University of Macau / Faculty of Science and Technology / Department of Computer and Information Science

This study considers bicriteria approaches to the minimum cost network flow problem and a rescheduling problem where those approaches find their applications. For the bicriteria integer minimum cost network flow problem, we generate all efficient solutions in two phases. The first phase generates the extreme supported efficient points that are the extreme points of the objective space of the continuous bicriteria network flow problem. In the second phase, we generate the nonextreme supported and unsupported efficient points by Integer Programming Based approaches. Our rescheduling problem considers parallel unrelated machine environments. The criteria are the total flow time as an efficiency measure and the total reassignment cost as a stability measure. We show that the problems that address linear functions of the two criteria can be represented by bicriteria network flow models. To generate all efficient solutions, we use a Classical Approach that is based on the optimal solutions of the singly constrained network flow problem and provide a Branch and Bound approach that starts with extreme supported efficient set and uses powerful bounds. To find an optimal solution to any nonlinear function of the two criteria, we provide a Branch and Bound approach and an Integer Programming Based approach that eliminates some portions of the efficient set that cannot provide improved solutions. We contribute both to the network flow and scheduling literature by proposing algorithms to the bicriteria network flow models and applying them to a rescheduling problem that is bicriteria in nature. The results of our extensive computations with up to 100 jobs and 12 machines have revealed that, the Branch and Bound algorithm finds the efficient set in less computational effort compared to the classical approach. In minimizing a nonlinear function of the two criteria both IP Based approach and Branch and Bound algorithm perform quite satisfactory.

In this study a time based bidding framework is developed which is used for dispatching jobs to manufacturing resources in a virtual shop-floor environment. Agent-based shop-floor control approach is implemented with machine and part agents. The Contract-net communication protocol is utilized as the negotiation scheme between these agents. Single step product reservation (SSPR) technique is adopted throughout the study. Primary objective is determined as meeting the due dates and if the lateness is inevitable, avoiding the parts of high priority from being late. A balanced machine utilization rate is set as the secondary objective. During bid construction step, the SSPR technique is augmented with W(SPT+CR) sequencing rule in order to obtain weighted tardiness results. Bids containing Earliest Finishing Time (EFT) and machine loading values of the corresponding machine are evaluated with considering the priority of the part. An elimination algorithm which discards the highly deviated bids having obvious differences is implemented at the initial stage of the bid evaluation step. A basic algorithm to control the maximum tardiness value is applied, as well. A simulation test bed is developed in order to implement the time concept into the presented bidding framework. The test bed is mainly based on the Computer Integrated Manufacturing Laboratory (CIMLAB) located in Middle East Technical University, Department of Mechanical Engineering. The developed bidding algorithm is tested under several cases. Results revealed that the proposed bidding framework was quite successful in meeting the objectives. The study is concluded with some specific future work, outlined in the light of the results obtained.

Production lines with unreliable machines have received a great amount of attention in the literature. Especially, two-station systems have mostly been studied because such systems are easier to handle when compared to the longer lines. In literature, longer lines are usually evaluated by a decomposition algorithm, whereby the long line is partitioned into chunks of two-station lines. Decomposition algorithms require intermediate buffer storages of capacity at least two or three. The trends in modern manufacturing practices, on the other hand, such as the Toyota Production System, dictate that intermediate storages be eliminated. Our work studies multi-station lines with no intermediate storage. We develop software to automate the generation of transition probability matrices to allow the analysis of system behavior. The algorithm allows the use of software packages to handle computations and to solve for exact solutions. Long-run behavior is obtained via the algorithm developed in the computational environment MATLAB. The purpose is to analyze the system performance measures such as starvation and blockage times of stations, production rate and work-in-process. In addition, the production rate and the work-in-process measures over failure and repair probabilities are curve-fit to establish simple and useful empirical formulas for lines consisting three, four and five identical stations. Numerical analyses show that the proposed algorithm is effective for exact solutions and the suggested formulas are valid for approximate solutions.

Vendor Managed Inventory (VMI) policy has been widely used in various supply chains due to the benefits such as lower inventory levels and costs of retailer, and less frequent stock outs. In this study, the benefits of VMI policy in a manufacturer-retailer setting are analyzed under three different scenarios (Traditional Decision Making, VMI agreement and Centralized Decision Making). A manufacturer that produces a particular product is considered and that product is sold to a retailer operating under known demand forecasts. Under Traditional Decision Making System, each party is responsible for its own costs. Under VMI, manufacturer controls the replenishment decisions of the retailer and solves a Constrained Two-Echelon Lot Sizing Problem with Backordering. Under Centralized Decision Making, manufacturer and retailer act like merged, the problem under consideration is Two-Echelon Single Item Lot Sizing with Backordering. Through an extensive numerical study, three different scenarios&rsquo / results are compared and the conditions beneficial under VMI are identified. Under VMI, a Lagrangean Relaxation algorithm is proposed to reduce solution time. In terms of computational effort, solution times of proposed algorithm and MIP model are compared.

In this study, we focus on a real life problem that involves a single item which is used in military operations. The items in use fail according to a Poisson process and lead times are deterministic. Four alternative inventory control models are developed. Among these models, a two-echelon system consisting of a depot in the upper and several bases in the lower echelon is operated currently. This system is compared to a single-echelon system that consists of several bases. The comparison reveals the importance of the holding cost incurred for the items intransit between the depot and the base which is ignored in most of the studies in literature. Both the two and single-echelon models are also extended to have repair ability. A continuous-review base-stock policy is used for all models. Exact models are formulated. The results are obtained under various lead time, unit costs and demand parameters. Results of four different settings are compared and the findings are reported.

Thesis (Ph.D.)--Mississippi State University. Department of Industrial and Systems Engineering. / Title from title screen. Includes bibliographical references.

Dissertation submitted in partial fulfilment of the requirements for the degree of Master of Business Administration, Business Studies Unit, Faculty of Commerce, Durban University of Techology, 2007. / Quality improvement is a fundamental and important attribute of a company’s business strategy and competitive positioning. The Durban-based paint factory of Dulux (Pty)Ltd, is the primary manufacturing and distribution site in South Africa. This site has to ensure that the consumers and customers in the target market, are satisfied with the quality of product and service received from the factory. This research focuses on the determination of employee perceptions of quality during 2006 at the paint factory site. In particular, how could these perceptions be effectively used by management as a basis for improving the quality ethic on the site. An improved quality ethic ensures a value- added product and service offer to the target market. The research investigates employee perceptions for various site departments and job grades within the context of several quality themes. Employee perceptions were determined by means of a quantitative survey conducted on the site population using a survey questionnaire. The study shows a primarily positive perception of quality by the employees. The subsequent descriptive and inferential statistical analysis quantifies these perceptions as statistically significant in relation to the research questions that were used in the research. There were some perceptions of quality that highlited potential areas for improvement within the site quality management system and the scope of application. These areas need to be considered by management in order to restore positive perception and support for the quality management system. It is recommended that an annual survey of employee perceptions be conducted by the Quality Assurance department and feedback discussed at the annual quality management review forum. An effective quality improvement and communications strategy can then be determined for implementation. It is also proposed that future research consider conducting a similar study at the service oriented Dulux Alberton site and another survey for the management team at the Durban factory.

The aim of this research was to examine whether and to what extent supply chain management (SCM) officials in the Central District Municipality designed and implemented SCM in a manner that encouraged sound financial management and compliance to SCM legislative requirements in local government. The substantive area of research was the Central District Municipality and its five local municipalities. The researcher used both qualitative and quantitative research designs with semi-structured face-to-face interview questionnaire administered over three months. The sampling population was the Central District Municipality and its local municipalities. The researcher conducted 30 interviews and the research analysis strategy was the grounded theory supported by quantitative presentation of closed ended questions in tables and figures with the use of statistical package for social sciences (SPSS). The findings of the study revealed that Central District Municipality to a certain extent depicted the practice of some of the elements of SCM. SCM implementation is currently at an infancy stage and these municipalities do not fully comply with national treasury circulars and regulations. The municipalities are faced with problems of lack of knowledge, skills and capacity. The study concludes with the development of proposition that need to be tested on SCM implementation and recommendations on how the central district municipality can improve SCM implementation process. / (M.Com.) North-West University, Mafikeng Campus, 2006

In an attempt to reduce costs and improve customer satisfaction, manufacturers have been adopting strategies such as Delayed Product Differentiation (DPD) while managing broader product lines. In this study, first a general framework on DPD is formed in the light of basic articles in the literature. The vanilla box assembly process which is a special form of modular design type of DPD is modeled and analyzed. In the vanilla box assembly process, inventory is stored in a special form of semi-finished products, called vanilla boxes, that can serve more than one final product. We model the vanilla box assembly process considering the costs of inventory and unsatisfied demand under the capacity limitations, stochastic demand and bill of material requirements. We formulate the model as an extensive form of stochastic integer program in which stochastic demand is modeled using a set of demand scenarios each of which is assigned a probability of occurrence. The model is solved as a standard integer programming model that minimizes the expected value of the objective function. The impact of product demand scenarios, common component levels, shortage penalty cost to holding cost ratio levels and capacity restrictions on the total cost and fill rates is studied. We compare the performance of vanilla box assembly process to assemble-to-order process and provide insights on their performances. Computational results indicate that the vanilla box assembly process is a promising alternative to the assemble-to-order process in most of the problem instances.