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(2008) Hasan, S. M. Kamrul; Sarker, Ruhul; Cornforth, DavidConference PaperThe Job-Shop Scheduling Problem (JSSP) is considered as one of the difficult combinatorial optimization problems and treated as a member of NP-complete problem class. In this paper, we consider JSSPs with an objective of minimizing makespan while satisfying a number of hard constraints. First, we develop a genetic algorithm (GA) based approach for solving JSSPs. We then introduce a number of priority rules such as partial reordering, gap reduction and restricted swapping to improve the performance of the GA. We run the GA incorporating these rules in a number of different ways. We solve 40 benchmark problems and compared their results with that of a number of well-known algorithms. We obtain optimal solutions for 27 problems, and the overall performance of our algorithms is quite encouraging.
(2007) Hasan, S. M. Kamrul; Sarker, Ruhul; Cornforth, DavidConference PaperThe Job-Shop Scheduling Problem (JSSP) is one of the most critical combinatorial optimization problems. The objective of JSSP in this research is to minimize the makespan. In this paper, we propose two Genetic Algorithm (GA) based approaches for solving JSSP. Firstly, we design a simple heuristic to reduce the completion time of jobs on the bottleneck machines that we call the reducing bottleneck technique (RBT). This heuristic was implemented in conjunction with a GA. Secondly; we propose to fill any possible gaps left in the simple GA solutions by the tasks that are scheduled later. We call this process the gap-utilization technique (GUT). With GUT, we also apply a swapping technique that deals only with the bottleneck job. We study 35 test problems with known solutions, using the existing GA and our proposed two algorithms. We obtain optimal solutions for 23 problems, and the solutions are very close for the rest.
(2008) Hasan, S. M. Kamrul; Sarker, Ruhul; Essam, DarylConference PaperThe primary objective of this research is to solve the job-shop scheduling problems by minimizing the makespan. In this paper, we first developed a genetic algorithm (GA) for solving JSSPs, and then improved the algorithm by integrating with three priority rules. The performance of the developed algorithm was tested by solving 40 benchmark problems and comparing their results with that of a number of well-known algorithms. For convenience of im-plementation, we developed a decision support system (DSS). In the DSS, we built a graphical user interface (GUI) for user friendly data inputs, model choices, and output generation. An overview of the DSS and the analysis of experimental results are provided.
(2007) Smith, WarrenConference PaperThe philosophy of the “Warman Design and Build Competition” and some of the challenges of running it are described in this perspective by its National Coordinator since 2003. In particular, the need is for the competition to work effectively across a wide range of student group ability. Not every group engaging with the competition will be competitive nationally, yet all should learn positively from the experience. Reported also in this paper is the collective feedback from the 2006 campus organizers in respect to their use of the competition as an educational experience in their classrooms. Each University participating uses the competition differently with respect to student assessment and the support students receive. However, all academic campus organizer responses to the survey suggest that the competition supports their own learning objectives very well. The competition which was first run in 1988 will have its 20th anniversary final in September this year. While the projects have varied widely over the years, the intent to challenge 2nd year university (predominantly mechanical) engineering students with an open-ended statement of requirements in a practical and experiential exercise has been a constant. Students are faced with understanding their opportunity and their client’s value system as expressed in a scoring algorithm; they are required to conceive, construct and demonstrate their device with limited prior knowledge and experience, and the learning outcomes clearly impact their appreciation for teamwork, leadership and product realization. The competition has been successful due in part to its underpinning by the National Committee on Engineering Design (Engineers Australia), the sponsorship of Weir Minerals and the commitment of many engineering design educators across Australia and New Zealand.
(2007) Pota, Himanshu; Katupitiya, Jayantha; Eaton, RayConference PaperThis work presents the derivation of a comprehensive mathematical model for an off-road vehicle such as an agricultural tractor that drags behind it a heavy implement. The models are being developed with the aim of designing robust controllers that will enable the high precision control of the implement’s trajectory. The developed model is subjected to real conditions, such as ground undulation and uncertainty, sloping terrain, tyre slippage, and constrained steering of the tractor. The implement is assumed to possess independently steered wheels for aiding in implement alignment. A complete model is presented and simulated under varying conditions. Primarily this work demonstrates and validates the trailed vehicle system behavior when the trailing implement is subjected to large drag forces due to ground engagement and the significantly large lateral disturbances that occur in real life broad acre farming conditions.
(2008) LI, M; WANG, F; Tabatabaei Balaei, Asghar; DEMPSTER, A.G; RIZOS, CConference Paper