In practice, projects may contain many activities. To schedule such projects, under constraints of limited resource and precedence relations, it becomes an NP hard problem. Any exact algorithms will have difficulty solving such problems. In addition, many activities of a project are quite often imprecise and vague due to lack of sufficient information. Fuzzy set theory is the best way to describe such data. In this study, a fuzzy simulated annealing approach is developed to handle resource-constrained project scheduling with fuzzy data.
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