Multi-site capacity planning and business optimisation for process industries.

Changing market conditions, volatile customer demand, intense competition and tightness of capital are some of the primary characteristics of the global economy that affect process industries nowadays. The main objective of the thesis is to facilitate business decision-making in today's increasingly complex and highly uncertain market environment by applying mathematical programming techniques for multi-site capacity planning and business optimisation in process industries. In the first part of the thesis, the problem of multi-site capacity planning under uncertainty in the pharmaceutical industry is addressed. A comprehensive two-stage, multi-scenario mixed-integer linear programming (MILP) model is proposed able to determine an optimal product portfolio and multi-site investment plan in the face of clinical trials uncertainty. A hierarchical algorithm is also developed in order to reduce the computational effort needed for the solution of the resulting large-scale MILP model. The applicability of the proposed solution methodology is demonstrated by a number of illustrative examples. The second part addresses the problem of business optimisation for customer demand management in process industries. A customer demand forecasting approach is developed based on support vector regression analysis. The proposed three-step algorithm is able to extract the underlying customer demand patterns from historical sales data and derive an accurate forecast as demonstrated through a number of illustrative examples. An active demand management approach for close substitute products is also developed based on price optimisation. The proposed methodology is able to determine optimal pricing policies as well as output levels, while taking into consideration manufacturing costs, resource availability, customer demand elasticity, outsourcing and market competition. An iterative algorithm is developed able to determine Nash equilibrium in prices for competing companies as demonstrated by the illustrative examples

Tariff-Rate Quotas : Difficult to model or plain simple?

The difficulty of reliably and accurately incorporating tariffrate quotas (TRQs) into trade models has received a lot of attention in recent years. As a result of the Uruguay Round of GATT negotiations, TRQs replaced an assortment of tariff and nontariff instruments in an effort to standardise trade barriers, and facilitate their future liberalisation. Understanding the nuances of TRQs is now particularly crucial for New Zealand because of the preferential access arrangements that New Zealand has for a number of products in highly protected markets such as the European Union, Japan, and the United States. It has been argued that TRQs are complex instruments and are difficult to model because for any trade flow between two countries, one of three regimes may be applicable : 1. The import quota may not be binding and the within-quota tariff applies; 2. The quota may be binding, the within-quota tariff applies, and a quota rent is created; or 3. Trade occurs over and above the quota, in which case an over-quota tariff applies (although, even in this regime, someone is still able to collect the quota rent on within-quota trade). But even this characterisation, which many claim is too complex to model, is a major simplification of reality. Bilateral preferences are ubiquitous, and such preferences are usually included in the determination of multilateral market access quotas. It is usual, therefore, that the TRQ instrument has several tiers to the quota schedule, plus a number of within and over-quota tariff rates applicable on either a bilateral or a multilateral basis. Further trade liberalisation creates something of a dilemma for New Zealand. Any decrease in over-quota tariffs and/or increase in quota levels potentially reduces the value of quota rents, many of which accrue to New Zealand due to the bilateral preferences. It is important, therefore, that New Zealand trade negotiators understand how much additional trade is required to offset the loss of New Zealands quota rents. Modelling trade in the presence of TRQs is the only way to ascertain this knowledge. The purpose of this paper is to show that complex TRQs can be modelled very easily and precisely. The only catch is that the model must be formulated as a complementarity problem rather than the more conventional linear or nonlinear optimisation problem. The concept will be demonstrated using a simple 3-region, single commodity spatial price equilibrium model of trade.Tariff-rate quota, trade modelling, mathematical programming, complementarity

Cost effectiveness of bio-ethanol to reduce carbon dioxide emissions in Greece

The purpose of this study is to evaluate ethanol cost- effectiveness with regards to carbon dioxide emissions. Actually, bio-fuel production is only viable thanks to the tax credit policy resulting in economic ‘deadweight’ loss. The environmental performance is assessed under the Life Cycle Assessment (LCA) framework. Economic burden to society to support the activity divided by avoided CO2 equivalent emissions indicates the bio-ethanol cost effectiveness. Agricultural feedstock supply that comprises of sugarbeets, grains and industrial processing sub-models are articulated in a regional sector model. The maximization of total welfare determines optimal crop mix for farmers and the best configurations for industry. This is illustrated for bio-ethanol produced by the ex-sugar industry in Thessaly, Greece. Life cycle activity analysis showed that, at the optimum, CO2 emission is reduced between 1 and 1.5 t of carbon dioxide equivalent per ton of ethanol. The unitary cost falls in the range of 100 to 250 euro per ton of CO2 and it is remarkably dependent on the agricultural policy scenario.Cost effectiveness, ethanol, mathematical programming, life cycle assessment, greenhouse gases

Global supply chains of high value low volume products

Imperial Users onl

The relevance of index funds for pension investment in equities

The rise of index funds over the past 25 years has been a remarkable phenomenon. The traditional rationale for the success of index funds is market efficiency, net of transaction costs. The authors also focus on the role of agency conflicts between fund managers and investors, which are hard to resolve, given the low power of statistical tests of performance. Most of the empirical evidence about the superiority of index funds comes from the United States. The authors discuss issues associated with the application of index funds in developing countries, as well as policy issues in the financial sector that affect the enabling market infrastructure for index funds. They also apply these ideas to thinking about the relevance of index funds for pension investment. The equity premium provides powerful motivation for equity investment by pension funds. Index funds make it possible to sidestep the complexities of forming contracts and monitoring institutions to govern fund managers. In developing countries that seek to use index funds in pension investment, there are avenues through which policymakers can make index funds more viable. In many countries there are significant avenues for improving construction of the market index as well as market mechanisms used in the equity market.Agricultural Knowledge&Information Systems,Payment Systems&Infrastructure,Economic Theory&Research,Markets and Market Access,Access to Markets

Opportunities for Dutch Biorefineries

Deze Roadmap Bioraffinage beschrijft een aantal mogelijke routes naar de ontwikkeling en implementatie van een bioraffinage-gerelateerde Bio-based Economy in Nederland. De Roadmap combineert korte- en middellange termijn mogelijkheden (commerciële implementatie, demonstratie plants, pilot plants en gerelateerd toegepast onderzoek) met strategisch onderzoek voor de langere termijn. Tevens zijn vier z.g. Moonshots uitgewerkt, als voorziene bioraffinagestrategieën met een grote potentie voor de Nederlandse economi

A Holistic Approach to Sustainability Analysis of Industrial Networks

The aim of this thesis is to support the evaluation of sustainable development strategies for industrial networks in the context of industrial ecology (IE). Industrial networks are a group of units which carry out, or contribute to, industrial activity, and are connected by material and energy flows, but also capital and information exchanges. The components of an industrial network encompass resource extraction, processing and refining, forming and assembly, use, disposal, as well as recycling and reprocessing. The motivation behind this research is the realisation that much of the current environmental system analysis focus within IE lacks a structured approach to considering: • system environment • dynamic nature of the system and its environment • economic and social impacts • the effect of uncertainty on analysis outcomes. It is argued in this thesis that current environmental analysis approaches used in IE can be improved in their capacity to capture the complexity of industrial systems, with the objective of promoting sustainable development. While IE emphasises the benefit of a systems approach to identifying environmental strategies in industry, analysis tools have to date not engaged extensively with important aspects such as the influence of system environment and dynamics on the viability of an environmental strategy, or with the economic or social impacts of industrial system development, which are equally important for sustainable development. Nor is the assessment of the effect of uncertainty on analysis outcomes an integral part of environmental analysis tools in IE. This is particularly significant when, in fact, the degree of uncertainty in assumptions and data used increases with the scope, and therefore the abstraction, of the system under consideration. IE will have to engage with the network and contextual complexities to a greater degree if it is to evolve from a concept to the application of its principles in practice. The main contribution of this thesis is therefore the development of a structured approach to analysing industrial networks for the purpose of identifying strategies to encourage sustainable development, while accounting for the complexity of the underlying system as well as the problem context. This analysis is intended to allow the identification of preferred network development pathways and to test the effectiveness of sustainable development strategies. A top-down, prescriptive approach is adopted for this purpose. This approach is chosen as the industrial network analysis is intended to identify how a network should develop, rather than focusing on how it could develop. Industrial networks are systems which are complex in both their structure and behaviour. This thesis also delivers a characterisation of these networks, which serves two purposes – quantifying key elements of structure and behaviour; and using this information to build a foundation for subsequent industrial network analysis. The value of such an approach can be seen in the following example. With a detailed understanding of individual network characteristics, both separately and collectively, it is possible to determine the source of issues, the means available to address them, any barriers that might exist, and the consequences of implementing any strategic interventions. The analysis approach proposed in this thesis is based on multi-criteria decisions analysis (MCDA), which, as a process, combines initial problem structuring and subsequent quantitative analysis stages. The tools employed within MCDA have been employed variously around considerations of sustainable development. Their value in this thesis is their integration within a rigorous analytical framework. Rigorous problem structuring is attractive as it helps elucidate the complexities of the system and its environment and is, by definition, designed to deal with multiple environmental social and economic criteria that would have to be considered to promote sustainable development. For the quantitative analysis, the industrial network analysis draws from existing analysis tools in IE, but predominately from other systems research disciplines, such as process systems engineering (PSE) and supply chain management (SCM). These fields, due to their maturity and practical focus, have invested a lot of research into system design and strategic planning, capturing system dynamics and uncertainty to ensure, within selected system constraints, that a proposed system or changes to a system are viable, and that the system is capable of achieving the stated objectives. Both PSE and SCM rely heavily on optimisation for system design and planning, and achieve good results with it as an analytical tool. The similarity between industrial networks and process systems / supply chains, suggests that an optimisation platform, specifically multi-objective dynamic optimisation, could be employed fruitfully for the analysis of industrial networks. This is the approach taken in this thesis. It is consistent with the “top down” approach advocated previously, which is deemed preferable for the identification and implementation analysis of strategic interventions. This enables the determination of a structure (design) that is “best” able to operate under future conditions (planning) with respect to the chosen sustainable development objectives. However, an analysis is only ever as good as its underlying data and assumptions. The complexity and scope of the industrial network and the challenge of articulating sustainable development target(s) give rise to significant uncertainties. For this reason a framework is developed within this thesis that integrates uncertainty analysis into the overall approach, to obtain insight into the robustness of the analysis results. Quantifying all the uncertainties in an industrial network model can be a daunting task for a modeller, and a decision-maker can be confused by modelling results. Means are therefore suggested to reduce the set of uncertainties that have to be engaged with, by identifying those which impact critically on model outcomes. However, even if uncertainty cannot be reduced, and the implementation of any strategy retains a degree of risk, the uncertainty analysis has the benefit that it forces an analyst to engage in more detail with the network in question, and to be more critical of the underlying assumptions. The analysis approach is applied to two case studies in this thesis: one deals with waste avoidance in an existing wood-products network in a large urban metropolis; the other with the potential for renewable energy generation in a developing economy. Together, these case studies provide a rich tableau within which to demonstrate the full features of the industrial network analysis. These case studies highlight how the context within which the relevant industrial network functions influences greatly the evolution of the network over time; how uncertainty is managed; and what strategies are preferred in each case in order to enhance the contribution of each network to sustainable development. This thesis makes an intellectual contribution in the following areas: • the characterisation of industrial networks to highlight sources of environmental issues, role the characteristics (could) play in the identification of (preferred) sustainable development strategies, and the need to explicitly consider these in a systems analysis. • the synthesis, adaptation and application of existing tools to fulfil the need for analysis tools in IE that can handle both contextual and system complexity, and address the above mentioned issues of lacking consideration of o system environment o dynamic nature of the system and its environment o economic and social impacts o the effect of uncertainty on analysis outcomes. • the development and demonstration of an industrial network analysis approach that o is flexible enough to model any industrial network at the inter-firm level, regardless of form and configuration of materials and products circulated, and depending on the existing network and the proposed strategies. o is able to encompass a wide range of environmental strategies, either individually or in combination depending on what best suits the situation, rather than focusing on any strategy in particular. o ensures long term viability of strategies, rather than short term solutions delivering incremental improvement. • the development of a comprehensive approach to capturing and assessing the effect of uncertainty on solution robustness for industrial network analysis, including the screening to determine the most important parameters, considering valuation and technical uncertainties, including future uncertainty. The industrial network analysis approach presented in this thesis looks more to how a network should develop (according to a set of sustainable development objectives), rather than how it may in actual fact develop. Consequently, the influence of agent interests and behaviour is not considered explicitly. This may be construed as a limitation of the industrial analysis approach. However, it is argued that the “top down” modelling approach favoured here is useful at a policy-making level. Here, for example, government instrumentalities, trade organisations and industry groupings, non-government organisations and community-based organisations are likely to be interested more in the performance of the network as a whole, rather than (necessarily) following the behaviour of individual agents within the network. Future work could well entertain the prospect of a mixed approach, in which the top-down approach of this thesis is complemented by a “bottom-up”, agent-based analysis. In this manner, it would be possible to give an indication of how attainable the identified industrial network development pathways are. Furthermore, the use of government incentives can be explored to assess if network development could approach the preferred development pathway which is identified using the methodology and results articulated in this thesis