A Simulation-Based Optimization Model for Determining the Sequence of Implementing Projects Related To New Product Development

Effective management of projects in research and development centers is one of the key objectives of these centers. Determining the optimal sequence of jobs affect the group productivity, earliness, and tardiness costs. One of the deterministic variants of the problem solving is well-known to be NP-Hard. If random elements are introduced into the problem, the level of complexity becomes higher. Hence, many priority rules have been developed to tackle stochastic job shop scheduling problem. However, to devise a better solution approach, simulation- optimization approach might be used. In this study, a mathematical model is developed for project scheduling with random process times and possible machine breakdowns. Then, a simulation-optimization model is designed to choose among a list of priority rules using Rockwell Arena 14. Finally, a numerical example was used to evaluate the quality of the model. Results show that the rule Longest Processing Time (LPT) yields the lowest total earliness and tardiness costs.