Multi-objectivization is a term used to describe strategies developed for optimizing single-objective problems by multi-objective algorithms. This paper focuses on multi-objectivizing the sum-of-the-parts combinatorial optimization problems, which include traveling salesman problem, unconstrained binary quadratic programming and other well-known problem. For we propose decompose its original ob...

We study the multi-armed bandit (MAB) problem where the agent receives a vectorial feedback that encodes many possibly competing objectives to be optimized. The goal of the agent is to find a policy, which can optimize these objectives simultaneously in a fair way. This multi-objective online optimization problem is formalized by using the Generalized Gini Index (GGI) aggregation function. We p...

The Generation expansion planning (GEP) problem is a large scale, mixed integer and the most complicated optimization problem. So we are using Multi-objective differential evolution (MODE) for solving the GEP problem. To calculate for best combinations of conventional sources with and without wind farm, GEP problem is considered for test system of and satisfy the constraints by calculating EENS...

the present paper aims to investigate the effects of modularity and the layout of subsystems and parts of a complex system on its maintainability. for this purpose, four objective functions have been considered simultaneously: i) maximizing the level of accordance between system design and optimum modularity design,ii) maximizing the level of accessibility and the maintenance space required,iii...

This paper considers a flowshop scheduling problem of a manufacturing cell that contains families of jobs whose setup times are dependent on the manufacturing ............ sequence of the families. Two objectives, namely the makespan and total flow time, have been considered simultaneously in this work. Since minimization of each of these two objectives is an NpHard problem, a Multi-Objective G...

Mathematical programming and artificial intelligence (AI) methods are known as the most effective and applicable procedures to form manufacturing cells in designing a cellular manufacturing system (CMS). In this paper, a bi-objective programming model is presented to consider the cell formation problem that is solved by a proposed multi-objective particle swarm optimization (MOPSO). The model c...

Most real world combinatorial optimization problems are difficult to solve with multiple objectives which have to be optimized simultaneously. Over the last few years, researches have been proposed several ant colony optimization algorithms to solve multiple objectives. The aim of this paper is to review the recently proposed multi-objective ant colony optimization (MOACO) algorithms and compar...