In this paper a simulated annealing(SA)algorithm is presented for the 0/1 mul- tidimensional knapsack problem.Problem-specific knowledge is incorporated in the algorithm description and evaluation of parameters in ord...In this paper a simulated annealing(SA)algorithm is presented for the 0/1 mul- tidimensional knapsack problem.Problem-specific knowledge is incorporated in the algorithm description and evaluation of parameters in order to look into the perfor- mance of finite-time implementations of SA.Computational results show that SA per- forms much better than a genetic algorithm in terms of solution time,whilst having a modest loss of solution quality.展开更多
基金This work was supported by the National Natural Science Foundation of China （No. 10201026, 10672111）.
文摘In this paper a simulated annealing(SA)algorithm is presented for the 0/1 mul- tidimensional knapsack problem.Problem-specific knowledge is incorporated in the algorithm description and evaluation of parameters in order to look into the perfor- mance of finite-time implementations of SA.Computational results show that SA per- forms much better than a genetic algorithm in terms of solution time,whilst having a modest loss of solution quality.
