Clustering methodsMathematical Programming, 1987
- Stochastic Methods for Global OptimizationAmerican Journal of Mathematical and Management Sciences, 1984
- Optimization by Simulated AnnealingScience, 1983
- Simulation and the Monte Carlo MethodWiley Series in Probability and Statistics, 1981