郑州大学学报（理学版）2025，Vol.57Issue(4)：71-79,9.DOI:10.13705/j.issn.1671-6841.2023260
最小冲突启发式辅助离散的海洋捕食者求解RB模型
Minimum Conflict Heuristic Assisted Discrete Ocean Predator Solving RB Model
摘要
Abstract
The revised B(RB)model was a stochastic instance model that possessed an exact phase-change growth domain in constraint-satisfiable problems.A solution algorithm was proposed for solving RB model instances,based on a combination of meta-heuristics and local search.Utilizing the marine predator algorithm,the initial solution space was discretized by real coding,and the three core phases of the marine predator algorithm were optimized.The current candidate solutions were targeted to guide the search towards the optimal solution.In the final stage,with the assistance of the local search method,the current optimal solution was passed to the minimum-conflict heuristic of the annealing strategy when the resulting optimal solution failed to satisfy the solution of the RB model instances,further enhancing the algorithm's solving efficiency.Experimentally,the algorithm was shown to be significantly more accurate and time-efficient than many other heuristic algorithms.It demonstrated the potential of high probability solution even when it was close to the satisfiability phase transition point.关键词
RB模型/约束可满足问题/海洋捕食者算法/元启发式/最小冲突启发式Key words
RB model/constraint satisfiability problem/marine predators algorithm/meta heuristic/minimum conflict heuristic分类
计算机与自动化引用本文复制引用
杨易,王晓峰,华盈盈,杨澜,庞立超..最小冲突启发式辅助离散的海洋捕食者求解RB模型[J].郑州大学学报（理学版）,2025,57(4):71-79,9.基金项目
国家自然科学基金项目(62062001) （62062001）
宁夏青年拔尖人才项目(2021) （2021）
北方民族大学研究生创新项目(YCX23145) （YCX23145）
