Project scheduling and equipment planning with random breakdowns.

Most of the research works conducted on Project Scheduling Problem (PSP) especially Resource Constrain Project Scheduling Problem (RCPSP) either ignore equipment planning or schedule the activities first, and then plan for the required equipment. Moreover, little works that consider simultaneous PSP and Equipment Planning (EP) are based on the assumption that the equipment is continuously available. However, in reality, equipment is subject to either random breakdowns or deterministic maintenance programs that make it not being available all the time. In this paper, the PSP and EP problems are simultaneously considered in closer to reality situations in which the equipment is not always available. In order to minimize costs and overcome the associated functional and structural complexities, the problem is first mathematically formulated. Then, a system simulator along with a genetic algorithm is utilized to find a near optimum solution. As there are no benchmarks available in the literature, a simulated annealing algorithm is also employed in combination with the simulator to validate the obtained results. In addition, design of experiments is used to set the parameters of the algorithms such that both the running times and the responses are minimized. Computational results on 400 generated test problems of different sizes indicate good performance of the genetic algorithm with respect to the basic parameters of the selected problem.