The process of multiple criteria decision making (MCDM) is of determining the best choice among all of the probable alternatives. The problem of supplier selection on which decision maker has usually vague and imprecise knowledge is a typical example of multi criteria group decision-making problem. The conventional crisp techniques has not much effective for solving MCDM problems because of imp...

The purpose of this paper is to present an alternative of a hybrid method based on Saaty’s Analytical Hierarchy Process and on the Technique for Order Preference by using the Similarity to Ideal Solution method (AHP-TOPSIS) and, based on the AHP and its use of pairwise comparisons, to extend it to a new method called α-D MCDMTOPSIS (α-Discounting Method for multi-criteria decision making-TOPSIS...

In modern business world group decision-making is becoming an extremely important activity. Recent research on computerized group decision support has focused extensively on supporting people co-located in place and time. There is a need, however, for more research focused on asynchronous group decision support systems (GDSS). Multicriteria decision-making (MCDM) theory has produced a wide rang...

Abstract This paper presents an efficient cooperative multi-populations swarm intelligence algorithm based on the Harris Hawks optimization (HHO) algorithm, named CMPMO-HHO, to solve multi-/many-objective problems. Specifically, this firstly proposes a novel framework with dual elite selection CMPMO/des. With four excellent strategies, namely one-to-one correspondence between objectives and sub...

Abstract Single-objective continuous optimization can be challenging, especially when dealing with multimodal problems. This work sheds light on the effects that multi-objective may have in single-objective space. For this purpose, we examine inner mechanisms of recently developed sophisticated local search procedure SOMOGSA. method solves problems based first expanding problem an additional ob...

Objectives . A frequently used method for obtaining Pareto-optimal solutions is to minimize a selected quality index under restrictions of the other indices, whose values are thus preset. For scalar objective function, global minimum sought that contains restricted indices as penalty terms. However, landscape such function has steep-ascent areas, which significantly complicate search minimum. T...

Many-objective optimization problems (MaOPs) are challenging in scientific research. Research has tended to focus on algorithms rather than algorithm frameworks. In this paper, we introduce a projection-based evolutionary algorithm, MOEA/PII. Applying the idea of dimension reduction and decomposition, it divides objective space into projection plane free dimension(s). The balance between conver...

Multi-modal multi-objective optimization problems (MMMOPs) have multiple subsets within the Pareto-optimal Set, each independently mapping to same Pareto-Front. Prevalent evolutionary algorithms are not purely designed search for solution subsets, whereas, MMMOPs demonstrate degraded performance in objective space. This motivates design of better addressing MMMOPs. The present work identifies c...

The first steps of multi-criteria decision making (MCDM) are typically the decomposition and structuring of the decision problem at hand. As all subsequent process steps of MCDM are based on the initial structuring of the decision problem, the validity of the structure representing the decision problem is of particular importance for the quality of the decision making process. This paper seeks ...