An improved chemical reaction optimisation algorithm for the 0-1 knapsack problem

被引:2
|
作者
Salami, Hamza Onoruoiza [1 ]
Bala, Abubakar [2 ]
机构
[1] Univ Hafr al Batin, Coll Comp Sci & Engn, Hafar al Batin 31991, Saudi Arabia
[2] Univ Teknol PETRONAS, Dept Elect & Elect Engn, Seri Iskandar 32610, Perak, Malaysia
关键词
chemical reaction optimisation; CRO; knapsack problems; metaheuristic algorithms; MONARCH BUTTERFLY OPTIMIZATION; PARTICLE SWARM OPTIMIZATION; SEARCH ALGORITHM; BAT ALGORITHM;
D O I
10.1504/IJBIC.2022.124334
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Knapsack problems (KPs) are well studied NP-hard problems with numerous real-life applications like capital budgeting, cargo loading, load-shedding in microgrids, and resource allocation in cloud computing. Chemical reaction optimisation (CRO) is a recently developed metaheuristic algorithm that works based on the principles of chemical reactions. This paper proposes a CRO-based algorithm for solving the 0-1 knapsack problem (0-1 KP). The proposed algorithm (newCRO) utilises a novel, optimistic neighbourhood search operator and a greedy repair and optimisation operator to fix invalid solutions and improve feasible solutions. We test the newCRO on a wide range of large-scale 0-1 KP benchmark problems, and its results are compared with five other existing methods to show its superior optimisation capabilities.
引用
收藏
页码:253 / 266
页数:14
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