With the deepening of uncertainty and fuzziness people’s understanding things, it becomes more convenient to use fuzzy decision making in evaluating schemes. These schemes not only include quantitative data but also consider evaluation information. In theory, Pythagorean set is extended, both which are less than or equal 1, increases scope application. This paper mainly studies selection green ...

In the field of evolutionary multiobjective optimization, the hypervolume indicator is the only single set quality measure that is known to be strictly monotonic with regard to Pareto dominance. This property is of high interest and relevance for multiobjective search involving a large number of objective functions. However, the high computational effort required for calculating the indicator v...

This paper proposes a modified particle swarm optimization considering time-varying acceleration coefficients for the economic-emission load dispatch (EELD) problem. The new adaptive parameter is introduced to update the particle movements through the modification of the velocity equation of the classical particle swarm optimization (PSO) algorithm. The idea is to enhance the performance and ro...

With construction of new large-scale water storage projects on the wane in the U.S. and other developed countries, attention must focus on improving the operational effectiveness and efficiency of existing reservoir systems for maximizing the beneficial uses of these projects. Optimal coordination of the many facets of reservoir systems requires the assistance of computer modeling tools to prov...

This article presents a broad overview of applications of Computational Intelligence (CI) paradigms in resource constrained project scheduling problems (RCPSP) including Fuzzy system (FS), Artificial Neural Networks (ANN), Particle Swarm Optimization (PSO), Tabu Search (TS), Genetic Algorithms (GA), Simulated Annealing (SA) and other metaheuristics techniques. Recent developments of computation...

This paper presents an evolutionary Multiobjective learning model achieving positive synergy between the Inference System and the Rule Base in order to obtain simpler and still accurate linguistic fuzzy models by learning fuzzy inference operators and applying rule selection. The Fuzzy Rule Based Systems obtained in this way, have a better trade-off between interpretability and accuracy in ling...

The purpose of the paper is to introduce a new type of fuzzy matrix games: fuzzy constrained matrix games. A computational method for its solution based on establishment of the auxiliary fuzzy linear programming for each player is proposed. The approach based on the multiobjective programming is established to solve these fuzzy linear programming. Effectiveness is illustrated with a numerical e...

Different constraint handling techniques have been used with multiobjective evolutionary algorithms (MOEA) to solve constrained multiobjective optimization problems. It is impossible for a single constraint handling technique to outperform all other constraint handling techniques always on every problem irrespective of the exhaustiveness of parameter tuning. To overcome this selection problem, ...

This paper presents a method to solve a linear or nonlinear Fuzzy Multiobjective Programming problem. We propose Genetic Search based approaches to the case in which fuzzy constraints are assumed.