Multiple-class multidimensional knapsack optimisation problem and its solution approaches
作者：
Highlights：
• We propose a novel multiple-class multidimensional knapsack optimisation problem.
• The optimisation objective of MCMKOP is to minimise the total cost of the chosen knapsacks.
• We prove that MCMKOP is a NP-hard problem.
• Three heuristic approaches, CPLEX and Gurobi are used to solve this problem.
• The hybrid simulated annealing genetic algorithm can obtain high-quality solutions.
摘要
•We propose a novel multiple-class multidimensional knapsack optimisation problem.•The optimisation objective of MCMKOP is to minimise the total cost of the chosen knapsacks.•We prove that MCMKOP is a NP-hard problem.•Three heuristic approaches, CPLEX and Gurobi are used to solve this problem.•The hybrid simulated annealing genetic algorithm can obtain high-quality solutions.
论文关键词：Combinatorial optimisation,Multiple-class multidimensional knapsack problem (MCMKOP),Genetic algorithm,Simulated annealing algorithm,Hybrid simulated annealing genetic algorithm (HSAGA)
论文评审过程：Received 3 March 2018, Revised 10 October 2018, Accepted 5 November 2018, Available online 3 December 2018, Version of Record 23 January 2019.
论文官网地址：https://doi.org/10.1016/j.knosys.2018.11.006
