Shipment consolidation is a logistics strategy whereby many small shipments are combined into a few larger loads. The economies of scale achieved by shipment consolidation help in reducing the transportation costs and improving the utilization of logistics resources. The fundamental questions about shipment consolidation are i) to how large a size should the consolidated loads be allowed to accumulate? And ii) when is the best time to dispatch such loads? The answers to these questions lie in the set of decision rules known as shipment consolidation policies. A number of studies have been done in an attempt to find the optimal consolidation policy. However, these studies are restricted to only a few types of consolidation policies and are constrained by the input parameters, mainly the order arrival process and the order weight distribution. Some results on the optimal policy parameters have been obtained, but they are limited to a couple of specific types of policies. No comprehensive method has yet been developed which allows the evaluation of different types of consolidation policies in general, and permits a comparison of their performance levels. Our goal in this thesis is to develop such a method and use it to evaluate a variety of instances of shipment consolidation problem and policies. In order to achieve that goal, we will venture to use matrix-analytic methods to model and solve the shipment consolidation problem. The main advantage of applying such methods is that they can help us create a more versatile and accurate model while keeping the difficulties of computational procedures in check. More specifically, we employ a discrete batch Markovian arrival process (BMAP) to model the weight-arrival process, and for some special cases, we use phase-type (PH) distributions to represent order weights. Then we model a dispatch policy by a discrete monotonic function, and construct a discrete time Markov chain for the shipment consolidation process. Borrowing an idea from matrix-analytic methods, we develop an efficient algorithm for computing the steady state distribution of the Markov chain and various performance measures such as i) the mean accumulated weight per load, ii) the average dispatch interval and iii) the average delay per order. Lastly, after specifying the cost structures, we will compute the expected long-run cost per unit time for both the private carriage and common carriage cases.

This thesis explores three consolidation problems derived from the daily operations of major international airfreight forwarders. First, we study the freight forwarder's unsplittable shipment planning problem in an airfreight forwarding network where a set of cargo shipments have to be transported to given destinations. We provide mixed integer programming formulations that use piecewise-linear cargo rates and account for volume and weight constraints, flight departure/arrival times, as well as shipment-ready times. After exploring the solution of such models using CPLEX, we devise two solution methodologies to handle large problem sizes. The first is based on Lagrangian relaxation, where the problems decompose into a set of knapsack problems and a set of network flow problems. The second is a local branching heuristic that combines branching ideas and local search. The two approaches show promising results in providing good quality heuristic solutions within reasonable computational times, for difficult and large shipment consolidation problems. Second, we further explore the freight forwarder's shipment planning problem with a different type of discount structure - the system-wide discount. The forwarder's cost associated with one flight depends not only on the quantity of freight assigned to that flight, but also on the total freight assigned to other flights operated by the same carrier. We propose a multi-commodity flow formulation that takes shipment volume and over-declaration into account, and solve it through a Lagrangian relaxation approach. We also model the "double-discount" scheme that incorporates both the common flight-leg discount (the one used in the unsplittable shipment problem) and the system-wide discount offered by cargo airlines. Finally, we focus on palletized loading using unit loading devices (ULDs) with pivots, which is different from what we assumed in the previous two research problems. In the international air cargo business, shipments are usually consolidated into containers; those are the ULDs. A ULD is charged depending on whether the total weight exceeds a certain threshold, called the pivot weight. Shipments are charged the under-pivot rate up to the pivot weight. Additional weight is charged at the over-pivot rate. This scheme is adopted for safety reasons to avoid the ULD overloading. We propose three solution methodologies for the air-cargo consolidation problem under the pivot-weight (ACPW), namely: an exact solution approach based on branch-and-price, a best fit decreasing loading heuristic, and an extended local branching. We found superior computational performance with a combination of the multi-level variables and a relaxation-induced neighborhood search for local branching.

Mobile phones have evolved from being devices just to make phone calls to become smartphones with added capabilities like surfing the network. Wireless communication has played a very important role in the evolution of smartphones. The work in this thesis aims to study the potential to reduce the energy consumption of the 3G communications by using a hybrid architecture. An idea first presented in the paper by Vergara and Nadjm-Tehrani [1]. This architecture consists of a group of nodes that communicate using WiFi or Bluetooth to forward their traffic using one node's 3G interface. In this thesis the named energy sharing scheme is implemented on Android mobile devices and experiments have been performed using a number of realistic traces to assess achievable gains and the energy footprint of the scheme itself. Even though communication technologies, screen features, multimedia capabilities, or processing power have been taken to the highest level, phones' batteries have not improved at the same speed. Nowadays battery lifetime has become a major issue with respect to cellular communication. With 3G communications Internet connection anytime and anywhere is provided to the terminals but this technology is optimized for peak performance whereas in underutilization it wastes a lot of energy. This makes it a big black hole from power consumption point of view when transmitting small amounts of data.

No description available.

Thesis (DBA(DoctorateofBusinessAdministration))--University of South Australia, 2007.

There are substantial bodies of literature that advance theory about why Merger and Acquisition (M and A) candidates are found to be unattractive, why negotiations aren???t concluded and why the benefits of companies that are acquired are not realized. Little, if any, research identifies why M and A opportunities are not pursued in the period after candidates are analysed and found to be attractive but before negotiations begin. This study addresses this period by developing a theoretical framework of the variables that intervene to reverse decisions to pursue apparently attractive candidates before negotiations begin and which, in doing so, result in missed opportunities. The study is informed primarily by the Strategic Management content literature (Ansoff, 1965, Porter, 1980) but draws from the strategy process literature (Huff and Reger, 1987) including streams in Strategic Decision Making (SDM) (Papadakis and Barwise, 1998, Schwenck, 1995). The framework is developed using a multiple-case study method. This choice was dictated by the study???s theory building objective, the nature of the research questions ??? that is, what variables influence decisions and how? ??? and the lack of an existing theoretical foundation on which to build. The sample consisted of 37 decisions reversals made by 27 firms in Australia, Europe and the USA. The results suggest that there are three major categories of variables that stop acquirers from pursuing potentially attractive acquisition candidates. These are related to the acquirers???: ??? Strategy and objectives: For example, whether there is a change in strategy or objectives, or either or both are poorly understood and agreed between organizational levels or units; ??? Organizational functional resources: For example, whether constraints on appropriate knowledge and skill sets develop or are perceived to be likely to develop during the post-evaluation period; ??? Other financial factors: For example, whether a shortage of funds develops. Twelve individual variables are identified. Ten of these appear to be consistent with factors that Ansoff and colleagues (1971) associate with post-acquisition failure although variable definitions are not always comparable. Poor management of the variables thus appears to have the potential to expose acquirers to two different but important vulnerabilities. First, potentially attractive M and A opportunities may be forgone if the variables are operative in the post-evaluation ??? pre-negotiation period; second, if they don???t become operative until after the acquisition is consummated, the benefits of attractive companies that are acquired may not be realized. This study???s most important contribution is to the theoretically diverse base of acquisition performance literature which, to-date, tends to examine phases in the M and A decision making process before or after the focal period of this study. It also illustrates the use of a general multi-theoretic model of Strategic Decision Making (Rajagopolan, et al., 1993, 1998) exclusively in the M and A domain, a domain whose decisions are worthy of study in their own right. Finally, it provides insights into a new set of factors subject to control that managers may take into account in their acquisition planning.

For at least thirty years urban growth management policies in Australian cities have focused on increasing residential densities as a method of addressing environmental issues. This view has been supported by a number of researchers who hypothesise that to achieve reductions in transport emissions individuals need to be encouraged to use public transport, and the most appropriate method of increasing public transport use occurs predominately from building residential areas at high densities around public transport nodes. This notion is integral to recent urban growth management policies in Sydney, which have sought to increase residential densities under the rubric of urban consolidation. There are a number of researchers who have promoted the benefit of increasing urban densities as a way of increasing public transport use. In Australia, the most cited research in this area is that of Newman and Kenworthy. Nonetheless, there are a number of commentators who have criticised the emphasis of density in increasing public transport use. These commentators assert that factors other than density, particularly socio-economic factors, are more important in influencing public transport use. Nevertheless, a major gap within this concept is that the research is conducted at the macro-level with minimal analysis at the meso or micro level. This thesis attempts to fill a gap in our knowledge by assessing the relationship between urban density and public transport use, particularly trains, at the macro, meso and micro level. The analyses used data across the Sydney metropolitan area and by geographical location to assess the implications of the density-public transport debate, and its articulation in urban consolidation policies. Such an analysis also has implications for other Australian cities who have promoted urban consolidation. The study concludes that residential density is not as important as socio-economic factors in influencing one form of public transport use, namely trains. Variables such as car ownership, country of origin, housing tenure, and the type and location of employment are more important in influencing train use than density. The study concludes that at the macro level the notion of increasing densities increases public transport use is plausible, yet at the micro level the relationship between high density housing and public transport use (in this case train use) is more complex. This suggests that the promotion of urban consolidation policies as a means to increase public transport use needs to be re-assessed. Importantly, there is still much research to be conducted to fully comprehend the relationships between housing and transport in order to better inform urban growth management policies in cities, including Sydney.

For at least thirty years urban growth management policies in Australian cities have focused on increasing residential densities as a method of addressing environmental issues. This view has been supported by a number of researchers who hypothesise that to achieve reductions in transport emissions individuals need to be encouraged to use public transport, and the most appropriate method of increasing public transport use occurs predominately from building residential areas at high densities around public transport nodes. This notion is integral to recent urban growth management policies in Sydney, which have sought to increase residential densities under the rubric of urban consolidation. There are a number of researchers who have promoted the benefit of increasing urban densities as a way of increasing public transport use. In Australia, the most cited research in this area is that of Newman and Kenworthy. Nonetheless, there are a number of commentators who have criticised the emphasis of density in increasing public transport use. These commentators assert that factors other than density, particularly socio-economic factors, are more important in influencing public transport use. Nevertheless, a major gap within this concept is that the research is conducted at the macro-level with minimal analysis at the meso or micro level. This thesis attempts to fill a gap in our knowledge by assessing the relationship between urban density and public transport use, particularly trains, at the macro, meso and micro level. The analyses used data across the Sydney metropolitan area and by geographical location to assess the implications of the density-public transport debate, and its articulation in urban consolidation policies. Such an analysis also has implications for other Australian cities who have promoted urban consolidation. The study concludes that residential density is not as important as socio-economic factors in influencing one form of public transport use, namely trains. Variables such as car ownership, country of origin, housing tenure, and the type and location of employment are more important in influencing train use than density. The study concludes that at the macro level the notion of increasing densities increases public transport use is plausible, yet at the micro level the relationship between high density housing and public transport use (in this case train use) is more complex. This suggests that the promotion of urban consolidation policies as a means to increase public transport use needs to be re-assessed. Importantly, there is still much research to be conducted to fully comprehend the relationships between housing and transport in order to better inform urban growth management policies in cities, including Sydney.

Thesis (Ph. D.)--Virginia Polytechnic Institute and State University, 1990. / Vita. Abstract. Includes bibliographical references (leaves 147-159). Also available via the Internet.

Thesis (LLM)--University of Stellenbosch, 2007. / Bibliography. Also available via the Internet.