This chapter studies the incorporation of uncertainty into multi-project rough-cut capacity planning. We use fuzzy sets to model uncertainties, adhering to the so-called possibilistic approach. We refer to the resulting proactive planning environment as Fuzzy Rough Cut Capacity Planning (FRCCP). Uncertain workloads are modeled as fuzzy numbers, and a Simulated Annealing (SA) procedure is proposed to solve the underlying optimization problem. The performance of the SA algorithm is studied in comparison to an existing deterministic Branch&Price algorithm and to an LP-based heuristic, which are both generalized to handle fuzzy parameters. Computational experiments are performed on instances from a shipyard maintenance centre, in which we examine the computational performance of the algorithms and we also study to what extent multi-objective optimization techniques can be applied.
|Title of host publication||Sequencing and scheduling with inaccurate|
|Editors||Yuri N. Sotskov, Frank Werner|
|Number of pages||16|
|Publication status||Published - 2014|
|Publisher||Nova Science Publishers|