||Development of Hybrid Simulation and Genetic Algorithms System for Solving Complex Crew Allocation Problems
||A. Al-Bazi, N. Dawood & Z. Khan
||This paper presents an innovative approach to solving complex crew allocation problems in any labour-intensive industry. This has been achieved by combining simulation with Genetic Algorithm (GA). The integrated system determines the least costly and most productive crews to be allocated on any produc-tion processes. Discrete Event Simulation methodology is used to simulate a manufacturing system. A special PROCESS module is developed to overcome limitation of the used simulation software that appears when us-ing normal PROCESS module. A concept of multi-layer chromosome is proposed to store different data sets in multi-layers structure. GA operators were developed to suit such chromosome structure. As a case study, a sleeper precast manufacturing system is chosen to prove the concept of the proposed allocation system. The results showed that adopting Manipulating a number of multi-skilled workers to be allocated among different production processes had a substantial impact on reducing total allocation cost, process-waiting time, and op-timising resource utilisation. 3D visualisation is presented.
|Year of publication:
A. Al-Bazi, N. Dawood & Z. Khan (2009).
Development of Hybrid Simulation and Genetic Algorithms System for Solving Complex Crew Allocation Problems. CIB W078 2009 (ISSN: 2706-6568),