Title :
Backtracking Ant Colony Algorithm for the 0ߝ1 Knapsack Problem
Author :
Jianqiang, Song ; Liang, Ma
Author_Institution :
Business school, University of Shanghai for Science and Technology, China
Abstract :
The 0ߝ1 Knapsack Problem is of a class of typical combinational optimization problems and is NP-hard. It has important practical significance to study it. Based on the characteristics of the 0ߝ1 Knapsack Problem, we design a binary coding directed graph which makes the Ant Colony algorithm suitable for the Knapsack Problem. In addition, we also adopt the concept of backtracking from the Nested Partition(NP) algorithm and apply it to the Ant Colony Optimization(ACO) for strengthening the Ant Colony algorithm of local search ability to solve the 0ߝ1 Knapsack Problem. Numerical tests on typical instances show the efficiency and advantage of the algorithm.
Keywords :
Algorithm design and analysis; Ant colony optimization; Business; Educational institutions; Evolutionary computation; Optimization; Partitioning algorithms; 0ߝ1 knapsack problem; ant colony optimization; backtracking ant colony optimization; nested partitions algorithm;
Conference_Titel :
Information Science and Engineering (ICISE), 2010 2nd International Conference on
Conference_Location :
Hangzhou, China
Print_ISBN :
978-1-4244-7616-9
DOI :
10.1109/ICISE.2010.5691518
