Paper Info
Title
A new grouping genetic algorithm for the quadratic multiple knapsack problem
Abstract
The quadratic multiple knapsack problem is an extension of the well known 0/1 multiple knapsack problem. In the quadratic multiple knapsack problem, profit values are associated not only with individual objects but also with pairs of objects. Profit value associated with a pair of objects is added to the overall profit if both objects of the pair belong to the same knapsack. Being an extension of the 0/1 multiple knapsack problem, this problem is also NP-Hard. In this paper, we have proposed a new steady-state grouping genetic algorithm for the quadratic multiple knapsack problem and compared our results with two recently proposed methods - a genetic algorithm and a stochastic hill climber. The results show the effectiveness of our approach.
Year
DOI
Venue
2007
10.1007/978-3-540-71615-0_19
EvoCOP
Keywords
Field
DocType
individual object,new grouping genetic algorithm,overall profit,genetic algorithm,stochastic hill climber,profit value,new steady-state,multiple knapsack problem,quadratic multiple knapsack problem,profitability,steady state,combinatorial optimization,knapsack problem
Mathematical optimization,Change-making problem,Generalized assignment problem,Combinatorial optimization,Continuous knapsack problem,Cutting stock problem,Knapsack problem,Polynomial-time approximation scheme,Mathematics,Genetic algorithm
Conference
Volume
ISSN
Citations 
4446
0302-9743
12
PageRank 
References 
Authors
0.73
7
2
Name
Order
Citations
PageRank
Alok Singh120117.15
Anurag Singh Baghel2484.11