Effective Methods for Constraint Handling in Quantum Inspired Evolutionary Algorithm for Multi-Dimensional 0–1 Knapsack Problem

In this paper, we study an evolutionary algorithm inspired by quantum computing, called a Quantum Inspired Evolutionary Algorithm (QIEA) for the solution of Multidimensional 0-1 Knapsack problem (MDKP). During the process of evolution in QIEAs, a repair algorithm is used to modify infeasible solutions produced in each generation in order to make them feasible. The choice of repair strategy impacts the performance of QIEAs to a large extent. Several repair algorithms have been proposed and tested for an effective solution of large problem instances. To demonstrate the effectiveness and applicability, we have tested the algorithms on several popular benchmark instances.