Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/14184
Title: Genetic algorithm compared to nonlinear optimization for labour and equipment assignment
Authors: Li, H 
Love, PED
Ogunlana, S
Keywords: Genetic algorithms
Labour and equipment assignment
Nonlinear optimization
Issue Date: 1998
Publisher: Routledge, Taylor & Francis Group
Source: Building research and information, 1998, v. 26, no. 6, p. 322-329 How to cite?
Journal: Building research and information 
Abstract: The genetic algorithm is a technique based on evolutionary optimization. A methodology for optimizing labour and equipment assignment using the genetic algorithm is presented. A number of modifications are introduced to the three operators of the genetic algorithm, namely, reproduction, crossover and mutation. Results from the genetic algorithm are compared to the nonlinear optimization technique in solving the labour and equipment assignment problem. A comparison of the two techniques indicates that the genetic algorithm has the capacity to ensure a global optimal solution. However, its computational operations take longer than the nonlinear optimization technique in obtaining near-optimal or optimal solutions.
URI: http://hdl.handle.net/10397/14184
ISSN: 0961-3218
EISSN: 1466-4321
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