Electricity swing option pricing by stochastic bilevel optimization: A survey and new approaches

We demonstrate how the problem of determining the ask price for electricity swing options can be considered as a stochastic bilevel program with asymmetric information. Unlike as for financial options, there is no way for basing the pricing method on no-arbitrage arguments. Two main situations are analyzed: if the seller has strong market power he/she might be able to maximize his/her utility, while in fully competitive situations he/she will just look for a price which makes profit and has acceptable risk. In both cases the seller has to consider the decision problem of a potential buyer – the valuation problem of determining a fair value for a specific option contract – and anticipate the buyer’s optimal reaction to any proposed strike price. We also discuss some methods for finding numerical solutions of stochastic bilevel problems with a special emphasis on using duality gap penalizations.     

A multi-agent optimization formulation of earthquake disaster prevention and management

Natural earthquake disasters are unprecedented incidents which take many lives as a consequence and cause major damages to lifeline infrastructures. Various agencies in a country are responsible for reducing such adverse impacts within specific budgets. These responsibilities range from before to after the incident, targeting one of the main phases of disaster management (mitigation, preparedness, and response). Use of OR in disaster management and coordination of its phases has been mostly ignored and highly recommended in former reviews. This paper presents a formulation to coordinate three main agencies and proposes a heuristic approach to solve the different introduced sub-problems. The results show an improvement of 7.5–24% when the agencies are coordinated.     

A methodology for supporting strategy implementation based on the VSM: A case study in a Latin-American multi-national

Soft OR tools have increasingly been used to support the strategic development of companies at operational and managerial levels. However, we still lack OR applications that can be useful in dealing with the “implementation gap”, understood as the scarcity of resources available to organizations seeking to align their existing processes and structures with a new strategy. In this paper we contribute to filling that gap, describing an action research case study where we supported strategy implementation in a Latin American multinational corporation through a soft OR methodology. We enhanced the ‘Methodology to support organizational self-transformation’, inspired by the Viable System Model, with substantive improvements in data collection and analyses. Those adjustments became necessary to facilitate second order learning and agreements on required structural changes among a large number of participants. This case study contributes to the soft OR and strategy literature with insights about the promise and constraints of this soft OR methodology to collectively structure complex decisions that support organizational redesign and strategy implementation.     

A perspective on operational research prospects for agriculture

This paper discusses the future of operational research (OR) for the agricultural industries in a broad sense, including horticulture and viticulture during a period of increased pressure on natural resources. The authors use their experience in the field along with published literature, to draw insights into new opportunities for OR, and how the OR community might adapt to realise these opportunities best. Trends in demand for food security and biofuels, the quest for sustainability, information technology (IT), and commercial power create new opportunities to support strategic investment and operations management within both primary production and the related supply chains. To realise such potential, the agricultural OR community needs to improve management of stakeholder relations, interdisciplinary synthesis, and the successful application of OR.     

A semi-oriented radial measure for measuring the efficiency of decision making units with negative data,using DEA

Data Envelopment Analysis (DEA) is a nonparametric method for measuring the efficiency of a set of decision making units such as firms or public sector agencies, first introduced into the operational research and management science literature by Charnes, Cooper, and Rhodes (CCR) [Charnes, A., Cooper, W.W., Rhodes, E., 1978. Measuring the efficiency of decision making units. European Journal of Operational Research 2, 429–444]. The original DEA models were applicable only to technologies characterized by positive inputs/outputs. In subsequent literature there have been various approaches to enable DEA to deal with negative data.     

An Activity-Based Costing decision model for life cycle assessment in green building projects

Carbon emissions are an increasingly important consideration in sustainable environmental development. In the green building industry, green construction cost controls and low-carbon construction methods are considered to be the key barriers encountered. Based on Corporate Social Responsibility (CSR) policy, management of carbon emissions from green building projects contributes to the acquisition of accurate building cost information and to a reduction in the environmental impact of these projects. This study focuses on the CO₂ emission costs and low-carbon construction methods, and proposes a 0–1 mixed integer programming (0–1 MIP) decision model for integrated green building projects, using an Activity-Based Cost (ABC) and life cycle assessment (LCA) approach. The major contributions of this study are as follows: (1) the integrated model can help construction company managers to more accurately understand how to allocate resources and funding for energy saving activities to each green building through appropriate cost drivers; (2) this model provides a pre-construction decision-making tool which will assist management in bidding on environmentally-friendly construction projects; and (3) this study contributes to the innovation operation research (OR) literature, especially in regard to incorporating the life cycle assessment measurement into construction cost management by utilizing a mixed decision model for green building projects.     

Making decisions in the absence of clear facts

Bennis and O’Toole [Bennis, W.G., O’Toole, J., 2005. How business schools lost their way. Harvard Business Review 83, 96–104] have recently argued that decision makers need guidance in ‘making decisions in the absence of clear facts’. As such, decision makers must be able to resourcefully use whatever limited information is available and advantageously portray its implications. Based on recently published theory which directly addresses this requirement, this paper demonstrates, through a practical example, how decision makers can make systemic decisions in situations characterized by extremely limited information and, furthermore, what form such decisions can take. Evidence is provided, therefore, that operational research can effectively address what appears to be a gap in management training.     

The evolution of transformation media in spherical trigonometry in 17th- and 18th-century China,and its relation to “Western learning”

Problems of spherical trigonometry in 17th- and 18th-century China were often reduced to problems in plane trigonometry and then solved by means of the proportionality of corresponding sides of similar right triangles. Nevertheless, in the literature on the history of Chinese mathematics, there is not much discussion on the transformation and reduction of spherical problems to the plane, and how the techniques utilized for such transformations evolved over time. In this article, I investigate the evolution of the transformation media involved. I will show that in the trigonometric treatises by Mei Wending (1633–1721) and Dai Zhen (1724–1777), the authors’ views on Western learning shaped their choices of transformation media, and conversely their choices of transformation media offered support to their views on trigonometry in the debate of Chinese versus Western methods. Based on my analysis, I also propose a reassessment of Dai’s treatise of trigonometry, which was controversial ever since its publication in the 18th century.     

An automated planning engine for biopharmaceutical production

We introduce an optimization-based production planning tool for the biotechnology industry. The industry’s planning problem is unusually challenging because the entire production process is regulated by multiple external agencies – such as the US Food and Drug Administration – representing countries where the biopharmaceutical is to be sold. The model is structured to precisely capture the constraints imposed by current and projected regulatory approvals of processes and facilities, as well as capturing the outcomes of quality testing and processing options, facility capacities and initial status of work-in-process. The result is a supply chain “Planning Engine” that generates capacity-feasible batch processing schedules for each production facility within the biomanufacturing supply chain and an availability schedule for finished product against a known set of demands and regulations. Developing the formulation based on distinct time grids tailored for each facility, planning problems with more than 27,000 boolean variables, more than 130,000 linear variables and more than 80,000 constraints are automatically formulated and solved within a few hours. The Planning Engine’s development and implementation at Bayer Healthcare’s Berkeley, CA manufacturing site is described.     

Pre-emption in resource-constrained project scheduling

The Resource-Constrained Project Scheduling Project (RCPSP), together with some of its extensions, has been widely studied. A fundamental assumption in this basic problem is that activities in progress are non-preemptable. Very little effort has been made to uncover the potential benefits of discrete activity pre-emption, and the papers dealing with this issue have reached the conclusion that it has little effect on project length when constant resource availability levels are defined. In this paper we show how three basic elements of many heuristics for the RCPSP – codification, serial SGS and double justification – can be adapted to deal with interruption. The paper is mainly focussed on problem 1_PRCPSP, a generalization of the RCPSP where a maximum of one interruption per activity is allowed. However, it is also shown how these three elements can be further adapted to deal with more general pre-emptive problems. Computational experiments on the standard j30 and j120 sets support the conclusion that pre-emption does help to decrease project length when compared to the no-interruption case. They also prove the usefulness of the justification in the presence of pre-emption. The justification is a RCPS technique that can be easily incorporated into a wide range of algorithms for the RCPSP, increasing their solution quality – maintaining the number of schedules calculated.     

A technological,organisational, and environmental analysis of decision making methodologies and satisfaction in the context of IT induced business transformations

Although Operational Research (OR) has successfully provided many methodologies to address complex decision problems, in particular based on the rationality principle, there has been too little discussion regarding their limited consideration in IT evaluation practice and associated decision making satisfaction levels in an organisational context. The aim of this paper is to address these issues through providing a current account of diffusion and infusion of OR methodologies in IT decision making practice, and by analysing factors affecting decision making satisfaction from a Technological, Organisational, and Environmental (TOE) framework in the context of IT induced business transformations. We developed a structural equation model and conducted an empirical survey, which supported four out of five developed research hypotheses. Our results show that while Decision Support Systems (DSSs), holistic IT evaluation methods, and management support seem to positively affect individual satisfaction, legislative regulation has an adverse effect. Results also revealed a persistent methodology diffusion and infusion gap. The paper discusses implications in each of these aspects and presents opportunities for future work.     

ASPECTS OF CONSTRUCTION AND PROOF IN A HAND-HELD DYNAMIC GEOMETRY ENVIRONMENT

This paper considers how the use of dynamic geometry software (Cabri II on the Texas TI 92) can contribute to the development of pupils’ ideas of construction and proof. Classroom research is reported involving a group of Year 8 pupils (aged 12 to 13) in a mixed urban comprehensive school in the North of England. Two perspectives are combined in analysing the classroom activities. Socio-culturally, the technology is seen as a mediating tool and intellectual development as a complex, dialectical process. A second perspective considers the elements of proof and concludes that, whilst verification and conviction have an importance, it is in explanation that proof becomes social. This combination may indicate the potential of the technology in supporting the development of ideas of construction and proof.     

Facilitators,decision makers,D.I.Y,users: Is intelligent multicriteria decision support for all feasible or desirable?

Effective software is an essential element of real world multicriteria decision aid (MCDA) and there are many ways in which the incorporation of intelligent support can, and has been shown to, enhance multicriteria decision support (MCDSS). However, there is little discussion in the literature about who is the intended benificiary of the intelligence -who is the intended user of a system? In this paper we pay particular attention to identifying the potential users of Intelligent MCDSSs, to identifying their needs and to how the provision of intelligent support can meet these needs. We examine the benefits to be derived from intelligent support and discuss a number of issues prompted by its provision, in particular the question of whether it is feasible or desirable to cater for all potential users of a system     

Using soft OR principles for collaborative simulation: a case study in the Dutch airline industry

Collaborative simulation is a method to handle problem situations that are technologically and socially complex. It combines discrete event simulation with methods, techniques and tools designed to help groups progress with their problems. Discrete event simulation and group support both appear to have clear promises in embedding soft OR principles, yet also contain limitations. Furthermore, simulation and group support appear to be complementary, balancing each other's limitations. Therefore, the combination of group support and discrete event simulation seems to be a fruitful vehicle for the application of soft OR principles. Through experiences in a case study at the cargo department of a major airline, we examine how collaborative simulation can be applied in practice as problem structuring method. We conclude that collaborative simulation has definite potential as a soft OR technique, but further research is required to speed up different steps of simulation to fully use simulation in interactive decision making sessions with multiple stakeholders.     

Dynamic price competition with discrete customer choices

For many years, dynamic pricing has proven to be an effective tool to increase revenue in the airline and other service industries. Most studies, however, focused on monopolistic models and ignored the fact that nowadays consumers can easily compare prices on the Internet. In this paper, we develop a game-theoretic model to describe real-time dynamic price competition between firms that sell substitutable products. By assuming the real-time inventory levels of all firms are public information, we show the existence of Nash equilibrium. We then discuss how a firm can adapt if it knows only the initial – but not the real-time – inventory levels of its competitors. We compare a firm’s expected revenue under different information structures through numerical experiments.     

Critical rationalism in practice: Strategies to manage subjectivity in OR investigations

The philosophical position referred to as critical rationalism (CR) is potentially important to OR because it holds out the possibility of supporting OR’s claim to offer managers a scientifically ‘rational’ approach. However, as developed by Karl Popper, and subsequently extended by David Miller, CR can only support practice (deciding what to do, how to act) in a very limited way; concentrating on the critical application of deductive logic, the crucial role of subjective judgements in making technical and moral choices are ignored or are at least left underdeveloped. By reflecting on the way that managers, engineers, administrators and other professionals take decisions in practice, three strategies are identified for handling the inevitable subjectivity in practical decision-making. It is argued that these three strategies can be understood as attempts to emulate the scientific process of achieving intersubjective consensus, a process inherent in CR. The perspective developed in the paper provides practitioners with a way of understanding their clients’ approach to decision-making and holds out the possibility of making coherent the claim that they are offering advice on how to apply a scientific approach to decision-making; it presents academics with some philosophical challenges and some new avenues for research.     

Applying stochastic goal programming: A case study on water use planning

A decision support model to help public water agencies allocate surface water among farmers and authorize the use of groundwater for irrigation (especially in Mediterranean dry regions) is developed. This is a stochastic goal programming approach with two goals, the first concerning farm management while the other concerns environmental impact. Targets for both goals are established by the agency. This model yields three reduction factors to decide the different reductions in available surface water, standard groundwater and complementary groundwater that the agency should grant/authorize for irrigation, this depending on if it is a dry or wet year. In drought periods, the model recommends using more groundwater (in percentage) than in wet periods. A case study using year-to-year statistical information on available water over the period 1941–2005 is developed through numerical tables. A step-by-step computational process is presented in detail.     

A graph-theoretic perspective on the links-to-concepts ratio expected in cognitive maps

Strategic options development and analysis (SODA) has maintained that it expects a links-to-concepts ratio of 1.15–1.20 in cognitive maps. This expectation is investigated from a graph-theoretic perspective in order to highlight two issues that the SODA literature has not mentioned. First, the ratio is impossible to achieve in tree-structured maps. Second, adherence to the expectation can result in minimally connected maps. Both issues are discussed with examples and calculations, and a conclusion is drawn that graph theory is a potentially rich, yet relatively untapped, source of insights for not only SODA, but for soft OR and systems thinking in general.     

Emergency response in natural disaster management: Allocation and scheduling of rescue units

Natural disasters, such as earthquakes, tsunamis and hurricanes, cause tremendous harm each year. In order to reduce casualties and economic losses during the response phase, rescue units must be allocated and scheduled efficiently. As this problem is one of the key issues in emergency response and has been addressed only rarely in literature, this paper develops a corresponding decision support model that minimizes the sum of completion times of incidents weighted by their severity. The presented problem is a generalization of the parallel-machine scheduling problem with unrelated machines, non-batch sequence-dependent setup times and a weighted sum of completion times – thus, it is NP-hard. Using literature on scheduling and routing, we propose and computationally compare several heuristics, including a Monte Carlo-based heuristic, the joint application of 8 construction heuristics and 5 improvement heuristics, and GRASP metaheuristics. Our results show that problem instances (with up to 40 incidents and 40 rescue units) can be solved in less than a second, with results being at most 10.9% up to 33.9% higher than optimal values. Compared to current best practice solutions, the overall harm can be reduced by up to 81.8%.     

On the convergence of Newton's method for a class of nonsmooth operators

We provide an analog of the Newton–Kantorovich theorem for a certain class of nonsmooth operators. This class includes smooth operators as well as nonsmooth reformulations of variational inequalities. It turns out that under weaker hypotheses we can provide under the same computational cost over earlier works [S.M. Robinson, Newton's method for a class of nonsmooth functions, Set-Valued Anal. 2 (1994) 291–305] a semilocal convergence analysis with the following advantages: finer error bounds on the distances involved and a more precise information on the location of the solution. In the local case not examined in [S.M. Robinson, Newton's method for a class of nonsmooth functions, Set-Valued Anal. 2 (1994) 291–305] we can show how to enlarge the radius of convergence and also obtain finer error estimates. Numerical examples are also provided to show that in the semilocal case our results can apply where others [S.M. Robinson, Newton's method for a class of nonsmooth functions, Set-Valued Anal. 2 (1994) 291–305] fail, whereas in the local case we can obtain a larger radius of convergence than before [S.M. Robinson, Newton's method for a class of nonsmooth functions, Set-Valued Anal. 2 (1994) 291–305].