Developing intelligent interactive approach for multi-objective optimization problems / Alia Youssef Gebreel Mohamed ; Supervised Mohamed Sayed Ali Osman , Waiel Fathi Abdelwahed , Mahmoud Mostafa Elsherbiny

Thesis (Ph.D.) - Cairo University - Institute of Statistical Studies and Research - Department of Operations Research

This thesis aims to present some approaches for solving multiobjective optimization problems. Firstly, it proposes an intelligent interactive approach based on genetic algorithm, bacterial foraging optimization, harmony search, hybrid genetic-bacterial foraging-harmony algorithm, and/ or hybrid bacterial foraging-harmony algorithm. Basically, these algorithms are used when the gradient search of objectives becomes difficult. To find a preferred efficient solution based on the minimum distance from the utopia point, this study is used to capture and represent the decision maker{u2019}s preference at every step of the optimization process. The bacterial and harmony algorithms got the same solution but with different performances. The harmony search or/ and the hybrid proposed algorithms are simple and mathematically less complex than genetic algorithm. Also, this research used the parametric study for providing essential information about the problem's behavior to the decision maker.Two novel algorithms are presented in this work to find the complete stability set of the first kind for parametric multi- objective linear programming problems. The complexity of determining this set is depended on the structure nature of the parameters. In addition, it produced a new method for solving multi-objective convex programming problems that depends on the normal of objective vectors

Issued also as CD