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.
Original language | English |
---|---|
Title of host publication | Computing in Civil Engineering |
Editors | Carlos H. Caldas, William J. O'Brien |
Publisher | American Society of Civil Engineers |
Pages | 166-175 |
ISBN (Print) | 978-0-7844-1052-3 |
DOIs | |
Publication status | Published - 2009 |