IEEE

Runtime Analysis of Evolutionary Algorithms for Multi-Party Multi-Objective Optimization

Abstract: In scenarios where multiple decision-makers operate within a common decision space, each focusing on their own multi-objective optimization problem (e.g., bargaining games), the problem can ...
Scientific Research Publishing

Deb, K. (2011) Multi-Objective Optimisation Using Evolutionary Algorithms: An Introduction. In: Wang, L.H., Ng, A.H.C. and Deb, K., Eds., Multi-Objective Evolutionary ...

ABSTRACT: Multi-objective optimization remains a significant and realistic problem in engineering. A trade-off among conflicting objectives subject to equality and inequality constraints is known as ...
Frontiers

CLMOAS: collaborative large-scale multi-objective optimization algorithms with adaptive strategies

In the field of multi-objective evolutionary optimization, prior studies have largely concentrated on the scalability of objective functions, with relatively less emphasis on the scalability of ...
IEEE

MORA-LLM: Enhancing Multi-Objective Optimization Recommendation Algorithm by Integrating Large Language Models

Abstract: Multi-objective evolutionary algorithms (MOEAs) have achieved notable success in recommendation systems (RSs) by meeting diverse user needs. However, existing MOEAs lack effective methods to ...
Scientific Research Publishing

A Review of Intelligent Optimization Algorithms in Supply Chain Networks ()

1 School of Mathematics and Statistics, Sichuan University of Science and Engineering, Zigong, China. 2 Institute of Computational Mathematics and Scientific/Engineering Computing, Chinese Academy of ...