In this thesis, we develop a new search procedure based on priority rule for the resource constrained project scheduling problem with the objective of minimizing makespan. In the search procedure, a solution is represented with a string of integers called priority list, each of which denotes priority of each activity. In our algorithm, the priority scheduling method is used for making a complete schedule from a given priority list. A simulated annealing algorithm is applied to find a priority list which gives a good project schedule. Unlike most of search methods, in our algorithm some activities are delayed on purpose so as to extend solution space, which gives a higher possibility of improving solution since non-delay schedules are not dominant in the problem. Our search algorithm is flexible in that it can be easily applied to problems with an objective function of a general form and complex constraints. The performance of search heuristic is compared with existing heuristics on test problems presented by Patterson and randomly generated problems. Computational results showed that our heuristic outperformed existing algorithms.
