Applied mathematical programming for production and engineering management
Applied mathematical programming for production and engineering management
More test examples for nonlinear programming codes
More test examples for nonlinear programming codes
Global optimization algorithms for a cad workstation
Journal of Optimization Theory and Applications
Integer and combinatorial optimization
Integer and combinatorial optimization
Journal of Optimization Theory and Applications
A collection of test problems for constrained global optimization algorithms
A collection of test problems for constrained global optimization algorithms
Randomized algorithms
Discrete Filled Function Method for Discrete Global Optimization
Computational Optimization and Applications
Discrete global descent method for discrete global optimization and nonlinear integer programming
Journal of Global Optimization
A discrete dynamic convexized method for nonlinear integer programming
Journal of Computational and Applied Mathematics
Discrete dynamic convexized method for nonlinearly constrained nonlinear integer programming
Computers and Operations Research
Quantum mechanics inspired Particle Swarm Optimisation for global optimisation
International Journal of Artificial Intelligence and Soft Computing
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In this paper, a computational algorithm, named RST2ANU algorithm, has been developed for solving integer and mixed integer global optimization problems. This algorithm, which primarily is based on the original controlled random search approach of Price [22i], incorporates a simulated annealing type acceptance criterion in its working so that not only downhill moves but also occasional uphill moves can be accepted. In its working it employs a special truncation procedure which not only ensures that the integer restrictions imposed on the decision variables are satisfied, but also creates greater possibilities for the search leading to a global optimal solution. The reliability and efficiency of the proposed RST2ANU algorithm has been demonstrated on thirty integer and mixed integer optimization problems taken from the literature. The performance of the algorithm has been compared with the performance of the corresponding purely controlled random search based algorithm as well as the standard simulated annealing algorithm. The performance of the method on mathematical models of three realistic problems has also been demonstrated.