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Machine Scheduling With Preventive MaintenancesBatun, Sakine 01 June 2006 (has links) (PDF)
In manufacturing environments, machines are usually subject to down periods due to various reasons such as preventive maintenance activities, pre-accepted jobs and pre-known material shortages. Among these reasons, preventive maintenance, which is defined as the pre-planned maintenance activities to keep the machine in its operating state, has gained much more importance in recent years.
In this thesis, we consider the single machine total flow time problem where the jobs are non-resumable and the machine is subject to preventive maintenance activities of known starting times and durations. We propose a number of optimality properties together with the upper and lower bounding procedures. Using these mechanisms, we build a branch and bound algorithm to find the optimal solution of the problem. Our extensive computational study on randomly generated test instances shows that our algorithm can solve large-sized problem instances with up to 80 jobs in reasonable times.
We also study a two-alternative maintenance planning problem with minor and major maintenances. We give an optimizing algorithm to find the timing of the maintenances, when the job sequence is fixed.
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Discrete Time/cost Trade-off Problem In Project SchedulingHafizoglu, Ahmet Baykal 01 July 2007 (has links) (PDF)
In project scheduling, the activity durations can often be reduced by dedicating additional resources. Time/Cost Trade-off Problem considers the compromise between the total cost and project duration. The discrete version of the problem assumes a number of time/cost pairs, so called modes, and selects a mode for each activity.
In this thesis we consider the Discrete Time/Cost Trade-off Problem. We first study the Deadline Problem, i.e., the problem of minimizing total cost subject to a deadline on project duration. To solve the Deadline Problem, we propose several optimization and approximation algorithms that are based on optimal Linear Programming Relaxation solutions. We then analyze the problem of generating all efficient solutions, and propose an approach that uses the successive solutions of the Deadline Problem.
Our computational results on large-sized problem instances have revealed the satisfactory behavior of our algorithms.
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Intelligent Search And Algorithms For Optimal Assignment Of Air Force Resources In OperationsRizvanoglu, Emre 01 December 2008 (has links) (PDF)
The growing extent and variety of present military operations forces to use the resources in hand at its best. Especially, the optimum usage and assignment of limited number of the air force resources to missions will provide a considerable advantage in the battle field. The problem of finding the feasible and optimum assignment has been known to be studied / yet performing the process faster is still a topic that captures researchers&rsquo / attention because of the computational complexity that the assignment problem involves within.
In this thesis, exploring the optimal assignment of fleets/aircrafts to targets/groups of targets is going to be performed via algorithms and heuristics. As the best choice for finding the exact solution, Branch-and-Bound algorithm, which is an intelligent way of searching for the solution on a solution tree where the nodes with potential of not leading to the solution are fathomed, has been investigated and applied according to the specific problem needs. The number of nodes on the search tree increases exponentially as the problem size increases. Moreover / as the size of the assignment problem increases, attaining the solution solely by Branch-and-Bound algorithm is definitely computationally expensive due to memory and time requirements. Therefore, Genetic algorithm which can provide good solutions in a relatively short time without having computational difficulties is considered as the second algorithm. Branch-and-Bound algorithm and Genetic algorithm are separately used for obtaining the solution. Hybrid algorithms which are combinations of Branch-and-Bound and Genetic algorithms are used with heuristics for improving the results.
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Flexible Assembly Line Design Problem With Fixed Number Of WorkstationsBarutcuoglu, Sirin 01 July 2009 (has links) (PDF)
ABSTRACT
FLEXIBLE ASSEMBLY LINE DESIGN PROBLEM WITH FIXED NUMBER OF WORKSTATIONS
Barutç / uoglu, Sirin
M.S. Department of Industrial Engineering
Supervisor: Prof. Dr. Meral Azizoglu
July 2009, 70 pages
In this thesis, we study a Flexible Assembly Line Design problem. We assume the task times and equipment costs are correlated in the sense that for all tasks the cheaper equipment gives no smaller task time. Given the cycle time and number of workstations we aim to find the assignment of tasks and equipments to the workstations that minimizes the total equipment cost. We study a special case of the problem with identical task times. For the general case, we develop a branch and bound algorithm that uses powerful lower bounds and reduction mechanisms. We test the performance of our branch and bound algorithm on randomly generated test problems. The results of our experiments have revealed that we are able to solve large-sized problem instances in reasonable times.
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Approximation and Optimal Algorithms for Scheduling Jobs subject to Release DatesYu, Su-Jane 30 July 2003 (has links)
In this dissertation, we study the single machine scheduling problem with an objective of minimizing the total completion time subject to release dates. The problem, denoted 1|rj £UCj ,was known to be strongly NP-hard and both theoretically and practically important. The focus of the research in this dissertation is to develop the efficient algorithms for solving the 1|rj|£UCj problem.
This thesis contains two parts.
In the first part, the theme concerns the approximation approach. We derive a necessary and sufficient condition for local optimality, which can be implemented as a priority rule and be used to construct three heuristic algorithms with running times of O(n log n). By ¡¨local optimality¡¨, we mean the optimality of all candidates whenever a job is selected in a schedule, without considering the other jobs preceding or following. This is the most broadly considered concepts of locally optimal rule. We also identify a dominant subset which is strictly contained in each of all known dominant subsets, where a dominant subset is a set of solutions containing all optimal schedules.
In the second part, we develop our optimality algorithms for the 1|rj |£UCj problem. First, we present a lemma for estimating the sum of delay times of the rest jobs, if the starting time is delayed a period of time in a schedule. Then, using the lemma, partially, we proceed to develop a new partition property and three dominance theorems, that will be used and have improved the branch-and-bound algorithms for our optimization approach. By exploiting the insights gained from our heuristics as a branching scheme and by exploiting our heuristics as an upper bounding procedure, we propose three branch-and-bound algorithms. Our algorithms can optimally solve the problem up to 120 jobs, which is known to be the best till now.
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Parameterized complexity and polynomial-time approximation schemesHuang, Xiuzhen 17 February 2005 (has links)
According to the theory of NPcompleteness, many problems that have important realworld applications are NPhard. This excludes the possibility of solving them in polynomial time unless P=NP. A number of approaches have been proposed in dealing with NPhard problems, among them are approximation algorithms and parameterized algorithms. The study of approximation algorithms tries to find good enough solutions instead of optimal solutions in polynomial time, while parameterized algorithms try to give exact solutions when a natural parameter is small.
In this thesis, we study the structural properties of parameterized computation and approximation algorithms for NP optimization problems. In particular, we investigate the relationship between parameterized complexity and polynomialtime approximation scheme (PTAS) for NP optimization problems.
We give nice characterizations for two important subclasses in PTAS: Fully Polynomial Time Approximation Scheme (FPTAS) and Effcient Polynomial Time Approximation Scheme (EPTAS), using the theory of parameterized complexity. Our characterization of the class FPTAS has its advantages over the former characterizations, and our characterization of EPTAS is the first systematic investigation of this new but important approximation class.
We develop new techniques to derive strong computational lower bounds for certain parameterized problems based on the theory of parameterized complexity. For example, we prove that unless an unlikely collapse occurs in parameterized complexity theory, the clique problem could not be solved in time O(f (k)no(k)) for any function
f . This lower bound matches the upper bound of the trivial algorithm that simply enumerates and checks all subsets of k vertices in the given graph of n vertices.
We then extend our techniques to derive computational lower bounds for PTAS and EPTAS algorithms of NP optimization problems. We prove that certain NP optimization problems with known PTAS algorithms have no PTAS algorithms of running time O(f (1/Epsilon)no(1/Epsilon)) for any function f . Therefore, for these NP optimization problems, although theoretically they can be approximated in polynomial time to an arbitrarily small error bound Epsilon, they have no practically effective approximation algorithms for small error bound Epsilon. To our knowledge, this is the first time such lower bound results have been derived for PTAS algorithms. This seems to open a new direction for the study of computational lower bounds on the approximability of NP optimization problems.
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General schedulability bound analysis and its applications in real-time systemsWu, Jianjia 17 September 2007 (has links)
Real-time system refers to the computing, communication, and information system with deadline requirements. To meet these deadline requirements, most systems use a mechanism known as the schedulability test which determines whether each of the admitted tasks can meet its deadline. A new task will not be admitted unless it passes the schedulability test. Schedulability tests can be either direct or indirect. The utilization based schedulability test is the most common schedulability test approach, in which a task can be admitted only if the total system utilization is lower than a pre-derived bound. While the utilization bound based schedulability test is simple and effective, it is often difficult to derive the bound. For its analytical complexity, utilization bound results are usually obtained on a case-by-case basis. In this dissertation, we develop a general framework that allows effective derivation of schedulability bounds for different workload patterns and schedulers. We introduce an analytical model that is capable of describing a wide range of tasks' and schedulers'ÃÂÃÂ behaviors. We propose a new definition of utilization, called workload rate. While similar to utilization, workload rate enables flexible representation of different scheduling and workload scenarios and leads to uniform proof of schedulability bounds. We introduce two types of workload constraint functions, s-shaped and r-shaped, for flexible and accurate characterization of the task workloads. We derive parameterized schedulability bounds for arbitrary static priority schedulers, weighted round robin schedulers, and timed token ring schedulers. Existing utilization bounds for these schedulers are obtained from the closed-form formula by direct assignment of proper parameters. Some of these results are applied to a cluster computing environment. The results developed in this dissertation will help future schedulability bound analysis by supplying a unified modeling framework and will ease the implementation practical real-time systems by providing a set of ready to use bound results.
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On Models and Methods for Global Optimization of Structural TopologyStolpe, Mathias January 2003 (has links)
<p>This thesis consists of an introduction and sevenindependent, but closely related, papers which all deal withproblems in structural optimization. In particular, we considermodels and methods for global optimization of problems intopology design of discrete and continuum structures.</p><p>In the first four papers of the thesis the nonconvex problemof minimizing the weight of a truss structure subject to stressconstraints is considered. First itis shown that a certainsubclass of these problems can equivalently be cast as linearprograms and thus efficiently solved to global optimality.Thereafter, the behavior of a certain well-known perturbationtechnique is studied. It is concluded that, in practice, thistechnique can not guarantee that a global minimizer is found.Finally, a convergent continuous branch-and-bound method forglobal optimization of minimum weight problems with stress,displacement, and local buckling constraints is developed.Using this method, several problems taken from the literatureare solved with a proof of global optimality for the firsttime.</p><p>The last three papers of the thesis deal with topologyoptimization of discretized continuum structures. Theseproblems are usually modeled as mixed or pure nonlinear 0-1programs. First, the behavior of certain often usedpenalization methods for minimum compliance problems isstudied. It is concluded that these methods may fail to producea zero-one solution to the considered problem. To remedy this,a material interpolation scheme based on a rational functionsuch that compli- ance becomes a concave function is proposed.Finally, it is shown that a broad range of nonlinear 0-1topology optimization problems, including stress- anddisplacement-constrained minimum weight problems, canequivalently be modeled as linear mixed 0-1 programs. Thisresult implies that any of the standard methods available forgeneral linear integer programming can now be used on topologyoptimization problems.</p><p><b>Keywords:</b>topology optimization, global optimization,stress constraints, linear programming, mixed integerprogramming, branch-and-bound.</p>
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Outcomes associated with Outward Bound and NOLS programs a means-end study : a thesis /Pronsolino, Daniel T., Goldenberg, Marni, January 1900 (has links)
Thesis (M.S.)--California Polytechnic State University, 2009. / Mode of access: Internet. Title from PDF title page; viewed on Jan. 8, 2010. Major professor: Dr. Marni Goldenberg. "Presented to the faculty of California Polytechnic State University, San Luis Obispo." "In partial fulfillment of the requirements for the degree [of] Master of Science in Agriculture, with specialization in Recreation, Parks, and Tourism." "December 2009." Includes bibliographical references (p. 80-88).
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Light front field theory calculation of deuteron properties /Cooke, Jason Randolph, January 2001 (has links)
Thesis (Ph. D.)--University of Washington, 2001. / Vita. Includes bibliographical references (p. 139-148).
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