Semi-obnoxious single facility location in Euclidean space
Computers and Operations Research
A hybrid grouping genetic algorithm for reviewer group construction problem
Expert Systems with Applications: An International Journal
Mathematical and Computer Modelling: An International Journal
Theory and Analysis of Company-Sponsored Value Co-Creation
Journal of Management Information Systems
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
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This paper proposes a new framework for the solution of interactive multiobjective group decision-making problems with interval parameters. Its novelty stems from a learning phase where decision makers (DMs) explore the structural characteristics of the specific Multiple Criteria Decision Making (MCDM) problem. This provides important and timely feedback to the DMs. Its core consists of four indices and their relationships.The solution framework consists of three stages. In the first, each DM provides the limits of variation for each problem parameter. These are subsequently combined into a unique interval of variation. Then, the stochastic multiobjective problem is transformed into a deterministic one. In the second stage, DMs use the four MCDM characteristics to familiarize themselves with the problem before expressing their preferences for nondominated solutions. The DMs are then guided through an interactive procedure to find their best nondominated solutions. In the last stage, all best nondominated solutions provided by the DMs are combined using a twofold approach to find the best-compromise nondominated solution. This final choice represents the opinion of the group of DMs. Our results show that the learning phase is beneficial to DMs in judging the quality of solutions, leading to better informed decisions.