A Robust Predictive-Reactive Allocating Approach, Considering Random Design Change in Complex Product Design Processes

In the highly dynamic complex product design process, task allocations recovered by reactive allocating decisions are usually subject to design changes. In this paper, a robust predictive–reactive allocating approach considering possible disruption times is proposed, so that it can absorb the disruption in the executing process and utilize the limited capacity of resource more effectively. Four indexes (Makespan, stability, robustness, and compression cost) are used to measure the quality of the proposed method. To illustrate the novel allocating idea, we first assign tasks to resources with the objective of a trade-off between the overall execution time and the overall design cost, which can transform the problem into a non-identical parallel environment. Then, the probability distribution sequencing (PDS) method combining with inserting idle time (IIT) is proposed to generate an original-predictive allocation. A match-up time strategy is considered to match up with the initial allocation at some point in the future. The relationship between the minimum match-up time and the compression cost is analyzed to find the optimal matchup time. Our computational results show that the proposed sequencing method is better than the shortest processing time (SPT) which is a common sequencing way mentioned in the literature. The robust predictive–reactive allocating approach is sensitive to the design change, which is helpful to reduce the reallocating cost and keep the robustness and stability.