caa a22 4500 475798791 CHVBK 20180406123731.0 cr unu---uuuuu 170329e20000701xx s 000 0 eng 10.1007/s001700070052 doi (NATIONALLICENCE)springer-10.1007/s001700070052 The Application of Parallel Multipopulation Genetic Algorithms to Dynamic Job-Shop Scheduling [Elektronische Daten] [J. G. Qi, G. R. Burns, D. K. Harrison] This paper describes the use of parallel multipopulation genetic algorithms (GAs) to meet the dynamic nature of job-shop scheduling. A modified genetic technique is adopted by using a specially formulated genetic operator to provide an efficient optimisation search. The proposed technique has been successfully implemented using the programming language MATrix LABoratory (MATLAB), providing a powerful tool for job-shop scheduling. Comparisons indicate that the proposed genetic algorithm has successfully improved upon the solution obtained from conventional approaches, particularly in coping with job-shop scheduling.: Springer-Verlag London Limited, 2000 Keywords:Dispatching rules nationallicence Genetic algorithms nationallicence Integer linear programming nationallicence Job-shop scheduling nationallicence MATLAB nationallicence Multi-population genetic algorithms nationallicence Qi J. G. Department of Engineering, Glasgow Caledonian University, Glasgow, UK, GB aut Burns G. R. Department of Engineering, Glasgow Caledonian University, Glasgow, UK, GB aut Harrison D. K. Department of Engineering, Glasgow Caledonian University, Glasgow, UK, GB aut https://doi.org/10.1007/s001700070052 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s001700070052 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Qi J. G. Department of Engineering, Glasgow Caledonian University, Glasgow, UK, GB aut NATIONALLICENCE 700 1- Burns G. R. Department of Engineering, Glasgow Caledonian University, Glasgow, UK, GB aut NATIONALLICENCE 700 1- Harrison D. K. Department of Engineering, Glasgow Caledonian University, Glasgow, UK, GB aut Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer