Mutual benefits of two multicriteria analysis methodologies: A case study for batch plant design

This paper presents a MultiObjective Genetic Algorithm (MOGA) optimization framework for batch plant design. For this purpose, two approaches are implemented and compared with respect to three criteria, i.e., investment cost, equipment number and a flexibility indicator based on work in process (the so-called WIP) computed by use of a discrete-event simulation model. The first approach involves a genetic algorithm in order to generate acceptable solutions, from which the best ones are chosen by using a Pareto Sort algorithm. The second approach combines the previous Genetic Algorithm with a multicriteria analysis methodology, i.e., the Electre method in order to find the best solutions. The performances of the two procedures are studied for a large-size problem and a comparison between the procedures is then made

Observing the observers – uncovering the role of values in research assessments of organic food systems

Assessing the overall effects of organic food systems is important, but also a challenge because organic food systems cannot be fully assessed from one single research perspective. The aim of the article is to uncover the role of values in assessments of organic food systems as a basis for discussing the implications of combining multiple perspectives in overall sustainability assessments of the food system. We explore how values are embedded in five research perspectives assessing organic food systems, 1) Food Science, 2) Discourse Analysis, 3) Phenomenology, 4) Neoclassical Welfare Economics and 5) Actor-Network Theory. The article shows that value has various meanings in different scientific perspectives, and that a strategy for including and balancing different forms of knowledge in overall assessments of the effects of food systems is needed. Based on the analysis, we propose five ecommendations: 1) Elucidate values as a necessary foundation for research assessment across perspectives. 2 The choice of perspective is decisive and should be openly discussed 3) Formulate common goals which can be translated into the different perspectives and 4) Consider assessment of food system sustainability a learning process and design it as such

Aggregation procedure based on majority principle for collective identification of firm’s crucial knowledge

It is very important to identify, preserve, and transfer knowledge to those who need it within firm. However, the identification of knowledge and especially tacit knowledge is a complex process because knowledge cannot be measured quantitatively. In this paper we present an approach for inducing a set of collective decision rules representing a generalized description of the preferential information of a group of decision makers involved in a multicriteria classification problem to identify crucial knowledge to be capitalized

Multi crteria decision making and its applications : a literature review

This paper presents current techniques used in Multi Criteria Decision Making (MCDM) and their applications. Two basic approaches for MCDM, namely Artificial Intelligence MCDM (AIMCDM) and Classical MCDM (CMCDM) are discussed and investigated. Recent articles from international journals related to MCDM are collected and analyzed to find which approach is more common than the other in MCDM. Also, which area these techniques are applied to. Those articles are appearing in journals for the year 2008 only. This paper provides evidence that currently, both AIMCDM and CMCDM are equally common in MCDM