Genetic algorithms + data structures = evolution programs (3rd ed.)
Genetic algorithms + data structures = evolution programs (3rd ed.)
Min-transitivity of fuzzy leftness relationship and its application to decision making
Fuzzy Sets and Systems
Multisection in Interval Branch-and-Bound Methods for Global Optimization – I. Theoretical Results
Journal of Global Optimization
Multisection in Interval Branch-and-Bound Methods for Global Optimization II. Numerical Tests
Journal of Global Optimization
Journal of Global Optimization
Ordering of Intervals and Optimization Problems with Interval Parameters
Cybernetics and Systems Analysis
Methods and Applications of Interval Analysis (SIAM Studies in Applied and Numerical Mathematics) (Siam Studies in Applied Mathematics, 2.)
Two-objective method for crisp and fuzzy interval comparison in optimization
Computers and Operations Research
Hybrid Taguchi-genetic algorithm for global numerical optimization
IEEE Transactions on Evolutionary Computation
Genetic algorithm based multi-objective reliability optimization in interval environment
Computers and Industrial Engineering
Journal of Mathematical Modelling and Algorithms
Hi-index | 7.29 |
This paper deals with two different optimization techniques to solve the bound-constrained nonlinear optimization problems based on division criteria of a prescribed search region, finite interval arithmetic and interval ranking in the context of a decision maker's point of view. In the proposed techniques, two different division criteria are introduced where the accepted region is divided into several distinct subregions and in each subregion, the objective function is computed in the form of an interval using interval arithmetic and the subregion containing the best objective value is found by interval ranking. The process is continued until the interval width for each variable in the accepted subregion is negligible. In this way, the global optimal or close to global optimal values of decision variables and the objective function can easily be obtained in the form of an interval with negligible widths. Both the techniques are applied on several benchmark functions and are compared with the existing analytical and heuristic methods.