Permutation flowshop scheduling problem (PFSP) is a classical combinatorial optimisation problem, which has attracted much attention from academia and industry in the last two decades. However, there are still great challenges to overcome. In existing heuristic methods, jobs with similar processing times cannot be efficiently distinguished, so that jobs are not effectively sequenced, which could result in a poor scheduling solution. Also, most existing research has focused on static PFSPs with a single-objective, however, a single objective is sometimes not good enough, and multiple objectives are often required. In addition, many interruptions or disturbances such as newly arrived orders frequently occur, which creates significant challenges and needs to be addressed in scheduling research. This work focused on new job differentiation methods, multi-objective optimisation, and dynamic scheduling methods in static and dynamic environments respectively. In the static environment, three new priority rules using high moments of a probability distribution of job processing times are proposed, for the first time, so that jobs can be effectively distinguished and ordered. As a result, three new heuristics as well as a new tie-breaking rule are developed based on Nawaz-Enscore-Ham (NEH) heuristic for single-objective PFSPs. For multi-objective PFSPs, with makespan and idletime as the bicriteria, a new heuristic method is developed by incorporating a new priority rule and a new tie-breaking rule. As a result, our work has proved that makespan and idletime are not equivlent in sheduling optimisation, which corrects the existent misunderstanding in the scheduling community. In the dynamic environment, PFSPs with new order arrivals are investigated, and a new heuristic method is proposed by integrating a new match-up and real-time strategy through orders’ mixing. Also, a new meta-heuristic algorithm derived from iterated greedy algorithm is developed with a new enhanced destruction & construction method and a novel repair mechanism. For ease of application, a digital tool is developed to automatically implement these algorithms. A real industrial case is used to demonstrate the validity of these scheduling methods.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:727425 |
| Date | January 2017 |
| Creators | Liu, Weibo |
| Publisher | Queen's University Belfast |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
Page generated in 0.0014 seconds