An outer-inner fuzzy cellular automata algorithm for dynamic uncertainty multi-project scheduling problem

Current research on the resource-constrained multi-project scheduling problem(RCMPSP) mainly focuses on the constrained resources or other single uncertainty factor that cannot satisfy the practical need of enterprise management. This paper addresses the dynamic uncertain multi-project scheduling problem (DUMPSP), which alleviates the above problem of RCMPSP by synthesizing the analysis of uncertainty, sensitivity, and lean management of resources and durations. An outer-inner uncertainty fuzzy cellular automata algorithm (OIUFCA) is proposed to solve DUMPSP. The problem is divided into several parts: (1) fuzzy cell is employed to describe the project cell and process cell in DUMPSP; (2) a fuzzy outer cellular automata (FOCA) model is defined to solve the project scheduling of DUMPSP, and a fuzzy inner cellular automata (FICA) model is constructed to solve the process scheduling; (3) multi-level feedback strategy (MFS) is further proposed to deal with the multi-level dual-stage optimization problem of DUMPSP. Besides, FOCA and FICA model execute co-evolution under the control of MFS. Extensive experiments are carried out to evaluate the performances of OIUFCA with other state-of-the-art algorithms. It is revealed that OIUFCA achieves a better performance in success rate and convergence speed in solving DUMPSP, and OIUFCA has a good solution under different conditions of uncertainty, sensibility, and lean management.