Date of Award
Industrial and Manufacturing Systems Engineering
El Maraghy, H. A.
CC BY-NC-ND 4.0
In this research a solution methodology and a software program system for assignment of dual resources (Machines and Workers) were developed. By considering two dual resource constrained problems as the candidate problems, an optimized GA based heuristic was developed. First genetic algorithms were used to determine the optimal staffing level which can be viewed as a basic design decision. Second, genetic algorithms were used to make short range control decisions regarding the operations of dual resource constrained shop. Six different dispatching rules such as SPT, EOPNDD, EDD, FCFS, LSO, LPT and eight performance criteria were used. The performance of each rule with respect to each performance criterion for dual resource constrained shops is compared to single resource constrained shop. Finally, a system has been developed in 'C'. Scheduling data required for schedule optimization is inputted into the system by user interface. Genetic algorithms optimize the assignment of dual resources to each task. The genetic algorithms output a list of several assignment of dual resources to each task. This assignment of dual resources is then analyzed by the output analyzer. (Abstract shortened by UMI.) Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis1997 .P378. Source: Masters Abstracts International, Volume: 37-01, page: 0337. Adviser: H. A. ElMaraghy. Thesis (M.A.Sc.)--University of Windsor (Canada), 1997.
Patel, Vishvas., "Scheduling in a dual resource constrained system using genetic algorithms." (1997). Electronic Theses and Dissertations. 3379.