Solving 0/1 knapsack problem using hybrid TLBO-GA algorithm

Abstract

The 0/1 knapsack problem is attempted to solve using various soft computing methods till date. This paper proposes hybrid TLBO-GA algorithm which is hybrid of teaching learning-based optimization (TLBO) algorithm with genetic algorithm (GA). The 0/1 knapsack problem is a combinatorial optimization problem. The 0/1 knapsack problem aims to maximize the benefit of objects in a knapsack without exceeding its capacity as a constraint. In the literature, it is found that TLBO works for real-coded or real-valued problems. Hybrid TLBO-GA combines evolutionary process of TLBO and binary chromosome representation of GA for solving the knapsack problem (KP). Hybrid TLBO-GA combines advantages of both TLBO and GA. Results are taken on random as well as standard date sets using hybrid TLBO-GA for 0/1 knapsack problem. Hybrid TLBO-GA results are compared with the results obtained using simple genetic algorithm (SGA) on the same data sets. The results obtained using hybrid TLBO-GA are found satisfactory.