Operationalizing Cost-Volume-Profit analysis under uncertainty

Cost-Volume-Profit analysis is a major business planning tool. It is limited by its assumptions about known price and costs. This study uses MAPLE software to operationalize CVP under uncertainty for practical application. Illustrated examples show that the impact of expected selling price and expected variable cost on expected breakeven quantity is more sensitive than the impact of the standard deviations of selling price and variable cost. Specifically, when expected selling price decreases, the expected breakeven quantity increases rapidly. However, as the standard deviations of selling price or variable cost increases, expected breakeven quantity increases at the same rate

MCA4climate: A Practical Framework for Planning Pro-Development Climate Policy

MCA4climate is a major new UNEP initiative providing 1 Introduction practical assistance to governments in preparing their climate change mitigation and adaptation plans and strategies. It aims to help governments, particularly in developing countries, identify policies and measures that are low cost, environmentally effective and consistent with national development goals. It does this by providing a structured approach to assessing and prioritizing climate-policy options, while taking into consideration associated social, economic, environmental and institutional costs and benefits. In doing so, it seeks to counter the widely held perception that tackling climate change is costly, highlight the potential developmental benefits of addressing climate change and encourage action to that end

Minimizing the Cost of Innovative Nuclear Technology Through Flexibility: The Case of a Demonstration Accelerator-Driven Subcritical Reactor Park

Presented is a methodology to analyze the expected Levelised Cost Of Electricity (LCOE) in the face of technology uncertainty for Accelerator-Driven Subcritical Reactors (ADSRs). It shows that flexibility in the design and deployment strategy of an ADSR park demonstrator significantly reduces its expected LCOE. The methodology recognizes in the conceptual design a range of possible technological outcomes for the ADSR accelerator system. It identifies flexibility “on” and “in” the design to modify the future development path in light of such uncertain scenarios. Uncertainty and flexibility are incorporated in the ADSR valuation. The resulting economic assessment is more realistic than typical discounted cash flow analysis that does not consider a range of development outcomes, or the flexibility to change development path

The boomerang returns? Accounting for the impact of uncertainties on the dynamics of remanufacturing systems

Recent years have witnessed companies abandon traditional open-loop supply chain structures in favour of closed-loop variants, in a bid to mitigate environmental impacts and exploit economic opportunities. Central to the closed-loop paradigm is remanufacturing: the restoration of used products to useful life. While this operational model has huge potential to extend product life-cycles, the collection and recovery processes diminish the effectiveness of existing control mechanisms for open-loop systems. We systematically review the literature in the field of closed-loop supply chain dynamics, which explores the time-varying interactions of material and information flows in the different elements of remanufacturing supply chains. We supplement this with further reviews of what we call the three ‘pillars’ of such systems, i.e. forecasting, collection, and inventory and production control. This provides us with an interdisciplinary lens to investigate how a ‘boomerang’ effect (i.e. sale, consumption, and return processes) impacts on the behaviour of the closed-loop system and to understand how it can be controlled. To facilitate this, we contrast closed-loop supply chain dynamics research to the well-developed research in each pillar; explore how different disciplines have accommodated the supply, process, demand, and control uncertainties; and provide insights for future research on the dynamics of remanufacturing systems

2Planning for Contingencies: A Decision-based Approach

A fundamental assumption made by classical AI planners is that there is no uncertainty in the world: the planner has full knowledge of the conditions under which the plan will be executed and the outcome of every action is fully predictable. These planners cannot therefore construct contingency plans, i.e., plans in which different actions are performed in different circumstances. In this paper we discuss some issues that arise in the representation and construction of contingency plans and describe Cassandra, a partial-order contingency planner. Cassandra uses explicit decision-steps that enable the agent executing the plan to decide which plan branch to follow. The decision-steps in a plan result in subgoals to acquire knowledge, which are planned for in the same way as any other subgoals. Cassandra thus distinguishes the process of gathering information from the process of making decisions. The explicit representation of decisions in Cassandra allows a coherent approach to the problems of contingent planning, and provides a solid base for extensions such as the use of different decision-making procedures.Comment: See http://www.jair.org/ for any accompanying file

A philosophical context for methods to estimate origin-destination trip matrices using link counts.

This paper creates a philosophical structure for classifying methods which estimate origin-destination matrices using link counts. It is claimed that the motivation for doing so is to help real-life transport planners use matrix estimation methods effectively, especially in terms of trading-off observational data with prior subjective input (typically referred to as 'professional judgement'). The paper lists a number of applications that require such methods, differentiating between relatively simple and highly complex applications. It is argued that a sound philosophical perspective is particularly important for estimating trip matrices in the latter type of application. As a result of this argument, a classification structure is built up through using concepts of realism, subjectivity, empiricism and rationalism. Emphasis is put on the fact that, in typical transport planning applications, none of these concepts is useful in its extreme form. The structure is then used to make a review of methods for estimating trip matrices using link counts, covering material published over the past 30 years. The paper concludes by making recommendations, both philosophical and methodological, concerning both practical applications and further research