Theory and Applications for Evolutionary Multi-Criteria Decision-Making
• 大类 : 工程技术 - 2区
• 小类 : 计算机：人工智能 - 2区
• 小类 : 计算机：理论方法 - 2区
Complex problems usually require the simultaneous consideration of multiple performance criteria within multidisciplinary environments. Since the middle of the 1990s, the population-based heuristic approaches have been widely used in the field of Evolutionary Multi-Criterion Optimization (EMO) toaddress such problems. This is evidenced by the rapidly growing number of research publications and by the availability of excessive related software tools. Recently, EMO researchers have understood the necessity to develop and integrate decision making into EMO, and the need for cross-fertilization between EMO and the Multiple Criteria Decision Making (MCDM) communities has become apparent.
The main aim of this special issue is to bring together both experts and new-comers to discuss new and existing issues in these areas, in particular, to continue the integration and blending of ideas between EMO and MCDMresearchers, and to stimulate engagement with the user community.
Full papers are invited on recent advances in the development and application of EMO approaches, new horizons for multi-criteria decision-making, which may be pathfinders for a step-change in multidisciplinary decision-making, or showcase developments in the MCDM communities that have potential for blending with EMO themes, or consider hybrid EMO-MCDM methods and applications. In addition, application papers in the area of hybrid renewable energy system optimal design and management are highly encouraged.
You are invited to submit papers that are unpublished original work for this special issue. The topics include, but are not limited to:
- Interactive Multi-objective Optimization
- Multiple Objective Continuous and Combinatorial Optimization
- Pareto optimal knee front search
- Evolutionary Many-objective Optimization
- Hybrid EMO-MCDM methodologies
- Multiple Attribute Utility Theory
- Theoretical aspects of EMO and MCDM methodologies
- Outranking Methods
- Multiple Criteria Decision Aiding
- Goal Programming
- Preference Modeling
- Multiple Objective Metaheuristics
- Multiple Criteria Choice, Ranking, and Sorting
- Fuzzy Multiple Criteria Decision Making
- Data-driven and model-based multu-objective optimization
- Dynamic Multi-objective Optimization
- Applications of EMO, MCDM in government, business, industry and interdisciplinary sciences.