Optimal Fuzzy Scheduling and Sequencing of Work-Intensive Multiple Projects Under Normal and Unexpected Events

This research proposed optimization models for task scheduling and sequencing in work-intensive multiple projects under normal and unexpected events. The objectives of scheduling model were minimizing the total overtime/under-time costs and maximizing satisfaction values on tasks due dates and processing standard times. Further, the sequencing model aimed to minimize the sum of tasks' start times, maximize resource utilization, and maximize satisfaction on project completion times. Illustrations of the proposed scheduling and sequencing optimization models were provided where the results showed effective scheduling and sequencing of project tasks at minimal costs and achieved the desired satisfaction levels on tasks and projects and significantly enhanced resource efficiency at minimal overtime and under-time costs. Further, optimization models were modified to deal with unexpected events. In conclusion, the proposed models may support project managers in planning project tasks in a cost-effective manner under normal and unexpected events.