Hybrid Algorithms for Multiple Objective Optimization Problems
MATLAB Approach
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This book consists of six chapters. Chapter (1) presents a computational view to generate ¿-Pareto optimal solutions for the fuzzy multiple objective optimization problems based on the ¿-Level sets method and the weighting method using MATLAB. The purpose of chapter (2) is to obtain non-dominated solutions for stochastic multiple objective optimization problems based on the chance constrained programming technique and the weighting approach using MATLAB. The purpose of chapter (3) is to generate numerical Pareto optimal solutions for fractional multiple objective optimization problems based ...
This book consists of six chapters. Chapter (1) presents a computational view to generate ¿-Pareto optimal solutions for the fuzzy multiple objective optimization problems based on the ¿-Level sets method and the weighting method using MATLAB. The purpose of chapter (2) is to obtain non-dominated solutions for stochastic multiple objective optimization problems based on the chance constrained programming technique and the weighting approach using MATLAB. The purpose of chapter (3) is to generate numerical Pareto optimal solutions for fractional multiple objective optimization problems based on the Charens - Cooper transformation method and the weighting method using MATLAB. Chapter (4) focuses on the solution of integer linear fractional multiple objective optimization problems of a special type, where such problems have block angular structure of the constraints. Chapter (5) is concerned with solving large scale linear fractional multiple objective optimization problems with chance-constraints. Chance-constraints involve random numbers in the right-hand sides. In chapter (6), I extend TOPSIS for solving Linear Fractional multiple objective Optimization problems.
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