Over the past few decades, decision making has gained popularity in the area of operations research (OR) due to its frequent implications in managerial domains as it enables decision makers to come up with preeminent decisions. Multiple-criteria decision making (MCDM) – a well-known decision making process – is based on the progress in introducing the methods and procedures of multiple conflicting criteria into management planning processes. MCDM is widely used by a large number of decision makers in a variety of fields, such as economics, financial analysis, flood risk management, housing evaluation, disaster management and customer relationship management.
Although MCDM has many diversified advantages, this highly useful decision-making methodology still contains certain unresolved issues. Decision making – either under multiple criteria or under risk – Is always burdened with uncertainty.
In their seminal work, Bellman and Zadeh distinguished between statistical randomness and fuzziness by asserting that the former has to do with uncertainty regarding membership or non-membership of an object to a set. In statistical analysis an object belongs to a set either perfectly or not at all. Fuzziness, however, relates to sets where grades, ranging from full membership to full non-membership, are possible. In analysis, it is of concern whether the object belongs strongly, moderately or weakly to a set. However, it is possible to combine both types of uncertainty; in decision models under risk, individual states of the world can be modelled through fuzzy sets and at the same time the probabilities of the states of the world can be fuzzy.
Uncertainty implies that there are specific, although unknown, outcomes or sets of outcomes associated with each action that the decision maker(s) can take. This concept of uncertainty assumes that a stochastic process underlies the connection between the actions and outcomes. Although this stochastic process may not be completely known to the decision maker, there is no question that it does exist uniquely. Fuzziness, on the other hand, is qualitatively different. Fuzziness stems more from the concept of imprecision stemming from the decision maker not being able to clearly distinguish between groups of possible outcomes. This difficulty is more consistent with the real-world situation presented by multiple-attribute, multiple-objective decision problems.
Decision making, one of the most crucial and omnipresent human activities in the real world, is characterised as a process of choosing the best alternative(s) or course(s) of action, from a set of alternatives, to attain a goal (or goals). It becomes a much more complex task when more criteria, more decision makers or different states of the world need to be taken into account. Classic mathematics provides various tools for multiple-criteria and group decision making and decision making under risk. Fuzzification of these methods is possible and desirable, because the models based on these fuzzified methods better capture the modelled reality. In this special issue we aim to map the state of the art in this area and showcase successful applications and promising new methods in mathematical decision support.
This special issue invites submission focusing on mathematical methods in multiple criteria decision making, group decision making and decision making under risk, and their applications to real life problems. Decision making is always based on evaluation; the multiple criteria evaluation itself can be the desired goal in many situations. Papers dealing with evaluation models are therefore also invited. Theoretical and practically oriented papers contributing to the field of evaluation and decision making are welcome, including papers on novel software implementations of these methods. Contributions from the broad field of operations research with an overlap to evaluation and decision making theory and applications are also invited.
Suitable topics include, but are not limited to, the following:
- Decision making theory
- Multiple criteria evaluation and decision making
- Decision making under risk and uncertainty
- Fuzzy methods of decision making
- Decision support systems
- Real world applications of evaluation and decision making models
Submission of manuscripts: 12 December, 2014
Notification to authors: 27 March, 2015
Final versions due: 29 May, 2015