Horizon Setting Research Articles

A Generalized Dynamic Discrete Choice Model for Green Vehicle Adoption

Abstract: Much is happening in the automotive industry and new models are in the market or are expected to be available soon. At the same time, environmental awareness, new regulations for increased fuel efficiency, and the need to diminish greenhouse gas emissions make small vehicles and alternative fuel vehicles more competitive. As a consequence, vehicle characteristics and consumer decisions will change rapidly in the short and medium run. Accounting for the dynamic of the problem is important to correctly forecast green vehicle acceptance and to evaluate eco-friendly policies. This paper proposes a generalized dynamic discrete choice approach that models purchase behavior and forecasts future preferences in a finite time horizon setting. The framework allows one-time purchases, repeated purchases, univariate and multivariate diffusion processes that capture the evolution of vehicle characteristics and dynamics in the market conditions. The models proposed are estimated using stated preference data collected in Maryland. Results show that the formulation with repeated purchases successfully captures changes in the market shares, and that the multivariate diffusion process adopted to model the evolution of fuel prices further improves both model fit and the ability to recover peaks in demand. The estimated coefficients have been applied to test different policy scenarios, including changes in fuel prices, vehicle purchase prices, and improvements of car characteristics. These policies have a high impact on the adoption of electric cars and on their diffusion in the marketplace.

On Monotone Recursive Preferences

We explore the set of preferences defined over temporal lotteries in an infinite horizon setting. We provide utility representations for all preferences that are both recursive and monotone. Our results indicate that the class of monotone recursive preferences includes Uzawa–Epstein preferences and risk-sensitive preferences, but leaves aside several of the recursive models suggested by Epstein and Zin (1989) and Weil (1990). Our representation result is derived in great generality using Lundberg's (1982, 1985) work on functional equations.

Infinite horizon optimal policy for an inventory system with two types of product sharing common hardware platforms

We consider a periodic review inventory system and present its optimal policy in the infinite horizon setting. The optimal inventory policy that maximizes the infinite horizon expected discounted profit for the model is analytically obtained by relating to the finite horizon setting using results from variational analysis. Results are provided that elucidate the operations of the inventory system in the long run.

The temporal aspects of the evidence-based influence maximization on social networks

The influence maximization problem selects a set of seeds to initiate an optimal cascade of decisions. This paper uses parallel cascade evidence-based diffusion modelling, which views influence as a consequence of the evidence exchange between the connected actors, to investigate the temporal aspects of the social cascade propagation and effective time horizon for long-term campaign planning. Mixed-integer programming is used to explore the optimal timing of evidence injection and the ensuing network behaviour. The paper defines the notion of mid-term and long-term cascade stability and analyses the dynamics of social cascades for varied evidence discount factor values. This exploration reveals that the time horizon setting affects the optimal placement of seeds in a given problem and, hence, has to be set in a way to reflect the decision-maker's short-term or long-term goals. A Cplex-based heuristic algorithm is developed to iteratively find such a preferable cascade stability time horizon. Moreover, a conducted fractional factorial experiment reveals that the forgetfulness effect and the presence of competition significantly affect the cascade persistence. Somewhat counter-intuitively, it is discovered that a strong positive evidence can become more persistent (long-lasting) in the presence of weak opposing evidence.

A simple framework for the axiomatization of exponential and quasi-hyperbolic discounting

The main goal of this paper is to investigate which normative requirements, or axioms, lead to exponential and quasi-hyperbolic forms of discounting. Exponential discounting has a well-established axiomatic foundation originally developed by Koopmans (1960, 1972) and Koopmans et al. (1964) with subsequent contributions by several other authors, including Bleichrodt et al. (2008). The papers by Hayashi (2003) and Olea and Strzalecki (2014) axiomatize quasi-hyperbolic discounting. The main contribution of this paper is to provide an alternative foundation for exponential and quasi-hyperbolic discounting, with simple, transparent axioms and relatively straightforward proofs. Using techniques by Fishburn (1982) and Harvey (1986), we show that Anscombe and Aumann's (1963) version of Subjective Expected Utility theory can be readily adapted to axiomatize the aforementioned types of discounting, in both finite and infinite horizon settings.

On Monotone Recursive Preferences

We explore the set of preferences defined over temporal lotteries in an infinite horizon setting. We provide utility representations for all preferences that are both recursive and monotone. Our results indicate that the class of monotone recursive preferences includes Uzawa and risk-sensitive preferences, but leaves aside several of the recursive models suggested by Epstein and Zin (1989). Our representation result is derived in great generality using Lundberg (1982, 1985)'s work on functional equations.

What is the Minor Standstill of the Moon?

2014–2015 was the period of the minor standstill of the Moon. Archaeoastronomy has shown that many prehistoric monuments in northwest Europe have horizon alignments on the Sun’s solstices and the Moon’s standstills (North 1996; Ruggles 1999). These are horizon range properties of the risings and settings of the Sun and the Moon. In northern latitudes, at summer solstice, the Sun rises in the northeast and sets in the northwest, while at winter solstice, the Sun rises in the southeast and sets in the southwest (Figure 1). For a given latitude and horizon elevation, the horizon positions for these solar events are fixed.1 The unaided human eye cannot detect any change in its horizon rise or set position during a solstice for three days before or after the day of the solstice (Ruggles 1999, 25) and, for the monument builders of prehistoric Europe, each solstice is therefore a seven-day event. After the week of the summer solstice, the Sun begins to rise and set further south on the horizon. Pendulum-like, these horizon positions are slow to change close to the solstices and fastest in mid-swing during the equinoxes. At winter solstice, the Sun once again rises in an apparently fixed horizon position for a week, but now in the southeast. A monument that has a horizon alignment on a solstice Sun (summer or winter, rise or set) is therefore a selection of one seven-day event of sunrises or sunsets out of a total 353 (365–14+2) events in any one year. There are important differences when a monument is aligned on the Moon. Unlike the Sun, the limits to the Moon’s horizon range fluctuate. When the Moon’s range is at its greatest extent, what Thom (1971) called the major standstill of the Moon, at the latitude of Stonehenge, the Moon’s horizon range is 10° of azimuth further north or south on the horizon than the Sun ever reaches at each of its four solstice positions. Nine or so years later, the Moon’s horizon range has shrunk to about 10° within the extreme horizon

Diagnostic problems of elementary soil processes and profile-differentiated soils of the Precarpathian region

Present condition, scientific concepts and ways of further development of diagnosis problem of elementary soil processes and genetic nature profiled-differentiated gleyed soils of the Pre-Carpathian region, known as brownish-podzolic, brownsoil-podzolic and sod-podzolic, based on stable indicators of soil properties are studied. Eluvial-illuvial differentiation nature of the soil profile of the studied soils is founded. The aim of research was to develop criteria for the diagnosis of elementary soil processes and genetic nature profiled-differentiated soil deposits of Ciscarpathia and discovering of the parameters of the relevant indicators of soil properties. The soil profile with his characteristic set of genetic horizons and morphological characteristics can result from taking place of both various set (kit) of ESP and of varying intensity of individual processes (complex ESP). Formation of genetic soil type is caused by the course of the profile forming (main) process with the possible participation of several (related) processes. An important condition for the diagnostic determination of profile-differentiated soils in the Ciscarpathia is the search for reliable diagnostic criteria for basic elementary soil processes (ESP) which play a crucial role in the genesis and determine their macromorphological characteristics: lessivage, podzolisation, gleying and eluvial-gleying processes. Diagnostic criteria of the elluvial processes resulted in gross chemical composition of the soil (molecular ratio), particle size distribution (loss sludge) and mineralogy silt fraction (montmorillonite content) were tested. The criteria for establishing genetic origin of the Pre-Carpathian soils, podzolization and eluvial-gley processes detection and their possible parameters were suggested. Followed the impact of the prevailing development of individual creating profile elementary soil processes (podzolization, eluvial-gley and gleying) by laboratory simulation modeling of soil regimes that are conducive to them (washing, water stagnant and contrast) for evaluative indicators of acid-base soil buffer and made the conclusions about the possibility of these processes isolation. Eluvial-illuvial differentiation of Ciscarpathia typical soils is coursed by passage of profile forming process of podzolisation (acid hydrolysis, podzolic) and related from the group of eluvial - eluvial-gleying process and lessivage. They are diagnosed by the gross grain and chemical composition of the soil and the content of montmorillonite. Brown soil forming processes have a significant impact on the formation of humus status and physical and chemical properties of the studied soil. Substantiated differences forming the group composition of humus and fractional composition of humic acids of soils formed underbrownsoil formation processes from the sod soils type (the ratio of humic acids to fulvic acid, gumatcalcium content, optical density of humic substances). Advantages and disadvantages of using quantitative identification criteria - profile humus accumulation factor in the genetic diagnosis of soil type are analyzed. In the conditions of wash and contrasting modes of moisture, causing the priority development processes of podzolisation and gleye- eluvial respectively a similar trend of formation of acid-base buffer capacity of soil and similar parameters of evaluating indicators within the soil profile are observed. It is impossible to separate the processes of podzolisation and gleye- eluvial using the indicators of acid-base buffering. Describing of profile structure, morphological and genetic traits of genetic horizons, the profile distribution of acid-base buffering indicators (even without the use of criteria based on gross chemical and grain composition and content of clay minerals) help to clear identify brownish-podzolic gley soils of Ciscarpathia.

New methods for slicing and dicing seismic volumes

G lobal seismic interpretation techniques aim to arrive at fully interpreted seismic volumes. ‘Fully’ in this context, however, is misleading as it gives the impression that we are dealing with an end product and that there is no more interpretation to be carried out. This is not the case. The correlated geologic timelines of these volumes open up new ways to analyse seismic data, thereby increasing our understanding of the depositional history and improving our ability to find stratigraphic traps and to build accurate geologic models. Geologic information in global seismic interpretation techniques can be unlocked through new methods for dicing and slicing seismic volumes. Using HorizonCube, this can be achieved through attributes and a 3D Slider in a workflow that combines 2D and 3D visualization techniques with interactive analysis. Examples of such techniques will be introduced. The HorizonCube consists of a dense set of horizons that are computed from the seismic dip field. The vertical separation between horizons in a HorizonCube varies spatially. This feature is exploited in a new set of attributes called HorizonCube attributes that capture local and global information. Examples are: HorizonCube density and HorizonCube thickness attributes. Both attributes can be highly effective in the interpretation of unconformities, condensed sections and sedimentation rates. For slicing and dicing seismic volumes, we use a 3D Slider in a workflow that combines 2D and 3D visualization techniques with interactive analysis. The workflow enables scanning thousands of auto-tracked horizons rapidly with the objective to identify pairs of horizons corresponding to top and base of depositional features of interest. In the next step, isochron thicknesses or attribute responses are computed and geobodies are extracted.

Integrated Bioenergy Supply Chain Network Planning Problem

We consider planning and design of an extended supply chain for bioenergy networks (i.e., networks for multibiomass as well as biofuel logistics) in an integrated fashion while simultaneously addressing strategic and tactical decisions pertaining to location, production, inventory, and distribution in a multiperiod planning horizon setting. In our modeling, we also explicitly incorporate realistic operational parameters, including biomass deterioration rates and transportation economies of scale. For an efficient solution of our model, we suggest a Benders decomposition–based algorithm that can handle realistic size problems for design and analysis purposes. We implement the approach in a particular way using callback functions, in which the master problem is solved only once; we also develop surrogate constraints for enhanced lower bounds to obtain improved convergence especially for large instances. We provide computational results that demonstrate the efficiency of the solution approach on a wide-ranging set of problem instances. Furthermore, we develop a realistic case using data pertaining to the state of Texas and conduct an extensive analysis on the effects of varying input parameters on the design outcomes for a bioenergy supply chain network.

Safety Stock, Excess Capacity or Diversification: Trade‐Offs under Supply and Demand Uncertainty

Firms mitigate uncertainty in demand and supply by carrying safety stock, planning for excess capacity and diversifying supply sources. In this study, we provide a framework to jointly optimize these three levers in a periodic review infinite horizon setting, and in particular we examine how one can reduce inventory and capacity investments through proper diversification strategies. Observing that a modified base‐stock inventory policy is optimal, we find that the capacity‐diversification problem is well behaved and characterize the optimal mix of safety stock, excess capacity and extra number of supply sources. We find that higher supply uncertainty results in higher safety stock, more excess capacity, and higher diversification. But safety stock and diversification are non‐monotonic in demand uncertainty. Our results can be extended to situations in which suppliers are heterogeneous, and can be used to develop effective heuristics.

Safety stock placement in supply chains with demand forecast updates

Supply chains are exposed to many types of risks and it may not be obvious where to keep safety stocks in the supply chain to hedge against those risks, while maintaining a high customer service level. In this paper, we develop an approach to determine the safety stock levels in supply chain systems that face demand uncertainty. We model customer demand following the Martingale Model of Forecast Evolution (MMFE). An extensive body of literature discusses the safety stock placement problem in supply chains, but most studies assume independent and identically distributed demand. Our approach is based on a simulation study in which mathematical models are solved in a rolling horizon setting. It allows determining the safety stock levels at each stage of the supply chain. Based on a numerical study, we find that a big portion of the safety stocks should be placed downstream in the supply chain to achieve a high customer service level.

Optimal Management of Markets for Bankable Emission Permits

We examine the optimal management of emission permit markets when banking but not borrowing of permits is allowed. The regulator maximizes expected social welfare through an optimal allocation rule in an infinite horizon setting. The policy is second-best as the emission cap is set before the uncertainty about the current state of the economy is resolved. In this setting, the role of banking is to decrease the regulator’s risk as it generates an endogenous price floor in the permit markets. We show that the regulator’s optimal policy adjusts the emissions cap irrespective of the existing number of permits in the bank, with the implication that the regulator neutralizes the effect of the existing bank on future permit prices. We derive the optimality conditions for the second-best emission cap with banking and solve the model analytically in the case of IID shocks. Our results show that the discount factor together with the slopes of the marginal damages and benefits determine the welfare gains from allowing baking of permits. Finally, to address the current state of the EU Emission Trading Scheme (EU ETS) and guide the design of future permit markets, we solve the model numerically with persistent shock process and show that the optimal emission cap is positively correlated with business cycles, meaning that during downturns the regulator should tighten the cap. The expected emissions and permit prices also correlate positively with economic activity.

A decision support system for cooperative transportation planning: Design, implementation, and performance assessment

In this paper, we describe a decision support system for cooperative transportation planning in the German food industry where several manufacturing companies share their fleets to reduce transportation costs. Besides using vehicles of their fleets, there are different outsourcing options offered by logistics service providers, but these are much more expensive. The decision-making kernel of the decision support system is implemented as a multi-agent-system (MAS). The kernel provides a distributed hierarchical algorithm for cooperative transportation planning and an on-line data layer that contains all the information for decision making. We sketch the distributed hierarchical transportation planning algorithm and identity the required software agents. The MAS interacts via web services with a commercial tour planning system that persistently stores the resulting tour plans, orders, and customer data. Moreover, the tour planning system is used to offer graphical user interfaces to interact with the users. The data layer is updated by order and customer data from the ERP systems of the different manufacturing companies. We describe the architecture and the implementation of the MAS and the overall coupling framework. Furthermore, we discuss the simulation-based performance assessment of the resulting decision support system when the system is applied in a rolling horizon setting and present some computational results. The results demonstrate that the MAS approach is appropriate for the cooperative transportation planning domain.

Simulation-based performance assessment of master planning approaches in semiconductor manufacturing

Semiconductor manufacturing is confronted with a large number of products whose mix is changing over time, heterogeneous fabrication processes, re-entrant flows of material, and different sources of environmental and system uncertainty. In this context, the mid-term production planning approach, i.e., master planning, typically does not capture the entire complexity of the shop-floor. It deals with an aggregated representation of the production system. There is a need for evaluating the planning algorithm in use while taking the execution level into account. Therefore, we introduce in this paper a simulation-based framework that allows for modeling the behavior of the market demand and the production system. An appropriate performance assessment methodology is proposed. The performance of two heuristic approaches for master planning in semiconductor manufacturing, a genetic algorithm and a rule-based assignment procedure, is evaluated within a rolling horizon setting while considering demand and execution uncertainty. A reduced discrete-event simulation model is used to mimic a one-stage network of wafer fabrication facilities. The results of simulation experiments are discussed.

Optimal consumption under uncertainty, liquidity constraints, and bounded rationality

I study how boundedly rational agents can learn a “good” solution to an infinite horizon optimal consumption problem under uncertainty and liquidity constraints. Using an empirically plausible theory of learning I propose a class of adaptive learning algorithms that agents might use to choose a consumption rule. I show that the algorithm always has a globally asymptotically stable consumption rule, which is optimal. Additionally, I present extensions of the model to finite horizon settings, where agents have finite lives and life-cycle income patterns. This provides a simple and parsimonious model of consumption for large agent based models.

Analysis of batch ordering inventory models with setup cost and capacity constraint

Stochastic periodic-review batch ordering inventory problems appear in many industrial settings. However, few literature deals with the optimal ordering polices for such problems, no mention to the inclusion of the fixed ordering cost and the production capacity. In this paper, we consider a single-item periodic-review batch ordering inventory system with the consideration of the setup cost and the capacity constraint for each order over a finite planning horizon. By proposing several new convex notions, we show that a batch-based (s,S) policy is optimal for the unlimited ordering capacity case, while for the limited ordering capacity case, a modified (r,Q) policy is optimal for the setting with zero ordering setup cost, and a batch-based X–Y band policy for the setting with positive ordering setup cost. Moreover, we analytically study the sensitivity of the policy parameters with respect to the capacity and batch order size, and derive the bounds on the optimal policy parameters. We further extend our analysis to the infinite horizon setting and show that the structure of the optimal policy remains similar. Finally, the numerical experiments provide some insights into the impact of model parameters on the benefit of reducing the batch size and increasing the ordering capacity, and indicate that ignoring batch requirement may lead to a significant cost increment.

Optimal Consumption Under Uncertainty, Liquidity Constraints, and Bounded Rationality

I study how boundedly rational agents can learn a good solution to an infinite horizon optimal consumption problem under uncertainty and liquidity constraints. Using an empirically plausible theory of learning I propose a class of adaptive learning algorithms that agents might use to choose a consumption rule. I show that the algorithm always has a globally asymptotically stable consumption rule, which is optimal. Additionally, I present extensions of the model to finite horizon settings, where agents have finite lives and life-cycle income patterns. This provides a simple and parsimonious model of consumption for large agent based models.

Small-scale maps of geochemical barriers

We examined the various aspects of the study into radial geochemical barriers in soils, their classification, and some mapping problems as well as the experience in compiling small-scale maps of geochemical barriers. We describe the technique for compiling maps of geochemical barriers (topsoils — biogeochemical and subsoil — physicochemical barriers) for the territory of Russia, based on M. A. Glazovskaya’s new typological grouping of barriers. The maps thus compiled are the result of applying the new typization and target-oriented interpretation of soil profiles (sets of genetic horizons) for the purposes of mapping large territories.

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