Title :
Machine requirements planning and workload assignment using genetic algorithms
Author :
Porter, B. ; Mak, K.L. ; Wong, Y.S.
Author_Institution :
Dept. of Aeronaut. Mech. & Manuf. Eng., Salford Univ., UK
fDate :
29 Nov-1 Dec 1995
Abstract :
This paper presents a genetic approach to determining the optimal number of machines required in a manufacturing system for meeting a specified production schedule. This use of genetic algorithms is illustrated by solving a typical machine requirements planning problem. Comparison of the respective results obtained by using the proposed approach and a standard mixed-integer programming package shows that the proposed approach is indeed an effective means for optimal manufacturing systems design
Keywords :
computer aided production planning; genetic algorithms; integer programming; manufacturing resources planning; production control; resource allocation; scheduling; genetic algorithms; machine requirements planning; mixed-integer programming package; optimal machine number; optimal manufacturing systems design; production schedule; workload assignment; Aerospace industry; Cost function; Genetic algorithms; Genetic engineering; Manufacturing industries; Manufacturing systems; Mathematical model; Meeting planning; Pulp manufacturing; Systems engineering and theory;
Conference_Titel :
Evolutionary Computation, 1995., IEEE International Conference on
Conference_Location :
Perth, WA
Print_ISBN :
0-7803-2759-4
DOI :
10.1109/ICEC.1995.487472
