since lean concept has appeared many works have been done on decreasing or even eliminating of wastes such as extra inventory. although these studies have not taken into account expected availability seriously. so in this paper, a multiple objective decision making (modm) model has been developed by viewpoint of these subjects. they are decreasing wastes and increasing system availability. wast...

data envelopment analysis (dea) is a nonparametric approach to estimate relative efficiency of decision making units (dmus). dea and is one of the best quantitative approach and balanced scorecard (bsc) is one of the best qualitative method to measure efficiency of an organization. since simultaneous evaluation of network performance of the quad areas of bsc model is considered as a necessity a...

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...

Many real-world tasks require making decisions that involve multiple possibly conflicting objectives. To succeed in such tasks, intelligent systems need planning or learning algorithms that can e ciently find di↵erent ways of balancing the trade-o↵s that such objectives present. In this tutorial, we provide an introduction to decision-theoretic approaches to coping with multiple objectives. We ...

supplier selection is one of the most important activities of purchasing departments. this importance is increased even more by new strategies in a supply chain, because of the key role suppliers perform in terms of quality, costs and services which affect the outcome in the buyer’s company. supplier selection is a multiple criteria decision making problem in which the objectives are not equall...

in a robust parameter design (rpd) problem, the experimenter is interested to determine the values of con-trol factors such that responses will be robust or insensitive to variability of the noise factors. response sur-face methodology (rsm) is one of the effective methods that can be employed for this purpose. since quality of products or processes is usually evaluated through several quality ...