Title

An Adaptive Genetic Algorithm for Demand- Driven and Resource-Constrained Project Scheduling in Aircraft Assembly

Document Type

Article

Publication Date

4-2015

Publication Source

Information Technology and Management

DOI

10.1007/s10799-015-0223-7

Publisher

Springer New York LLC

ISBN/ISSN

1385951X

Peer Reviewed

yes

Abstract

Scheduling of aircraft assembling activities is proven as a non-deterministic polynomial-time hard problem; which is also known as a typical resource-constrained project scheduling problem (RCPSP). Not saying the scheduling of the complex assemblies of an aircraft, even for a simple product requiring a limited number of assembling operations, it is difficult or even infeasible to obtain the best solution for its RCPSP. To obtain a high quality solution in a short time frame, resource constraints are treated as the objective function of an RCPSP, and an adaptive genetic algorithm (GA) is proposed to solve demand-driven scheduling problems of aircraft assembly. In contrast to other GA-based heuristic algorithms, the proposed algorithm is innovative in sense that: (1) it executes a procedure with two crossovers and three mutations; (2) its fitness function is demand-driven. In the formulation of RCPSP for aircraft assembly, the optimizing criteria are the utilizations of working time, space, and operators. To validate the effectiveness of the proposed algorithm, two encoding approaches have been tested with the real data of demand.

Keywords

Aircraft assembly, Demand-driven, Genetic algorithm, NP-hard problems, Project scheduling, Resource-constrained, Resource-constrained project scheduling problem (RCPSP)

Disciplines

Engineering

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