MODELING: A TOOL FOR ENHANCING THE SURVIVAL PROSPECTS OF AFRICAN WILDLIFE

ABSTRACT. In this article we consider the role of modeling in some aspects of the conservation of African wildlife. The first study is concerned with the endangered black rhino. Animals are being translocated from high density areas to new sites in an attempt to build up the South African population as rapidly as possible. We investigate the efficacy of different translocation strategies. Next we discuss a spatial stochastic metapopulation model used to test management strategies to enhance the survival likelihood of the rare samango monkey. The value of the model is to encourage the use of corridor policies even though there may be little apparent observable benefit in a manager's lifetime. Finally, we look at some commercial aspects of exploiting wildlife on a sustainable basis. By increasing the profitability of wildlife enterprises the incentive to conserve is increased. We look at improving the financial returns from game ranches.     

Modeling carbon spot and futures price returns with GARCH and Markov switching GARCH models

This paper makes use of spot and futures market data to carry out a thorough analysis of the dynamics of carbon price returns in the European Union Emission Trading Scheme for the whole first commitment period from 2008 to 2012. Understanding the properties of carbon price returns is especially crucial for industries which have to comply with an emission trading system and other market participants such as risk managers and speculators. We therefore seek to develop accurate models which capture the behavior of carbon price returns comprehensively. We apply a broad spectrum of GARCH model specifications, using different distributions for model innovations. As both time series, spot and futures price returns, exhibit asymmetric behavior in their variance, we additionally take Markov regime switching models for the variance equation into consideration. Empirical results demonstrate that AGARCH, NARCH and GJR fit the data best. We further show that, in the error term of any model, fat-tailed distributions—in particular the generalized error distribution—significantly improve the fit. Additionally, as futures returns seem to carry informational content concerning subsequent spot returns, we propose a sound, yet parsimonious, spot returns model, well-suited to capturing the dynamics. Finally, the most appropriate models for spot and futures price returns are tested in an out-of-sample environment, and further checked for robustness in data subsets. Subsequently a model for each market is proposed.     

Deposit games with reinvestment

In a deposit game coalitions are formed by players combining their capital. The proceeds of their investments then have to be divided among those players. The current model extends earlier work on capital deposits by allowing reinvestment of returns. Two specific subclasses of deposit games are introduced. These subclasses provide insight in two extreme cases. It is seen that each term dependent deposit game possesses a core element. Capital dependent deposit games are also shown to have a core element and even a population monotonic allocation scheme if the revenue function exhibits increasing returns to scale. Furthermore, it is shown that all superadditive games are deposit games if one allows for debt.     

Modeling international investment decisions for financial holding companies

This research analyzes the internationalization process model developed by Johanson and Vahlne and derives two integer programming investment decision models that consider the risk attitudes of investment firms. Johanson and Vahlne’s model provides a starting point for building a model that suits the investment approach and decision making process of financial holding companies. In practice, when firms make an international investment decision, there is a need for a model that can generate outputs based on financial measures such as profit, investment returns, and tolerable levels of risk. Thus, in this paper, Johanson and Vahlne’s concepts are studied and financial managers are interviewed to derive models that match the investment decision procedures of the firms. The model helps firms manage the risks of their investments and derive accurate investment strategies based on investment objectives and constraints.     

MODELING AND THE MANAGEMENT OF MIGRATORY BIRDS

Mathematical modeling of migratory bird populations is reviewed in the context of migratory bird management. We focus on dynamic models of waterfowl, since most management-oriented migratory bird models concern waterfowl species. We describe the management context for these modeling efforts, with a focus on large-scale operational data collection programs and on processes by which waterfowl harvest is regulated and waterfowl habitats are protected and managed. Through their impacts on key population parameters such as recruitment and survival rate, these activities can influence population dynamics, thereby providing managers some measure of control over the status of populations. Recent applications of the modeling of waterfowl are described in terms of objectives, mathematical structures, and contributions to management. Finally, we discuss research needs and data limitations in migratory bird modeling, and offer suggestions to increase the value to managers of future modeling efforts.     

Avoiding non-optimal management decisions by applying a three-person inspection game

An inspection game models a conflict situation between an inspector and an inspectee. The mathematical analysis aims to generate optimal behavior of the inspectee under the assumption that an undesirable action of the inspectee could otherwise be carried out strategically. In this paper the controller’s (inspector’s) particular job is to audit a manager’s (inspectee’s) decision and to submit a report to the company’s top managers for examination. Thus, a conflict as regards the choice of behavioral actions of the manager, the controller and the top management impends. Based on Fandel and Trockel (2011a) this modified inspection game is discussed here for the first time as a three-person game in the context of a manager’s faulty decision that will unnecessarily add to the company’s costs and that the top management understandably wishes to minimize. We will first examine the conditions under which a Nash equilibrium occurs in this three-person game in which poor management, poor monitoring and poor revision coincide. We will then examine the effects that the penalties and bonuses exert on the Nash equilibrium solution. We will find that penalties and bonuses can neutralize each other in their effects on the improved decision making by the manager and the controller.     

Modeling networked systems using the topologically distributed bounded rationality framework

In networked systems research, game theory is increasingly used to model a number of scenarios where distributed decision making takes place in a competitive environment. These scenarios include peer‐to‐peer network formation and routing, computer security level allocation, and TCP congestion control. It has been shown, however, that such modeling has met with limited success in capturing the real‐world behavior of computing systems. One of the main reasons for this drawback is that, whereas classical game theory assumes perfect rationality of players, real world entities in such settings have limited information, and cognitive ability which hinders their decision making. Meanwhile, new bounded rationality models have been proposed in networked game theory which take into account the topology of the network. In this article, we demonstrate that game‐theoretic modeling of computing systems would be much more accurate if a topologically distributed bounded rationality model is used. In particular, we consider (a) link formation on peer‐to‐peer overlay networks (b) assigning security levels to computers in computer networks (c) routing in peer‐to‐peer overlay networks, and show that in each of these scenarios, the accuracy of the modeling improves very significantly when topological models of bounded rationality are applied in the modeling process. Our results indicate that it is possible to use game theory to model competitive scenarios in networked systems in a way that closely reflects real world behavior, topology, and dynamics of such systems. © 2016 Wiley Periodicals, Inc. Complexity 21: 123–137, 2016     

A review of operations research models in invasive species management: state of the art,challenges, and future directions

Invasive species are a major threat to the economy, the environment, health, and thus human well-being. The international community, including the United Nations’ Global Invasive Species Program (GISP), National Invasive Species Council (NISC), and Center for Invasive Species Management (CISM), has called for a rapid control of invaders in order to minimize their adverse impacts. The effective management of invasive species is a highly complex problem requiring the development of decision tools that help managers prioritize actions most efficiently by considering corresponding bio-economic costs, impacts on ecosystems, and benefits of control. Operations research methods, such as mathematical programming models, are powerful tools for evaluating different management strategies and providing optimal decisions for allocating limited resources to control invaders. In this paper, we summarize the mathematical models applied to optimize invasive species prevention, surveillance, and control. We first define key concepts in invasive species management (ISM) in a framework that characterizes biological invasions, associated economic and environmental costs, and their management. We then present a spatio-temporal optimization model that illustrates various biological and economic aspects of an ISM problem. Next, we classify the relevant literature with respect to modeling methods: optimal control, stochastic dynamic programming, linear programming, mixed-integer programming, simulation models, and others. We further classify the ISM models with respect to the solution method used, their focus and objectives, and the specific application considered. We discuss limitations of the existing research and provide several directions for further research in optimizing ISM planning. Our review highlights the fact that operations research could play a key role in ISM and environmental decision-making, in particular closing the gap between the decision-support needs of managers and the decision-making tools currently available to management.     

Resource allocation in the North Sea demersal fisheries: A goal programming approach

The management of a fishery is a complex task generally involving multiple, often conflicting, objectives. These objectives typically include economic, biological and social goals such as improving the income of fishers, reducing the catch of depleted species and maintaining employment.Multicriteria decision making (MCDM) techniques appear wellsuited to such a management problem, allowing compromises between conflicting objectives to be analysed in a structured framework. In comparison to other fields, such as water resource planning, forestry and agriculture, there have been few applications of MCDM to fisheries.In this paper, a goal programming model of the North Sea demersal fishery is presented. The model is used to demonstrate the potential applicability of this type of approach to the analysis and development of fisheries management plans with multiple objectives. Alternative scenarios are considered for the problem, and tradeoffs between given objectives are also highlighted and discussed.     

A Bidding Simulation for Training Estimators

A simulation for training estimators and managers is described. The game simulates a bidding situation in the construction industry, with the participants split into teams which bid against each other for government contracts. The contracts are differentiated in terms of workload implications and location, and the teams are encouraged to use discriminating bidding strategies. The cost estimates provided include substantial uncertainty, and the teams can purchase more accurate estimates as well as buying competitive information. As a result of playing the game, participants appreciated the importance of expenditure on estimates, keeping good records, and using simple bidding models.     

An Interactive Dynamic Inventory-Production Control System

The development and evaluation of an interactive model for controlling inventories and scheduling production in a high technology batch production environment are discussed. The model allows the use of expert knowledge and company policy for matters such as customer service and safety stocks, in an interactive way. Production of a large number of products has to be scheduled for a number of time periods and a modified Wagner-Whitin algorithm is used for developing good schedules. A versatile data and information management system is a part of the developed software which has been implemented using a standard microcomputer. An evaluation suggests that the system is a practical one for use by busy managers. Further, it results in substantial cost savings and increased customer service.     

Coalitions and payoffs in three‐person sequential games: Initial tests of two formal models

In this paper we develop two formal models predicting coalitions and payoffs among rank striving players in a sequential three‐person game. We test the models’ predictions with data from a laboratory study of eleven male triads. Each triad plays a sequence of games; in each game a two‐person coalition forms and divides the coalition's point value between the two coalition partners. Participants know that the sequence of games will end without warning at a randomly chosen time; at the sequence's end each player's monetary payoff is a linear function of the rank of his accumulated point score, relative to those of the other members of his triad. The complexity of this situation prevents players and analysts from representing it as a single game; thus they are unable to use n‐person game theory to identify optimal strategies. Consequently, we assume that players, unable to develop strategies that are demonstrably optimal in the long run, adopt certain bargaining heuristics and surrogate short run objectives.

The two models follow the same basic outline; they differ, however, in the planning horizon they assume players to use. Proceeding from a priori assumptions concerning each player's decision calculus and the bargaining process, the two models state the probability that each coalition forms and predict the point divisions in the winning coalition. The laboratory data provide consistently strong support for the predictions of both models.     

Optimal pricing and ordering policy for non-instantaneous deteriorating items under inflation and customer returns

This paper deals with an economic production quantity inventory model for non-instantaneous deteriorating items under inflationary conditions considering customer returns. We adopt a price- and time-dependent demand function. Also, the customer returns are considered as a function of both price and demand. The effects of time value of money are studied using the Discounted Cash Flow approach. The main objective is to determine the optimal selling price, the optimal replenishment cycles, and the optimal production quantity simultaneously such that the present value of total profit is maximized. An efficient algorithm is presented to find the optimal solution. Finally, numerical examples are provided to solve the presented inventory model using our proposed algorithm, which is further clarified through a sensitivity analysis. The results of analysing customer returns provide important suggestions to financial managers who use price as a control to match the quantity sold to inventory while maximizing revenues. The paper ends with a conclusion and an outlook to future studies.     

Monotone Approximations of Minimum and Maximum Functions and Multi-objective Problems

In this paper the problem of accomplishing multiple objectives by a number of agents represented as dynamic systems is considered. Each agent is assumed to have a goal which is to accomplish one or more objectives where each objective is mathematically formulated using an appropriate objective function. Sufficient conditions for accomplishing objectives are derived using particular convergent approximations of minimum and maximum functions depending on the formulation of the goals and objectives. These approximations are differentiable functions and they monotonically converge to the corresponding minimum or maximum function. Finally, an illustrative pursuit-evasion game example with two evaders and two pursuers is provided.     

Controlling inventories with stochastic item returns: A basic model

Environmental legislation and customer expectations increasingly force manufacturers to take back their products after use. Returned products may enter the production process again as input resources. Material management has to be modified accordingly.One of the areas concerned is inventory management. The present paper provides a step towards a systematic analysis of inventory control in the context of reuse. A basic inventory model is presented comprising Poisson demand and returns. For this model, an optimal control policy is derived and optimal control parameters are computed. Moreover, a numerical analysis is provided of the impact of the return-flow on the inventory system. Comparison with traditional (s,Q)-inventory models is central throughout the analysis.     

The Use of Models for Environmental Forecasting and Corporate Planning

This paper presents briefly, the forecasting and planning activities which have evolved over the years in Esso Petroleum Company. It describes three computer models developed in the Corporate Planning Department for these activities an econometric model for short-term environmental forecasting and economic analysis; a horizon year optimization model for long-range corporate objectives setting; and a multi-time period simulation model for financial forecasting and planning both in short and long term. The structure, use and limitations of each of the models are discussed.     

Goal Programming Models for Assigning Search and Rescue Aircraft to Bases

This paper develops several variations of a goal programming model for optimally allocating a fleet of search and rescue aircraft to a fixed set of available and potentially available bases. In addition, the model determines the number of aircraft of each type from each base (at which that type has been stationed) to assign to the various search locations. The criterion for optimality is to maximize the probability of locating each distress in a specified time. These models are then modified to include fleet planning issues. Solution procedures relating to the models are discussed.     

Contracting over multiple parameters: Capacity allocation in semiconductor manufacturing

This paper is a generalization of Mallik and Harker [Mallik, S., Harker, P.T., 2004. Coordinating supply chains with competition: Capacity allocation in semiconductor manufacturing. European Journal of Operational Research 159, 330–347] that presented an integrated model of incentive problems arising in forecasting and capacity allocation. In that model, multiple product managers and multiple manufacturing managers forecast the means of their respective demand and capacity distributions, and a central coordinator allocates capacities based on these forecasts. A mechanism that elicits truthful information from the managers was the main contribution of that paper. The objective of this paper is to generalize our previous results to multiple statistics reporting. This work assumes that the central coordinator can ask the managers to report multiple statistics (mean and variance, for example) about their respective distributions. We propose a game theoretic model and design a mechanism (a bonus scheme and an allocation rule) that elicits truthful reporting of all statistics by all managers. It turns out that the structure of the optimal bonus schemes are rather simple with easily calculable parameters. We also show that a large class of allocation rules are manipulable. A bonus is often required for elicitation of truthful information. We compare our results of multiple statistics reporting with those from Mallik and Harker (2004). We also characterize under what conditions the reporting of the extra information is of limited use.     

Models for collective decision making in industry

When actions are taken by individual managers within a firm to enhance certain performance criteria they may be found to have an adverse effect on other criteria. Changes in pricing policies and promotional activity, modifications in product design, increased mechanisation of production processes or operations, etc., are just examples of actions which in general do not have equally desirable consequences on the most commonly pursued objectives within the company, such as that of reducing unit costs, or those of increasing turnover, market share, profit levels and return on capital employed.In this paper simple models are developed and analysed, each enabling the user to assess explicitly the effects on the unit cost; the revenue and the profit of combined changes imposed on the system by management decisions or by external factors. It is suggested that these models be used as a basis for discussion by the managers involved with a view to reaching a consensus as to the desirable decisions that should be taken.     

Bank Balance-Sheet Management: An Alternative Multi-Objective Model

Bank balance-sheet management entails considering competing and conflicting objectives such as maximization of returns and minimization of risks associated with alternative portfolio combinations. Traditional multi-objective models simply provide the decision-maker with the entire set of non-dominated solutions; the decision-maker must then choose, unaided, the best solution based on his subjective trade-offs, experience and judgement. This paper develops an alternative multi-objective balance-sheet management model which allows the explicit incorporation of the decision-maker's trade-offs between conflicting objectives, and attempts to reduce his cognitive burden while ensuring that the solution obtained belongs to the set of non-dominated points.