A multiple channel queueing model under an uncertain environment with multiclass arrivals for supplying demands in a cement industry

In recent years, cement consumption has increased in most Asian countries, including Malaysia. There are many factors which affect the supply of the increasing order demands in the cement industry, such as traffic congestion, logistics, weather and machine breakdowns. These factors hinder smooth and efficient supply, especially during periods of peak congestion at the main gate of the industry where queues occur as a result of inability to keep to the order deadlines. Basic elements, such as arrival and service rates, that cannot be predetermined must be considered under an uncertain environment. Solution approaches including conventional queueing techniques, scheduling models and simulations were unable to formulate the performance measures of the cement queueing system. Hence, a new procedure of fuzzy subset intervals is designed and embedded in a queuing model with the consideration of arrival and service rates. As a result, a multiple channel queueing model with multiclass arrivals, (M1, M2)/G/C/2Pr, under an uncertain environment is developed. The model is able to estimate the performance measures of arrival rates of bulk products for Class One and bag products for Class Two in the cement manufacturing queueing system. For the (M1, M2)/G/C/2Pr fuzzy queueing model, two defuzzification techniques, namely the Parametric Nonlinear Programming and Robust Ranking are used to convert fuzzy queues into crisp queues. This led to three proposed sub-models, which are sub-model 1, MCFQ-2Pr, sub-model 2, MCCQESR-2Pr and sub-model 3, MCCQ-GSR-2Pr. These models provide optimal crisp values for the performance measures. To estimate the performance of the whole system, an additional step is introduced through the TrMF-UF model utilizing a utility factor based on fuzzy subset intervals and the α-cut approach. Consequently, these models help decision-makers deal with order demands under an uncertain environment for the cement manufacturing industry and address the increasing quantities needed in future

Using Hybrid Simulation/Analytical Queueing Networks to Capacitate USAF Air Mobility Command Passenger Terminals

The objective of this study is to model operations at an airport passenger terminal to determine the optimal service capacities at each station given estimated passenger flow patterns and service rates. The central formulation is an open Jackson queueing network that can be applied to any USAF Air Mobility Command (AMC) terminal regardless of passenger type mix and flow data. A complete methodology for analyzing passenger flows and queue performance of a single flight is produced and then embedded in a framework to analyze the same for multiple departing flights. Queueing network analysis (QNA) is used because no special software license or methodological training is required, results are obtained in a spreadsheet model with computational response times that are instantaneous, and data requirements are substantially reduced compared with discrete-event simulation (DES). However, because of the assumptions of QNA, additional research contributions were required. First, arrivals of passengers are time-dependent, not steady-state. Theoretical results for time-dependent queue networks in the literature are limited, so a method for using DES to adjust for arrival time-dependency in QNA is developed. Second, beyond quality of service in the network, a key performance measure is the percentage of passengers who do not clear the system by a fixed time. To populate the QNA mean value system sojourn time, DES is used to develop a generic sojourn time probability distribution. All DES computations have been pre-calculated off-line in this thesis and complete a hybrid DES/QNA analytical model. The model is exercised and validated through analysis of the facility at Hickam AFB, which is currently undergoing redesign. For larger flights, adding a server at the high-utilization queues, namely the USDA inspection and security screening stations, halve system congestion and dramatically increase throughput

Modelling activities in a Critical Care Unit

The Critical Care Unit (CCU) is the sector of the hospital where, as the name suggests, critically ill patients receive treatment. The main aim of this research is to identify and apply suitable Operational Research techniques to model patient flow in the CCU at the University Hospital of Wales, Cardiff. The Operational Research techniques employed in this thesis include queueing theory and simulation. These methods have been utilised previously in the field of healthcare with much success. The thesis begins by considering two aspects of queueing theory, namely batch service queueing theory and batch arrival queueing theory. The latter of these is utilised to model patient flow within the CCU. Although queueing theory may be used as a good approximation to activities in the Unit, it does not incorporate all aspects of real-life. Thus discrete-event simulation is suggested as an alternative approach. Two types of statistical analysis, CART and Regression, are applied to both length of stay and mortality variables. The results from these statistical tests are compiled and investigated in more depth. Finally, a discrete event simulation model is built in Visual Basic for Applications, for Microsoft Excel. This simulation model incorporates many of the complexities of a CCU, such as patient priority and cancellation of scheduled patients if all beds on the Unit are occupied. The model is then used to test various "what-if type" scenarios, including the possibility of funding additional beds, the concept of ring-fencing of beds for different levels of care, and the likely effect of reducing the impact of bed-blocking

Modelling and Optimisation of GSM and UMTS Radio Access Networks

The size and complexity of mobile communication networks have increased in the last years making network management a very complicated task. GSM/EDGE Radio Access Network (GERAN) systems are in a mature state now. Thus, non-optimal performance does not come from typical network start-up problems, but, more likely, from the mismatching between traffic, network or propagation models used for network planning, and their real counterparts. Such differences cause network congestion problems both in signalling and data channels. With the aim of maximising the financial benefits on their mature networks, operators do not solve anymore congestion problems by adding new radio resources, as they usually did. Alternatively, two main strategies can be adopted, a) a better assignment of radio resources through a re-planning approach, and/or b) the automatic configuration (optimisation, in a wide sense) of network parameters. Both techniques aim to adapt the network to the actual traffic and propagation conditions. Moreover, a new heterogenous scenario, where several services and Radio Access Technologies (RATs) coexist in the same area, is now common, causing new unbalanced traffic scenarios and congestion problems. In this thesis, several optimisation and modelling methods are proposed to solve congestion problems in data and signalling channels for single- and multi-RAT scenarios

Entropy Maximisation and Queues With or Without Balking. An investigation into the impact of generalised maximum entropy solutions on the study of queues with or without arrival balking and their applications to congestion management in communication networks.

An investigation into the impact of generalised maximum entropy solutions on the study of queues with or without arrival balking and their applications to congestion management in communication networks Keywords: Queues, Balking, Maximum Entropy (ME) Principle, Global Balance (GB), Queue Length Distribution (QLD), Generalised Geometric (GGeo), Generalised Exponential (GE), Generalised Discrete Half Normal (GdHN), Congestion Management, Packet Dropping Policy (PDP) Generalisations to links between discrete least biased (i.e. maximum entropy (ME)) distribution inferences and Markov chains are conjectured towards the performance modelling, analysis and prediction of general, single server queues with or without arrival balking. New ME solutions, namely the generalised discrete Half Normal (GdHN) and truncated GdHN (GdHNT) distributions are characterised, subject to appropriate mean value constraints, for inferences of stationary discrete state probability distributions. Moreover, a closed form global balance (GB) solution is derived for the queue length distribution (QLD) of the M/GE/1/K queue subject to extended Morse balking, characterised by a Poisson prospective arrival process, i.i.d. generalised exponential (GE) service times and finite capacity, K. In this context, based on comprehensive numerical experimentation, the latter GB solution is conjectured to be a special case of the GdHNT ME distribution. ii Owing to the appropriate operational properties of the M/GE/1/K queue subject to extended Morse balking, this queueing system is applied as an ME performance model of Internet Protocol (IP)-based communication network nodes featuring static or dynamic packet dropping congestion management schemes. A performance evaluation study in terms of the model’s delay is carried out. Subsequently, the QLD’s of the GE/GE/1/K censored queue subject to extended Morse balking under three different composite batch balking and batch blocking policies are solved via the technique of GB. Following comprehensive numerical experimentation, the latter QLD’s are also conjectured to be special cases of the GdHNT. Limitations of this work and open problems which have arisen are included after the conclusion

OR in search for community

This year’s Keynote has a special format. The interest in Community OR has taken the form of a new Special Interest Group that is presently taking shape. To contribute to a better understanding of the variety of interest that is being incorporated, we have invited a number of people to present their ideas as short presentations or pitches. Below you will find an outline of what we have today. These may help to summarise the current thinking and (research) practices in Community OR. The presentations will be followed by a panel discussion. Social Innovation and Community OR Communities are the main addressees for sustainable change and improvement, at least in the European Union. There are some considerable difficulties here, as the cry for policies that are effective in delivering this change is getting stronger and communities are getting better in avoiding being addressed as stooges. At present OR explores contributions to the policy problem (see the new SIG for Social Policy). It is argued that policy should be supportive to community level activities and initiatives, rather than the reverse, if social innovation is to be promoted. Examples are presented. Organising Suppliers: Chain or commune? Economy-based supplier structures are organised under drivers that aim at the alignment of goals and the optimisation of resources available; however, this does not seem to apply to any size of business. Observations on microbusinesses suggest that they do not strive for economic drivers only. Lifestyle, family and other non-economic drivers are also part of their strategic decision making processes. Different snapshots about UK and Mexican microbusinesses are used to illustrate possibilities that supply chains and communities may provide. Community OR ideas are used as a framework for the comparison

Communities and food supply: looking at their intersection

There is an extended opinion that Food Supply Chains (FSCs) create economic value; usually by aligning different actors along the chain. However, for food microproducers, economic value is not necessarily the main driver to engage with FSCs. This opens up the discussion towards how to build FSCs with potential members that do not always recognise practical advantages in working with others. We propose explore previous research done in the area of Community Operational Research (COR) by looking microproducers not as links constituting a chain, where the weakest is removed for the benefit of the rest. We explore if there are benefits from being members from a community (Food Supply Communities, FSComs), where they identify which individual actions contribute to the collective self-construction, and vice versa. To contextualise the discussion, we use the case of a typical UK regional, county-based food marketing group which provides umbrella marketing support for specialist SMEs