How to Make the Most Productive Intervention in a Complex Economic System

Information about supply and demand propagates through supply chains in a queueing network with people and computers as batch information processors. As each batch processor delays propagation of information whilst pursuing optimal local decisions, the effect is delay and distortion of the information that is used to commit resources to actions in the supply chain. This thesis investigates the effect of delay and imperfect information as a source of error, to establish the case for change in research focus from optimal exploitation of physical constraints to optimal exploitation of information. In the context of real world supply chains, the thesis asks "How does one make the most productive intervention in a complex economic system?" and pursues a meta-intervention which perpetually minimises the discovered error-term. Evidence from literature indicates that agent-based modelling permits real-time peer-to-peer communication and distributed optimisation. Based on the literature the research project designs and develops an agent-based model which operates in real-time without batch-processes and can perform incremental multi-objective optimisation under realistic (chronologically progressive) conditions for decision making. The agent based model is then used to investigate two real-world supply chains, as case studies, which reveals a significant improvement of profitability and order-fulfilment. The thesis concludes that agent-based modelling is a very promising direction for "making the most productive intervention" as it reduces delay to a minimum. Finally it recommends that continuous improvement of decision making methods is a role better suited for humans, rather than operational decision making where computers cope much better with the high amount of detailed information

A Mechanism Design Approach to Bandwidth Allocation in Tactical Data Networks

The defense sector is undergoing a phase of rapid technological advancement, in the pursuit of its goal of information superiority. This goal depends on a large network of complex interconnected systems - sensors, weapons, soldiers - linked through a maze of heterogeneous networks. The sheer scale and size of these networks prompt behaviors that go beyond conglomerations of systems or `system-of-systems\u27. The lack of a central locus and disjointed, competing interests among large clusters of systems makes this characteristic of an Ultra Large Scale (ULS) system. These traits of ULS systems challenge and undermine the fundamental assumptions of today\u27s software and system engineering approaches. In the absence of a centralized controller it is likely that system users may behave opportunistically to meet their local mission requirements, rather than the objectives of the system as a whole. In these settings, methods and tools based on economics and game theory (like Mechanism Design) are likely to play an important role in achieving globally optimal behavior, when the participants behave selfishly. Against this background, this thesis explores the potential of using computational mechanisms to govern the behavior of ultra-large-scale systems and achieve an optimal allocation of constrained computational resources Our research focusses on improving the quality and accuracy of the common operating picture through the efficient allocation of bandwidth in tactical data networks among self-interested actors, who may resort to strategic behavior dictated by self-interest. This research problem presents the kind of challenges we anticipate when we have to deal with ULS systems and, by addressing this problem, we hope to develop a methodology which will be applicable for ULS system of the future. We build upon the previous works which investigate the application of auction-based mechanism design to dynamic, performance-critical and resource-constrained systems of interest to the defense community. In this thesis, we consider a scenario where a number of military platforms have been tasked with the goal of detecting and tracking targets. The sensors onboard a military platform have a partial and inaccurate view of the operating picture and need to make use of data transmitted from neighboring sensors in order to improve the accuracy of their own measurements. The communication takes place over tactical data networks with scarce bandwidth. The problem is compounded by the possibility that the local goals of military platforms might not be aligned with the global system goal. Such a scenario might occur in multi-flag, multi-platform military exercises, where the military commanders of each platform are more concerned with the well-being of their own platform over others. Therefore there is a need to design a mechanism that efficiently allocates the flow of data within the network to ensure that the resulting global performance maximizes the information gain of the entire system, despite the self-interested actions of the individual actors. We propose a two-stage mechanism based on modified strictly-proper scoring rules, with unknown costs, whereby multiple sensor platforms can provide estimates of limited precisions and the center does not have to rely on knowledge of the actual outcome when calculating payments. In particular, our work emphasizes the importance of applying robust optimization techniques to deal with the uncertainty in the operating environment. We apply our robust optimization - based scoring rules algorithm to an agent-based model framework of the combat tactical data network, and analyze the results obtained. Through the work we hope to demonstrate how mechanism design, perched at the intersection of game theory and microeconomics, is aptly suited to address one set of challenges of the ULS system paradigm - challenges not amenable to traditional system engineering approaches

MODELLING & SIMULATION HYBRID WARFARE Researches, Models and Tools for Hybrid Warfare and Population Simulation

The Hybrid Warfare phenomena, which is the subject of the current research, has been framed by the work of Professor Agostino Bruzzone (University of Genoa) and Professor Erdal Cayirci (University of Stavanger), that in June 2016 created in order to inquiry the subject a dedicated Exploratory Team, which was endorsed by NATO Modelling & Simulation Group (a panel of the NATO Science & Technology organization) and established with the participation as well of the author. The author brought his personal contribution within the ET43 by introducing meaningful insights coming from the lecture of \u201cFight by the minutes: Time and the Art of War (1994)\u201d, written by Lieutenant Colonel US Army (Rtd.) Robert Leonhard; in such work, Leonhard extensively developed the concept that \u201cTime\u201d, rather than geometry of the battlefield and/or firepower, is the critical factor to tackle in military operations and by extension in Hybrid Warfare. The critical reflection about the time - both in its quantitative and qualitative dimension - in a hybrid confrontation it is addressed and studied inside SIMCJOH, a software built around challenges that imposes literally to \u201cFight by the minutes\u201d, echoing the core concept expressed in the eponymous work. Hybrid Warfare \u2013 which, by definition and purpose, aims to keep the military commitment of both aggressor and defender at the lowest - can gain enormous profit by employing a wide variety of non-military tools, turning them into a weapon, as in the case of the phenomena of \u201cweaponization of mass migrations\u201d, as it is examined in the \u201cDies Irae\u201d simulation architecture. Currently, since migration it is a very sensitive and divisive issue among the public opinions of many European countries, cynically leveraging on a humanitarian emergency caused by an exogenous, inducted migration, could result in a high level of political and social destabilization, which indeed favours the concurrent actions carried on by other hybrid tools. Other kind of disruption however, are already available in the arsenal of Hybrid Warfare, such cyber threats, information campaigns lead by troll factories for the diffusion of fake/altered news, etc. From this perspective the author examines how the TREX (Threat network simulation for REactive eXperience) simulator is able to offer insights about a hybrid scenario characterized by an intense level of social disruption, brought by cyber-attacks and systemic faking of news. Furthermore, the rising discipline of \u201cStrategic Engineering\u201d, as envisaged by Professor Agostino Bruzzone, when matched with the operational requirements to fulfil in order to counter Hybrid Threats, it brings another innovative, as much as powerful tool, into the professional luggage of the military and the civilian employed in Defence and Homeland security sectors. Hybrid is not the New War. What is new is brought by globalization paired with the transition to the information age and rising geopolitical tensions, which have put new emphasis on hybrid hostilities that manifest themselves in a contemporary way. Hybrid Warfare is a deliberate choice of an aggressor. While militarily weak nations can resort to it in order to re-balance the odds, instead military strong nations appreciate its inherent effectiveness coupled with the denial of direct responsibility, thus circumventing the rules of the International Community (IC). In order to be successful, Hybrid Warfare should consist of a highly coordinated, sapient mix of diverse and dynamic combination of regular forces, irregular forces (even criminal elements), cyber disruption etc. all in order to achieve effects across the entire DIMEFIL/PMESII_PT spectrum. However, the owner of the strategy, i.e. the aggressor, by keeping the threshold of impunity as high as possible and decreasing the willingness of the defender, can maintain his Hybrid Warfare at a diplomatically feasible level; so the model of the capacity, willingness and threshold, as proposed by Cayirci, Bruzzone and Gunneriusson (2016), remains critical to comprehend Hybrid Warfare. Its dynamicity is able to capture the evanescent, blurring line between Hybrid Warfare and Conventional Warfare. In such contest time is the critical factor: this because it is hard to foreseen for the aggressor how long he can keep up with such strategy without risking either the retaliation from the International Community or the depletion of resources across its own DIMEFIL/PMESII_PT spectrum. Similar discourse affects the defender: if he isn\u2019t able to cope with Hybrid Threats (i.e. taking no action), time works against him; if he is, he can start to develop counter narrative and address physical countermeasures. However, this can lead, in the medium long period, to an unforeseen (both for the attacker and the defender) escalation into a large, conventional, armed conflict. The performance of operations that required more than kinetic effects drove the development of DIMEFIL/PMESII_PT models and in turn this drive the development of Human Social Culture Behavior Modelling (HCSB), which should stand at the core of the Hybrid Warfare modelling and simulation efforts. Multi Layers models are fundamental to evaluate Strategies and Support Decisions: currently there are favourable conditions to implement models of Hybrid Warfare, such as Dies Irae, SIMCJOH and TREX, in order to further develop tools and war-games for studying new tactics, execute collective training and to support decisions making and analysis planning. The proposed approach is based on the idea to create a mosaic made by HLA interoperable simulators able to be combined as tiles to cover an extensive part of the Hybrid Warfare, giving the users an interactive and intuitive environment based on the \u201cModelling interoperable Simulation and Serious Game\u201d (MS2G) approach. From this point of view, the impressive capabilities achieved by IA-CGF in human behavior modeling to support population simulation as well as their native HLA structure, suggests to adopt them as core engine in this application field. However, it necessary to highlight that, when modelling DIMEFIL/PMESII_PT domains, the researcher has to be aware of the bias introduced by the fact that especially Political and Social \u201cscience\u201d are accompanied and built around value judgement. From this perspective, the models proposed by Cayirci, Bruzzone, Guinnarson (2016) and by Balaban & Mileniczek (2018) are indeed a courageous tentative to import, into the domain of particularly poorly understood phenomena (social, politics, and to a lesser degree economics - Hartley, 2016), the mathematical and statistical instruments and the methodologies employed by the pure, hard sciences. Nevertheless, just using the instruments and the methodology of the hard sciences it is not enough to obtain the objectivity, and is such aspect the representations of Hybrid Warfare mechanics could meet their limit: this is posed by the fact that they use, as input for the equations that represents Hybrid Warfare, not physical data observed during a scientific experiment, but rather observation of the reality that assumes implicitly and explicitly a value judgment, which could lead to a biased output. Such value judgement it is subjective, and not objective like the mathematical and physical sciences; when this is not well understood and managed by the academic and the researcher, it can introduce distortions - which are unacceptable for the purpose of the Science - which could be used as well to enforce a narrative mainstream that contains a so called \u201ctruth\u201d, which lies inside the boundary of politics rather than Science. Those observations around subjectivity of social sciences vs objectivity of pure sciences, being nothing new, suggest however the need to examine the problem under a new perspective, less philosophical and more leaned toward the practical application. The suggestion that the author want make here is that the Verification and Validation process, in particular the methodology used by Professor Bruzzone in doing V&V for SIMCJOH (2016) and the one described in the Modelling & Simulation User Risk Methodology (MURM) developed by Pandolfini, Youngblood et all (2018), could be applied to evaluate if there is a bias and the extent of the it, or at least making clear the value judgment adopted in developing the DIMEFIL/PMESII_PT models. Such V&V research is however outside the scope of the present work, even though it is an offspring of it, and for such reason the author would like to make further inquiries on this particular subject in the future. Then, the theoretical discourse around Hybrid Warfare has been completed addressing the need to establish a new discipline, Strategic Engineering, very much necessary because of the current a political and economic environment which allocates diminishing resources to Defense and Homeland Security (at least in Europe). However, Strategic Engineering can successfully address its challenges when coupled with the understanding and the management of the fourth dimension of military and hybrid operations, Time. For the reasons above, and as elaborated by Leonhard and extensively discussed in the present work, addressing the concern posed by Time dimension is necessary for the success of any military or Hybrid confrontation. The SIMCJOH project, examined under the above perspective, proved that the simulator has the ability to address the fourth dimension of military and non-military confrontation. In operations, Time is the most critical factor during execution, and this was successfully transferred inside the simulator; as such, SIMCJOH can be viewed as a training tool and as well a dynamic generator of events for the MEL/MIL execution during any exercise. In conclusion, SIMCJOH Project successfully faces new challenging aspects, allowed to study and develop new simulation models in order to support decision makers, Commanders and their Staff. Finally, the question posed by Leonhard in terms of recognition of the importance of time management of military operations - nowadays Hybrid Conflict - has not been answered yet; however, the author believes that Modelling and Simulation tools and techniques can represent the safe \u201ctank\u201d where innovative and advanced scientific solutions can be tested, exploiting the advantage of doing it in a synthetic environment

Out-of-equilibrium economic dynamics and persistent polarisation

Most of economics is equilibrium economics of one sort or another. The study of outof- equilibrium economics has largely been neglected. This thesis, engaging with ideas and techniques from complexity science, develops frameworks and tools for out-of-equilibrium modelling. We initially focus our attention on models of exchange before examining methods of agent-based modelling. Finally we look at a set of models for social dynamics with nontrivial micro-macro interrelationships. Chapter 2 introduces complexity science and relevant economic concepts. In particular we examine the idea of complex adaptive systems, the application of complexity to economics, some key ideas from microeconomics, agent-based modelling and models of segregation and/or polarisation. Chapter 3 develops an out-of-equilibrium, fully decentralised model of bilateral exchange. Initially we study the limiting properties of our out-of-equilibrium dynamic, characterising the conditions required for convergence to pairwise and Pareto optimal allocation sets. We illustrate problems that can arise for a rigid version of the model and show how even a small amount of experimentation can overcome these. We investigate the model numerically characterising the speed of convergence and changes in ex post wealth. In chapter 4 we now explicitly model the trading structure on a network. We derive analytical results for this general network case. We investigate the e�ect of network structure on outcomes numerically and contrast the results with the fully connected case of chapter 3. We look at extensions of the model including a version with an endogenous network structure and a versions where agents can learn to accept a `worthless' but widely available good in exchanges. Chapter 5 outlines and demonstrates a new approach to agent-based modelling which draws on a number techniques from contemporary software engineering. We develop a prototype framework to illustrate how the ideas might be applied in practice in order to address methodological gaps in many current approaches. We develop example agent-based models and contrast the approach with existing agent-based modelling approaches and the kind of purpose built models which were used for the numerical results in chapters 3 and 4. Chapter 6 develops a new set of models for thinking about a wide range of social dynamics issues including human capital acquisition and migration. We analyse the models initially from a Nash equilibrium perspective. Both continuum and �nite versions of the model are developed and related. Using the criterion of stochastic stability we think about the long run behaviour of a version of the model. We introduce agent heterogeneity into the model. We conclude with a fully dynamic version of the model (using techniques from chapter 5) which looks at endogenous segregation

Guiding the next generation of doctoral students in operations management

This paper presents ways for senior researchers to help future doctoral students in Operations Management (OM) to overcome multiple challenges in: (a) conducting relevant research while demonstrating greater rigor, and (b) exploring multi-disciplinary research projects while mastering a single research method. Recognizing that knowledge is generally created in four broad stages ((I) awareness, (II) framing, (III) modeling and (IV) validation), we first argue that different research approaches (analytical, behavioral, case study, or empirical) serve different roles in each of these stages: (1) case study approach for awareness, (2) empirical methods for framing, (3) analytical modeling for modeling and analysis, and (4) behavioral for validation in the real world. Then we discuss ways to enable doctoral students to overcome the aforementioned challenges

Efficient Spectrum Management for Mobile Ad Hoc Networks

The successful deployment of advanced wireless network applications for defense, homeland security, and public safety depends on the availability of relatively interference-free spectrum. Setup and maintenance of mobile networks for military and civilian first-response units often requires temporary allocation of spectrum resources for operations of finite, but uncertain, duration. As currently practiced, this is a very labor-intensive process with direct parallels to project management. Given the wide range of real-time local variation in propagation conditions, spatial distribution of nodes, and evolving technical and mission priorities current human-in-the loop conflict resolution approaches seem untenable. If the conventional radio regulatory structure is strictly adhered to, demand for spectrum will soon exceed supply. Software defined radio is one technology with potential to exploit local inefficiencies in spectrum usage, but questions regarding the management of such network have persisted for years. This dissertation examines a real-time spectrum distribution approach that is based on principles of economic utility and equilibrium among multiple competitors for limited goods in a free market. The spectrum distribution problem may be viewed as a special case of multi-objective optimization of a constrained resource. A computer simulation was developed to create hundreds of cases of local spectrum crowding, to which simultaneous perturbation simulated annealing (SPSA) was applied as a nominal optimization algorithm. Two control architectures were modeled for comparison, one requiring a local monitoring infrastructure and coordination ("top down") the other more market based ("bottom up"). The analysis described herein indicates that in both cases "hands-off" local spectrum management by trusted algorithms is not only feasible, but that conditions of entry for new networks may be determined a priori, with a degree of confidence described by relatively simple algebraic formulas

Fuzzy decision making system and the dynamics of business games

Effective and efficient strategic decision making is the backbone for the success of a business organisation among its competitors in a particular industry. The results of these decision making processes determine whether the business will continue to survive or not. In this thesis, fuzzy logic (FL) concepts and game theory are being used to model strategic decision making processes in business organisations. We generally modelled competition by business organisations in industries as games where each business organization is a player. A player formulates his own decisions by making strategic moves based on uncertain information he has gained about the opponents. This information relates to prevailing market demand, cost of production, marketing, consolidation efforts and other business variables. This uncertain information is being modelled using the concept of fuzzy logic. In this thesis, simulation experiments were run and results obtained in six different settings. The first experiment addresses the payoff of the fuzzy player in a typical duopoly system. The second analyses payoff in an n-player game which was used to model a perfect market competition with many players. It is an extension of the two-player game of a duopoly market which we considered in the first experiment. The third experiment used and analysed real data of companies in a case study. Here, we chose the competition between Coca-cola and PepsiCo companies who are major players in the beverage industry. Data were extracted from their published financial statements to validate our experiment. In the fourth experiment, we modelled competition in business networks with uncertain information and varying level of connectivity. We varied the level of interconnections (connectivity) among business units in the business networks and investigated how missing links affect the payoffs of players on the networks. We used the fifth experiment to model business competition as games on boards with possible constraints or restrictions and varying level of connectivity on the boards. We also investigated this for games with uncertain information. We varied the level of interconnections (connectivity) among the nodes on the boards and investigated how these a ect the payoffs of players that played on the boards. We principally used these experiments to investigate how the level of availability of vital infrastructures (such as road networks) in a particular location or region affects profitability of businesses in that particular region. The sixth experiment contains simulations in which we introduced the fuzzy game approach to wage negotiation in managing employers and employees (unions) relationships. The scheme proposes how employers and employees (unions) can successfully manage the deadlocks that usually accompany wage negotiations. In all cases, fuzzy rules are constructed that symbolise various rules and strategic variables that firms take into consideration before taken decisions. The models also include learning procedures that enable the agents to optimize these fuzzy rules and their decision processes. This is the main contribution of the thesis: a set of fuzzy models that include learning, and can be used to improve decision making in business