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Minslack and Kangaroo Algorithms for Fuzzy Project Scheduling Problems
Omer Atli and Cengiz Kahraman

This paper uses a resource allocation model to solve the project scheduling problem under fuzzy environment. We employ the uses of kangaroo algorithms and the fuzzy set theory to develop the Resource-Constrained Project Scheduling (RCPS) model under uncertainty. Our work proposes a mathematical model to deal with project scheduling problem under vagueness and presenting the framework of a heuristic approach to fuzzy RCPSP using a fuzzy parallel kangaroo and minslack scheduling method. We adopted the Parallel Kangaroo Algorithm Method to Fuzzy RCPSP. The objective is to minimize project planning time with resource limitations 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-Arcs (AOA) representation in fuzzy critical path method (FCPM). Fuzzy RCPS is often a challenging issue in practice, due to its combinatorial nature and uncertainty. We present the application results of the computational the minslack and the Kangaroo algorithm and comparison of these two methods is also given.

Keywords: Fuzzy CPM; fuzzy set theory; fuzzy project scheduling; heuristics methods; kangaroo algorithm; fuzzy RCPSP

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