Scheduling and stability analysis of Cambridge Ring

textMulticlass queueing networks are widely used to model complex manufacturing systems and communications networks. In this dissertation we describe and analyze a multiclass queueing network model known as the Cambridge Ring. As the name suggest this network has a circular topology with unidirectional routing. In many cases the analysis of a stochastic model is a difficult task. For a few special cases of this network we show that all non-idling policies are throughput optimal for this system. One of the major differences between this work and precious literature is that we prove throughput optimality of all non-idling policies, whereas most of the previous work has been on establishing throughput optimality for a specific policy (usually First-In-First-Out). We use a macroscopic technique known as fluid model to identify optimal policies with respect to work in process. In one case we consider, the discrete scheduling policy motivated by the optimal fluid policy is indeed optimal in the discrete network. For the other special case we show by means of a deterministic counterexample that the discrete policy most naturally suggested by the fluid optimal policy may not be optimal for the queueing network. We also formulate the fluid holding cost optimization problem and present its solution for a simple version of the Cambridge Ring. Further we establish that the optimal policy under a class of policies known as "non-ejective" policies may be an idling policy. We use an example of the Cambridge Ring with a single vehicle to show that the optimal policy for this example has to be an idling policy.Operations Research and Industrial Engineerin

Use of network analysis, and fluid and diffusion approximations for stochastic queueing networks to understand flows of referrals and outcomes in community health care

Community services are fundamental in the delivery of health care, providing local care close to or in patient homes. However, planning, managing and evaluating these services can be difficult. One stand out challenge is how these services may be organised to provide coordinated care given their physical distribution, patients using multiple services, and the increasing use of these services by patients with differing needs. This is complicated by a lack of comparable measures for evaluating quality across differing community services. Presented in this thesis is work that I conducted, alongside the North East London Foundation Trust, to understand referrals and the use of outcome data within community services through data visualisation and mathematical modelling. Firstly, I applied several data visualisations, building from a network analysis, to aid the design of a single point of access for referrals into community services - helping to understand patterns of referrals and patient use. Of interest were concurrent uses of services, whether common patterns existed and how multiple referrals occurred over time. This highlighted important dynamics to consider in modelling these services. Secondly, I developed a patient flow model, extending fluid and diffusion approximations of stochastic queueing systems to include complex flow dynamics such as re-entrant patients and the use of multiple services in sequence. Patient health is also incorporated into the model by using states that patients may move between throughout their care, which are used to model the differential impact of care. I also produced novel methods for allocating servers across parallel queues and patient groups. Finally, I developed the concept of ``the flow of outcomes'' - a measure of how individual services contribute to the output of patients in certain health states over time - to provide operational and clinical insight into the performance of a network of services

Analytical Approximations to Predict Performance Measures of Manufacturing Systems with Job Failures and Parallel Processing

Parallel processing is prevalent in many manufacturing and service systems. Many manufactured products are built and assembled from several components fabricated in parallel lines. An example of this manufacturing system configuration is observed at a manufacturing facility equipped to assemble and test web servers. Characteristics of a typical web server assembly line are: multiple products, job circulation, and paralleling processing. The primary objective of this research was to develop analytical approximations to predict performance measures of manufacturing systems with job failures and parallel processing. The analytical formulations extend previous queueing models used in assembly manufacturing systems in that they can handle serial and different configurations of paralleling processing with multiple product classes, and job circulation due to random part failures. In addition, appropriate correction terms via regression analysis were added to the approximations in order to minimize the gap in the error between the analytical approximation and the simulation models. Markovian and general type manufacturing systems, with multiple product classes, job circulation due to failures, and fork and join systems to model parallel processing were studied. In the Markovian and general case, the approximations without correction terms performed quite well for one and two product problem instances. However, it was observed that the flow time error increased as the number of products and net traffic intensity increased. Therefore, correction terms for single and fork-join stations were developed via regression analysis to deal with more than two products. The numerical comparisons showed that the approximations perform remarkably well when the corrections factors were used in the approximations. In general, the average flow time error was reduced from 38.19% to 5.59% in the Markovian case, and from 26.39% to 7.23% in the general case. All the equations stated in the analytical formulations were implemented as a set of Matlab scripts. By using this set, operations managers of web server assembly lines, manufacturing or other service systems with similar characteristics can estimate different system performance measures, and make judicious decisions - especially setting delivery due dates, capacity planning, and bottleneck mitigation, among others

Analysis of buffer allocations in time-dependent and stochastic flow lines

This thesis reviews and classifies the literature on the Buffer Allocation Problem under steady-state conditions and on performance evaluation approaches for queueing systems with time-dependent parameters. Subsequently, new performance evaluation approaches are developed. Finally, a local search algorithm for the derivation of time-dependent buffer allocations is proposed. The algorithm is based on numerically observed monotonicity properties of the system performance in the time-dependent buffer allocations. Numerical examples illustrate that time-dependent buffer allocations represent an adequate way of minimizing the average WIP in the flow line while achieving a desired service level

Application of lean scheduling and production control in non-repetitive manufacturing systems using intelligent agent decision support

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.Lean Manufacturing (LM) is widely accepted as a world-class manufacturing paradigm, its currency and superiority are manifested in numerous recent success stories. Most lean tools including Just-in-Time (JIT) were designed for repetitive serial production systems. This resulted in a substantial stream of research which dismissed a priori the suitability of LM for non-repetitive non-serial job-shops. The extension of LM into non-repetitive production systems is opposed on the basis of the sheer complexity of applying JIT pull production control in non-repetitive systems fabricating a high variety of products. However, the application of LM in job-shops is not unexplored. Studies proposing the extension of leanness into non-repetitive production systems have promoted the modification of pull control mechanisms or reconfiguration of job-shops into cellular manufacturing systems. This thesis sought to address the shortcomings of the aforementioned approaches. The contribution of this thesis to knowledge in the field of production and operations management is threefold: Firstly, a Multi-Agent System (MAS) is designed to directly apply pull production control to a good approximation of a real-life job-shop. The scale and complexity of the developed MAS prove that the application of pull production control in non-repetitive manufacturing systems is challenging, perplex and laborious. Secondly, the thesis examines three pull production control mechanisms namely, Kanban, Base Stock and Constant Work-in-Process (CONWIP) which it enhances so as to prevent system deadlocks, an issue largely unaddressed in the relevant literature. Having successfully tested the transferability of pull production control to non-repetitive manufacturing, the third contribution of this thesis is that it uses experimental and empirical data to examine the impact of pull production control on job-shop performance. The thesis identifies issues resulting from the application of pull control in job-shops which have implications for industry practice and concludes by outlining further research that can be undertaken in this direction

Planning and Routing Algorithms for Multi-Skill Contact Centers

Koole, G.M. [Promotor

\u3ci\u3eThe Conference Proceedings of the 2003 Air Transport Research Society (ATRS) World Conference, Volume 1\u3c/i\u3e

UNOAI Report 03-5https://digitalcommons.unomaha.edu/facultybooks/1131/thumbnail.jp