In this paper, we propose a procedure, based on statistical design of experiments and gradient descent, that finds effective settings for parameters found in heuristics. We develop our procedure using four experiments. We use our procedure and a small subset of problems to find parameter settings for two new vehicle routing heuristics. We then set the parameters of each heuristic and solve 19 capacity-constrained and 15 capacity-constrained and route-length-constrained vehicle routing problems ranging in size from 50 to 483 customers. We conclude that our procedure is an effective method that deserves serious consideration by both researchers and operations research practitioners.
ASJC Scopus subject areas
- Information Systems
- Computer Networks and Communications
- Control and Optimization
- Management Science and Operations Research
- Artificial Intelligence