Extending capacity planning by positive lead times and optional overtime, earliness and tardiness for effective master production scheduling

Abstract

In this paper we consider the problem of improving the Master Production Schedule (MPS) in make-to-order production systems when demand exceeds available resource capacity. Due to the complexity of the problem, in practice solutions are usually obtained manually. We propose an algorithm that offsets production orders guided by tardiness, earliness and overtime penalties. The intermediate tool used to determine resource utilization is Rough Cut Capacity Planning (RCCP) extended by positive lead times and options for overtime, earliness and tardiness. This approach leads to a more realistic resource loading calculation, similar to CRP but without its computational burden. The discrete optimization model is solved by a Genetic Algorithm (GA); within the GA, delays or early deliveries of each order are represented as genes of a chromosome. The method is tested against systematically developed benchmark problems and real industrial data. Improvements over the traditional RCCP procedure and an ERP's embedded routines are demonstrated by the computational results and support the applicability of the proposed approach for real-life make-to-order environments.

Keywords:

• Manufacturing management
• ERP
• Genetic algorithms
• Master production scheduling
• Capacity planning

Acknowledgements

The authors would like to thank the anonymous referees for their constructive comments and contribution to the completion of this work.