This paper proposes a mathematical model to deal with project scheduling problem under vagueness and a framework of a heuristic approach to fuzzy resource‐constrained project scheduling problem (F‐RCPSP) using heuristic and metaheuristic scheduling methods. Our approach is very simple to apply, and it does not require knowing the explicit form of the membership functions of the fuzzy activity times. We first identify two typical activity priority rules, namely, resource over time and minimum slack priority rules. They are used in the F‐RCPS problem and in the initial solution of Taboo search (TS) method. We improved the TS algorithm method for the solution of F‐RCPSP. Our objective is to check the performance of these rules and metaheuristic method in minimizing the project completion time for the F‐RCPS problems. In our study, we use trapezoidal fuzzy numbers (TraFNs) for activity times and activity‐on‐nodes (AON) representation and compute several project characteristics such as earliest, latest, and slack times in terms of TraFNs. The computational experiment shows that the performance of the proposed TS is better than the evaluation and light beam search algorithms in the literature. © 2012 Wiley Periodicals, Inc.

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In this paper we consider the fuzzy and crisp multi mode resource-constrained project scheduling problem (F/C-MM-RCPSP) with multiple execution modes for each activity. The objective function is the minimization of the project completion time. Heuristics based on Minslack priority rules are considered as initial solution procedures for this problem. Nevertheless, the NP-hard nature of the problem which is difficult to use to solve realistic sized projects makes necessary the use of heuristic and metaheuristics in practice. A global search metaheuristics taboo search algorithm (TSA) is proposed to solve this NP-hard problem. Two heuristic algorithms are developed to solve an F/C-MM-RCPSP. The first one is a minslack priority scheduling algorithm which includes a combination of an activity and a mode selection rule; the second one is a TSA. The solutions obtained by the former algorithm with the best activity and mode-priority rule combination are used as a baseline to compare those obtained by the latter. Finally, we present the results of our through computational study. A computational experiment is described, performed on a set of instances based on standard test problems from the PSPlib for the MM-RCPSPs. The algorithms are computationally compared, the results are analyzed and discussed and some conclusions are given.

Aircraft's availability is certainly one of the most important features of modern avionic industry. The aircraft maintenance scheduling is one of the major decisions an airline has to make during its operation. When an aircraft maintenance event occurs, the overhaul tasks management process requires the execution of all tasks to perform and has to guarantee the on-time aircraft delivery and the respect of the daily flight schedule. Though maintenance scheduling comes as an end stage in an airline operation, it has potential for cost savings. Maintenance scheduling is an easily understood but difficult to solve problem. Given a flight schedule with aircraft assigned to it, the aircraft maintenance-scheduling problem is to determine which aircraft should fly which segment and when and where each aircraft should undergo different levels of maintenance check. The objective of this paper is to minimize the aircraft maintenance planning time and to show how to create a plan with critical path analyses under fuzzy environment. We use trapezoidal fuzzy numbers for activity times and Activity-on-Node (AON) representation in fuzzy critical path method (FCPM). An illustrative example is given for Aircraft Gas Turbine Engine Repair/Overhaul problem.

When the project is scheduled with a given set of resources, it is difficult to find the optimal solution. Resourceconstrained scheduling problems (RCPSP) are generally NP-hard. In this paper, a high level heuristic procedure "Tabu Search Algorithm (TSA)" is proposed to provide good solutions to resource-constrained, deterministic activity duration project scheduling problems. We present the application results of the computational tabu search and OPL-CPLEX algorithm and compare them with that of earlier applicable researches along with a discussion about further research. Our computational results are presented, which establish the superiority of tabu search over the existing heuristic algorithms. Two different solution strategies are also discussed, namely tabu search and OPL-CPLEX exact algorithm approach which can be used with the proposed model. Due to the execution time, we have shown that OPL-CPLEX's algorithm is a valid method with medium scale RCPSPs. For the considered deterministic problems, a good agreement has been obtained between theoretical and experimental results.