Scheduling with Fuzzy Methods

TL;DR

This paper introduces a heuristic scheduling method that integrates fuzzy logic to effectively handle vagueness in production parameters, aiming for near-optimal solutions in complex, NP-hard manufacturing scheduling problems.

Contribution

It presents a novel heuristic approach combining standard scheduling techniques with fuzzy methods to address vagueness and complexity in manufacturing scheduling.

Findings

The method produces near-optimal schedules efficiently.

It effectively manages vagueness in scheduling parameters.

The approach is suitable for complex NP-hard problems.

Abstract

Nowadays, manufacturing industries -- driven by fierce competition and rising customer requirements -- are forced to produce a broader range of individual products of rising quality at the same (or preferably lower) cost. Meeting these demands implies an even more complex production process and thus also an appropriately increasing request to its scheduling. Aggravatingly, vagueness of scheduling parameters -- such as times and conditions -- are often inherent in the production process. In addition, the search for an optimal schedule normally leads to very difficult problems (NP-hard problems in the complexity theoretical sense), which cannot be solved effciently. With the intent to minimize these problems, the introduced heuristic method combines standard scheduling methods with fuzzy methods to get a nearly optimal schedule within an appropriate time considering vagueness adequately.