Price and due date quoting for a mass customization company

Abstract

Mass customization is a competitive strategy based on offering a wide variety of options without greatly increasing production costs. Some associated challenges are the management of components inventory and job scheduling. Three unique scheduling mixed integer programming models with sequence dependent setups are proposed for different production scenarios. They allow quoting different sale prices depending on what due date is acceptable to the customer. Three solutions methods were employed, one is a mixed integer programming formulation with the Gurobi optimizer solver, which guarantees to find the optimal solution, but is restricted to the problem size. The others are a simulated annealing and an ant colony heuristic, which does not guarantee to find the optimal answer, but is not restricted by the size of the problem. Both heuristics probe to bring statistically similar results. Each solution method was successfully validated on a real-world mass customization firm. Due date variation analysis showed a high correlation between due date and cost. Model can be meaningfully used since long lead time can be a major cause for market share loss.