Interactive multiobjective optimization: A review of the state-of-the-art
Interactive multiobjective optimization (IMO) aims at finding the most preferred solution of a
decision maker with the guidance of his/her preferences which are provided progressively …
decision maker with the guidance of his/her preferences which are provided progressively …
A mini-review on preference modeling and articulation in multi-objective optimization: current status and challenges
Evolutionary multi-objective optimization aims to provide a representative subset of the
Pareto front to decision makers. In practice, however, decision makers are usually interested …
Pareto front to decision makers. In practice, however, decision makers are usually interested …
MOEA/D-ACO: A multiobjective evolutionary algorithm using decomposition and antcolony
Combining ant colony optimization (ACO) and the multiobjective evolutionary algorithm (EA)
based on decomposition (MOEA/D), this paper proposes a multiobjective EA, ie, MOEA/D …
based on decomposition (MOEA/D), this paper proposes a multiobjective EA, ie, MOEA/D …
A new local search-based multiobjective optimization algorithm
In this paper, a new multiobjective optimization framework based on nondominated sorting
and local search (NSLS) is introduced. The NSLS is based on iterations. At each iteration …
and local search (NSLS) is introduced. The NSLS is based on iterations. At each iteration …
Knee-based decision making and visualization in many-objective optimization
As an essential component in multi-and many-objective optimization, decision-making
process either selects a subset of solutions from the whole Pareto front or guides the search …
process either selects a subset of solutions from the whole Pareto front or guides the search …
Assessing the performance of interactive multiobjective optimization methods: A survey
Interactive methods are useful decision-making tools for multiobjective optimization
problems, because they allow a decision-maker to provide her/his preference information …
problems, because they allow a decision-maker to provide her/his preference information …
Preference incorporation in evolutionary multiobjective optimization: A survey of the state-of-the-art
Abstract After using Evolutionary Algorithms (EAs) for solving multiobjective optimization
problems for more than two decades, the incorporation of the decision maker's (DM's) …
problems for more than two decades, the incorporation of the decision maker's (DM's) …
Maintenance applications of multi-criteria optimization: A review
CS Syan, G Ramsoobag - Reliability Engineering & System Safety, 2019 - Elsevier
Modern-day maintenance optimization decisions are complex problems which need to
satisfy multiple and conflicting criteria. With increased applications and recent advances in …
satisfy multiple and conflicting criteria. With increased applications and recent advances in …
Does preference always help? A holistic study on preference-based evolutionary multiobjective optimization using reference points
The ultimate goal of multiobjective optimization is to help a decision maker (DM) identify
solution (s) of interest (SOI) achieving satisfactory tradeoffs among multiple conflicting …
solution (s) of interest (SOI) achieving satisfactory tradeoffs among multiple conflicting …
A review of hybrid evolutionary multiple criteria decision making methods
For real-world problems, the task of decision-makers is to identify a solution that can satisfy a
set of performance criteria, which are often in conflict with each other. Multi-objective …
set of performance criteria, which are often in conflict with each other. Multi-objective …