Fitness-Based Acceleration Coefficients Binary Particle Swarm Optimization (FACBPSO) to Solve the Discounted Knapsack Problem

The discounted {0-1} knapsack problem (D{0-1}KP) is a multi-constrained optimization and an extended form of the 0-1 problem. DKP composed set item batches where each batch has three items objective to maximize profit by selecting at most one from batch. Therefore, D{0-1}KP complex found many applications in real economic problems other areas concept promotional discounts exists. As belongs binary class problem, so novel particle swarm variant with modifications proposed this paper. acceleration coefficients are important parameters algorithm that keep balance between exploration exploitation. In conventional (BPSO), remain same iteration, whereas variant, fitness-based coefficient (FACBPSO), values based on fitness particle. This modification enforces least fit particles move fast best accordingly, which accelerates convergence speed reduces computing time. Experiments were conducted four instances having 10 datasets instance results FACBPSO compared BPSO new exact using greedy repair strategy. demonstrate outperforms PSO-GRDKP solving D{0-1}KP, improved feasible solution