关键词:
Engineering
Industrial Engineering
Mathematics
Job Shop Scheduling
Max Plus Algebra
Mathematical Modeling
Computational Complexity
Makespan
Heursitics
Simulation
Scheduling Algorithm
摘要:
This dissertation develops efficient methods for calculating the makespan of a perturbed job shop. All iterative scheduling algorithms require their performance measure, usually the makespan, to be calculated during every iteration. Therefore, this work can enhance the efficiency of many existing scheduling heuristics, e.g. Tabu Search, Genetic Algorithms, Simulated Annealing etc. This increased speed provides two major benefits. The first is the capability of searching a larger solution space, and second is the capability to find a better solution due to the extra time. The following is a list of major highlights of this dissertation. The dissertation extends the hierarchical block diagram model formulation and composition that was originally proposed by Imaev. An algorithm is developed that reduces the complexity of calculating the makespan of the perturbed schedule of job shop with no recirculation from O(MNlogMN) to O(N2), where M is the number of machines and N the number of parts. An efficient algorithm that calculates kleene star of a lower triangular matrix is presented. This algorithm has complexity of O((n3)/6) which is 1/16th of the traditional approach. Finally, a novel pictorial methodology, called the SBA (Serial Block Addition), is developed to calculate the makespan of a perturbed job shop. A very efficient single perturbed machine scheduling algorithm, with complexity of O(N2), is derived using the SBA method. The algorithm was tested on 10,000 randomly generated problems. The solutions provided by scheduling algorithm were 95.27% times, within a 3% deviation of the optimal solutions.