Um estudo algorítmico para a otimização de compra em grupo com múltiplos fornecedores e descontos em escala

Abstract

This work studies the optimization in the distribution of buyers in a group of suppliers, taking into consideration the necessities and preferences based on the product’s characteristics, group discounts available by the suppliers and the availability of the product on the suppliers’ stock. This study is composed of contextualization and formal definition of the problem, definition of the utilized algorithms and calculations, creation of instances, computational experiments, and analysis of results. The algorithms implemented and tested by computational experiments are the branch-and-bound, hill climbing, genetic algorithm, memetic algorithm, Variable Neighborhood Search (VNS), Greedy Randomized Adaptive Search (GRASP), and also algorithms, functions and heuristics created specifically for this problem.