Chapter
Apr 26, 2012
Using Genetic Algorithms to Improve Crew Allocation Process in Labour-Intensive Industries
Authors: Nashwan Dawood [email protected] and Ammar Al-Bazi, Ph.D. [email protected]Author Affiliations
Publication: Computing in Civil Engineering (2009)
Abstract
The high cost of skilled workers in labour-intensive production industries has motivated senior production managers to identify the best allocation strategy of crews of workers to appropriate processes. The aim of this paper is to develop a crew allocation system using Genetic Algorithms-based simulation modeling. The objective is to optimally allocate crews of workers to labour-intensive production industries to minimise labour costs. In this paper, a simulation-based Genetic Algorithm (GA) system dubbed "SIM_Crew" is developed to simulate the physical processes of a labour-driven facility. The GA is tailored to be embedded with the developed simulation model for improved solution searching. A chromosome structure is designed to apply such problems and a probabilistic selection of promising chromosomes is applied as a selection strategy, n-points crossover and mutation strategies are designed to add more randomness to the searching process. A case study in the precast industry is presented to demonstrate and validate the model.
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© 2009 American Society of Civil Engineers.
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Published online: Apr 26, 2012
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Professor, Center for Construction Innovation Research (CCIR), School of Science and Technology (SST), University of Teesside, Middlesbrough, TS1 3BA, UK. E-mail: [email protected]
Researcher, Center for Construction Innovation Research (CCIR), School of Science and Technology (SST), University of Teesside, Middlesbrough, TS1 3BA, UK. E-mail: [email protected]
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