A Constraint-Handling Technique for Genetic Algorithms using a Violation Factor
원문 초록
Over the years, several meta-heuristic algorithms were proposed and are now emerging as common methods for constrained optimization problems. Among them, genetic algorithms (GA's) shine as popular evolutionary algorithms (EA's) in engineering optimization. Most engineering design problems are difficult to resolve with conventional optimization algorithms because they are highly nonlinear and contain constraints. In order to handle these constraints, the most common technique is to apply penalty functions. The major drawback is that they require tuning of parameters, which can be very challenging. In this paper, we present a constraint-handling technique for GA's solely using the violation factor, called VCH (Violation Constraint-Handling) method. Several benchmark problems from the literature are examined. The VCH technique was able to provide a consistent performance and match results from other GA-based techniques.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Graph-Supported Dynamic Algorithm Configuration for Multi-Objective Combinatorial Optimization
Randomised Optimism via Competitive Co-Evolution for Matrix Games with Bandit Feedback
Benchmarking MOEAs for solving continuous multi-objective RL problems
Mergenetic: a Simple Evolutionary Model Merging Library
Evolutionary thoughts: integration of large language models and evolutionary algorithms
RainbowPlus: Enhancing Adversarial Prompt Generation via Evolutionary Quality-Diversity Search
토론
이 논문과 연결된 포럼 글이 아직 없습니다.