In the present study, a modified variant of Differential Evolution (DE) algorithm for solving multi-objective optimization problems is presented. The proposed algorithm, named Multi-Objective Differential Evolution Algorithm (MODEA) utilizes the advantages of Opposition-Based Learning for...

We propose a one-norm support vector machine (SVM) formulation as an alternative to the well-known formulation that uses parameter C in order to balance the two inherent objective functions of the problem. Our formulation is motivated by the ϵ-constraint approach that is used in bicriteria...

This work deals with the concept of satisfactory solution for Stochastic Multiobjective Programming (SMP) problems. Based on previous literature, we will introduce different concepts of satisfactory solutions for SMP problems, define a new concept of solution (where the decision maker (DM) sets...

Network reliability is a performance indicator of computer/communication networks to measure the quality level. However, it is costly to improve or maximize network reliability. This study attempts to maximize network reliability with minimal cost by finding the optimal transmission line...

We present an approach to interactive Multiple Criteria Decision Making based on preference driven Evolutionary Multiobjective Optimization with controllable accuracy.

This paper proposes an efficient, stage-wise optimisation model for scheduling part-time staff. During stage 1, the problem is formulated as a totally unimodular integer linear programme (ILP) that produces integer solution upon solving its LP relaxation. The model produces optimum work shifts...

Surface mining, often adopted for exploiting natural resources all over the world, is a major subject of debate as it causes major environmental impacts. It not only adversely alters the landscape but it also seriously hampers the traditional living conditions of numerous inhabitants, who may be...

In this paper we develop a general approach to generate all non-dominated solutions of the multi-objective integer programming (MOIP) Problem. Our approach, which is based on the identification of objective efficiency ranges, is an improvement over classical [epsilon]-constraint method....

We compare two different models for multicriterion routing in stochastic time-dependent networks: the classic "time-adaptive'' route choice and the more flexible "history-adaptive'' route choice. We point out some interesting properties of the sets of efficient solutions ("strategies'') found...