A Variable Neighborhood Search Algorithm for Two-Dimensional Bin Packing Problem with Compatible Categories

Adding additional constraints in Bin Packing with Compatible Categories using Variable Neighborhood Search metaheuristic algorithm will solve more real-life size instances problem. This research study determined the best assignment of packing a distinct product in order to minimize the required number of bins. This method was performed by testing extensive computational experiments in different algorithms with a very large set of 2000 instances. The tested instances differ in terms of number of items, bin capacities, compatibility matrices and proportion of items that belong to the different categories, length, weight and width constraints. The researchers had chosen First Fit Category Decreasing for Bin Packing with Compatible Category, and Variable Neighborhood Search for Bin Packing with Compatible Category algorithms for comparative experiment of the result and an average of one (1) bin reduced was achieved. Therefore this indicates that a Variable Neighborhood Search algorithm for two-dimensional can effectively solve the problem of Bin Packing with Compatible Categories.