The improvement of water quality in the streams of the Glenelg Hopkins catchment is a priority of the Glenelg Hopkins regional strategy. A major source of water pollution in the region is linked to agricultural activities as high nutrient levels from runoff have the potential to increase the incidence of blue-green algae in the waterways. Land use change, reduced rainfall, more frequent extreme rainfall events and higher temperatures associated with climate change are likely to exacerbate this trend. Water testing data of the Total Phosphorus (TP) levels in the Hopkins River and at other sites within the Hopkins Catchment indicate increasing incidence of TP above the Environment Protection Authority's target levels for extended periods of each year. Earlier research indicated that phosphorus in runoff increases when pasture fertility increases and that fertiliser management practices should be considered as an element of preventative action for reducing nutrient pollution. During our research, a survey was undertaken in the Hopkins River catchment, to determine the current management of phosphorus (P) fertilisers on grazing and mixed enterprise farms, the attitude of farmers to natural resource management and their understanding of nutrient pollution. The survey also gathered information on the way farmers made fertiliser management decisions. If cooperation relating to phosphorus fertiliser application could be facilitated between groups of farmers, it may be possible to reduce nutrient runoff into the Hopkins waterways. Cooperative game theory has successfully been used worldwide in the resolution of environmental problems where there is an economic impact to the decision making process. In this project, the amount of phosphorus applied per hectare was used in a cooperative game theory model assessing the potential for cooperative action on phosphorus management by groups of farmers, based on the trade off between the economic cost of pollution to the region waterways and the economic production benefits to the individual. The outcome of this work was individual optimal strategies for fertiliser application, allowing individual farmers to reduce their impact of agricultural production on the health of the catchment. Involving the farmer groups, while undertaking the project, raised awareness amongst the farming population of the regional nutrient pollution caused by runoff from agricultural land, and enlisted their assistance towards adopting a cooperative approach to the problem. In addition, the results have been mapped using a Geographical Information System (GIS) for visual presentation and to demonstrate the use of this process in natural resource management with the farmer groups.

We consider a decentralized, two-echelon supply chain where the upper echelon --the supplier-- bears the inventory risk. To service the retailers, the supplier either keeps inventory reserved for each of her customers or else pools inventory to share among her customers. The common insight regarding inventory pooling is that it reduces costs and so increases profits for the supply chain party carrying inventory. However, it has recently been shown that inventory pooling may indeed reduce the total supply chain profits. We further show that inventory pooling may reduce supply chain profits even under traditional service contracts based on the frequently invoked measure of service, probability of stock-out. We model the inventory transactions among the retailers and the supplier as a cooperative game. The players have the option of reserving inventory or forming inventory-pooling coalitions. The total profit of the coalitions is allotted to the players using a profit-sharing mechanism based on Shapley value. We analyze the properties of the proposed profit-sharing scheme in two steps. We first consider a stylized model with two retailers who are not necessarily identical. Then we extend the analysis to an arbitrary number of identical retailers. In both cases, we assume the demand across retailers is independent. We find that the Shapley value allocations coordinate the supply chain and are individually rational. However for more than two retailers, they may not be in the core. Even when they satisfy all the stability properties, including membership in the core, they may be perceived unfair since a player's allocation can exceed his contribution to the total supply chain profit. In addition to analyzing the stability properties of the proposed allocation mechanism, we are also interested in the types of behavior the mechanism induces in the players. We find that the retailers prefer pooling partners with either very high or low service level requirements and the supplier prefers retailers with low service requirements since this gives her the ability to maximize her profit allocation. Finally, we analyze the effects of demand variance on the allocations and the profitability of strategic retailer coalitions.

Energy consumption and its management have been clearly identified as a challenge in computing and communication system design, where energy economy is obviously of paramount importance for battery powered devices. This thesis addresses the energy efficiency of mobile communication at the user end in the context of cellular networks. We argue that energy efficiency starts by energy awareness and propose EnergyBox, a parametrised tool that enables accurate and repeatable energy quantification at the user end using real data traffic traces as input. EnergyBox offers an abstraction of the underlying states for operation of the wireless interfaces and allows to estimate the energy consumption for different operator settings and device characteristics. The tool is used throughout the thesis to quantify and reveal inefficient data communication patterns of widely used mobile applications. We consider two different perspectives in the search of energy-efficient solutions. From the application perspective, we show that systematically quantifying the energy consumption of design choices (e.g., communication patterns, protocols, and data formats) contributes to a significantly smaller energy footprint. From the system perspective, we devise a cross-layer solution that schedules packet transmissions based on the knowledge of the network parameters that impact the energy consumption of the handset. These attempts show that application level decisions require a better understanding of possible energy apportionment policies at system level. Finally, we study the generic problem of determining the contribution of an entity (e.g., application) to the total energy consumption of a given system (e.g., mobile device). We compare the state-of-the-art policies in terms of fairness leveraging cooperative game theory and analyse their required information and computational complexity. We show that providing incentives to reduce the total energy consumption of the system (as part of fairness) is tightly coupled to the policy selection. Our study provides guidelines to select an appropriate policy depending on the characteristics of the system.

Virtual Enterprise (VE) is an organizational collaboration concept which provides a competitive edge in the globalized business environment. The life cycle of a VE consists of four stages i.e. opportunity identification (Pre-Creation), partner selection (Creation), operation and dissolution. The success of VEs depends upon the efficient execution of their VE-lifecycles along with knowledge enhancement for the partner enterprises to facilitate the future formation of efficient VEs. This research aims to study the different issues which occur in the VE lifecycle and provides a platform for the formation of high performance enterprises and VEs. In the pre-creation stage, enterprises look for suitable partners to create their VE and to exploit a market opportunity. This phase requires explicit and implicit information extraction from enterprise data bases (ECOS-ontology) for the identification of suitable partners. A description logic (DL) based query system is developed to extract explicit and implicit information and to identify potential partners for the creation of the VE. In the creation phase, the identified partners are analysed using different risks paradigms and a cooperative game theoretic approach is used to develop a revenue sharing mechanism based on enterprises inputs and risk minimization for optimal partner selection. In the operation phases, interoperability remains a key issue for seamless transfer of knowledge information and data. DL-based ontology mapping is applied in this research to provide interoperability in the VE between enterprises with different domains of expertise. In the dissolution stage, knowledge acquired in the VE lifecycle needs to be disseminated among the enterprises to enhance their competitiveness. A DL-based ontology merging approach is provided to accommodate new knowledge with existing data bases with logical consistency. Finally, the proposed methodologies are validated using the case study. The results obtained in the case study illustrate the applicability and effectiveness of proposed methodologies in each stage of the VE life cycle.

The performance of many protocols and applications of Vehicular Ad hoc Networks (VANETs), depends on vehicles obtaining enough fresh information on the status of their neighbouring vehicles. This should be fulfilled by exchanging Basic Safety Messages (BSMs) also called beacons using a shared channel. In dense vehicular conditions, many of the beacons are lost due to channel congestion. Therefore, in such conditions, it is necessary to control channel load at a level that maximizes BSM dissemination. To address the problem, in this thesis algorithms for adaptation of beaconing to control channel load are proposed. First, a position-based routing protocol for VANETs is proposed and the requirement of adaptive beaconing to increase the performance of the protocol is indicated. The routing protocol is traffic-aware and suitable for city environments and obtains real-time traffic information in a completely ad hoc manner without any central or dedicated control, such as traffic sensors, roadside units, or information obtained from outside the network. The protocol uses an ant-based algorithm to find a route that has optimum network connectivity. Using information included in small control packets called ants, vehicles calculate a weight for every street segment that is proportional to the network connectivity of that segment. Ant packets are launched by vehicles in junction areas. To find the optimal route between a source and destination, a source vehicle determines the path on a street map with the minimum total weight for the complete route. The correct functionality of the protocol design has been verified and its performance has been evaluated in a simulation environment. Moreover, the performance of the protocol in different vehicular densities has been studied and indicated that in dense vehicular conditions the performance of the protocol degrades due to channel load created by uncontrolled periodic beaconing. Then, the problem of beaconing congestion control has been formulated as non-cooperative games, and algorithms for finding the equilibrium point of the games have been presented. Vehicles as players of the games adjust their beacon rate or power or both, based on the proposed algorithms so that channel load is controlled at a desired level. The algorithms are overhead free and fairness in rate or power or both rate and power allocation are achieved without exchanging excess information in beacons. Every vehicle just needs local information on channel load while good fairness is achieved globally. In addition, the protocols have per-vehicle parameters, which makes them capable of meeting application requirements. Every vehicle can control its share of bandwidth individually based on its dynamics or requirements, while the whole usage of the bandwidth is controlled at an acceptable level. The algorithms are stable, computationally inexpensive and converge in a short time, which makes them suitable for the dynamic environment of VANETs. The correct functionality of the algorithms has been validated in several high density scenarios using simulations.

À l'ère de la mondialisation, l’environnement industriel et économique a subi plusieurs changements majeurs. Les chaînes logistiques sont en train de devenir de plus en plus de complexes réseaux composés de nombreux acteurs qui sont tantôt en concurrence et tantôt coopèrent pour répondre aux incessantes exigences des consommateurs. Dans un tel contexte, les entreprises se sont rapidement rendu compte de la limite du modèle complètement décentralisé où chacune d’entre elles optimise sa propre chaîne logistique indépendamment des autres acteurs. Afin de trouver de nouvelles sources de compétitivité et de faire face à la perpétuelle complexité de l’environnement économique, les entreprises tentent de dépasser la frontière des actions individuelles favorisant les actions coordonnées et centralisées. Désormais, la coopération entre les diverses chaînes logistiques et la formation d’alliances se trouvent au coeur des préoccupations des entreprises. En effet, en mutualisant les moyens logistiques, la coopération permet une meilleure exploitation des ressources et par le biais des actions collectives, elle permet de mieux bénéficier des économies d’échelles conduisant à réduire significativement les coûts et à générer des bénéfices considérables. Toutefois, dans de tels systèmes coopératifs, les acteurs sont indépendants et par ailleurs toujours intéressés en priorité par leurs profits individuels. De ce fait, la coopération soulève deux enjeux essentiels : (1) Quelles sont les alliances qui sont susceptibles de se former ? Et (2), comment partager les bénéfices réalisés sur les différents acteurs coopérants ? Dans cette thèse, nous nous intéressons au phénomène de la coopération dans les chaînes logistiques. Particulièrement, nous posons les précédentes questions dans des chaînes logistiques ou plusieurs firmes peuvent réduire leurs coûts logistiques en optant pour une gestion collective des stocks. Les principaux résultats de cette thèse portent sur l’utilisation des principes de la théorie des jeux coopératifs pour déterminer les alliances les plus profitables ainsi que la portion de profit que chaque firme doit recevoir afin de garder la stabilité des alliances formées. / In the age of outsourcing and globalization, the economic and industrial landscape has seen many radical changes. In such context, supply chains are becoming complex networks of a large number of entities that sometimes compete and sometimes cooperate to fulfill customers’ needs. Standalone supply chains, where each entity makes its decisions so as to maximize its own profits according to its own objectives, often lead to a loss of efficiency and fail to face the complexity of the economic environment they are facing with. Cooperative structures, however, where resources/service facilities are shared and decisions are made to maximize the global profit, prove to be more beneficial and efficient. Consequentially, many companies are fundamentally changing their way of doing business by exceeding the border of standalone and individual actions toward collective actions and cooperative strategies. Therefore, building alliances appears as a successful strategy in modern supply chain networks. In general, cooperation enables a better exploitation of the system’s resources and offers the opportunity to get benefit from large economies of scope, which in turn reduces the total cost/increases the total savings. However, it raises two natural questions that need to be addressed: (1) Which coalitions can be expected to be formed? And, (2) How will the cooperating actors share their total profit? In this Ph.D. dissertation, we tempt to address these questions in retail supply chains where independent retailers coordinate their replenishment from a supplier in order to save on delivery costs. Considering various joint replenishment environments, our principal contribution is to use principles from cooperative game theory to identify the most profitable alliances and to determine the portion of profit that would be allocated to each actor in order to guarantee the stability of the formed alliances.

Cooperation among humanitarian organizations has attracted increasing attention to enhance effectiveness and efficiency of relief supply chains. Our research focuses on horizontal cooperation in inventory management which is currently implemented in the United Nations Humanitarian Response Depot (UNHRD) network. The present work follows a two-step research approach, which involves collection of empirical data and quantitative modeling to examine and overcome the coordination challenges of the network. Our interviews with members of the network identified several managerial issues for sustainable cooperative inventory management that the UNHRD network pursues. Using a newsvendor model in the context of non-cooperative game theory, our research has explored member humanitarian organizations' incentive of joining the network, a coordination mechanism which achieves system optimality, and impacts of members' decisions about stock rationing. Our results indicate that behaviors of member HOs do not necessarily align with the UNHRD's expectation. Our results suggest that for system optimality, a system coordinator should carefully assess the circumstances, including demand coefficient and stock rationing. Our research also proposes a policy priority for the first-best system optimal inventory management.

The Cooperative Game Theory is a scientific discipline which offers rich mathematical apparatus for describing complex situations in the social reality. Its apparatus includes an extension to hierarchical structures and therefore can be applied to numerous research problems from the International Relations field. However, a cooperative game theoretical approach is very scarcely used. The main goal of the diploma thesis is to demonstrate, on the research problem of decision making in participation in local conflicts, the benefits of results that can be achieved by the application of the Cooperative Game Theory. In the first part of the thesis, theoretical foundations are laid and basic concepts are introduced. The second part is focused on forming a series of models of cooperative games with hierarchical structures from four local conflict situations, which are subsequently restricted in order to describe authoritative relations in structure. Restricted games are solved, the results are interpreted and evaluation of how these results can contribute to addressing the research problem follows.

Shale gas has emerged as a potential resource to transform the global energy market. Nevertheless, gas extraction from tight shale formations is only possible after horizontal drilling and hydraulic fracturing, which generally demand large amounts of water. Part of the ejected fracturing fluid returns to the surface as flowback water, containing a variety of pollutants. Thus, water reuse and water recycling technologies have received further interest for enhancing overall shale gas process efficiency and sustainability. Thereby, the objectives of this thesis are: - Develop mathematical models to treat flowback and produced water at various salinities and flow rates, decreasing the high environmental impact due to the freshwater withdrawal and wastewater generated during shale gas production at minimum cost. - Develop mathematical programming models for planning shale gas water management through the first stage of the well's life to promote the reuse of flowback water by optimizing simultaneously all operations belonging several wellpads. Within the first objective, we developed medium size generalized disjunctive-programming (GDP) models reformulated as mixed integer non-linear programming problems (MINLPs). First, we focused on flowback water pretreatment and later, in wastewater desalination treatment. Particularly, an emergent desalination technology, Membrane Distillation, has been studied. All mathematical models have been implemented using GAMS® software. First, we introduce a new optimization model for wastewater from shale gas production including a superstructure with several water pretreatment alternatives. The mathematical model is formulated via GDP to minimize the total annualized cost. Hence, the superstructure developed allows identifying the optimal pretreatment sequence with minimum cost, according to inlet water composition and wastewater desired destination (i.e., water reuse as fracking fluid or desalination in thermal or membrane techonologies). As each destination requires specific composition constraints, three case studies illustrate the applicability of the proposed approach. Additionally, four distinct flowback water compositions are evaluated for the different target conditions. The results highlight the ability of the developed model for the cost-effective water pretreatment system synthesis, by reaching the required water compositions for each specified destination. Regarding desalination technologies, a rigorous optimization model with energy recovery for the synthesis of multistage direct contact membrane distillation (DCMD) system has been developed. The mathematical model is focused on maximizing the total amount of water recovered. The outflow brine is fixed close to salt saturation conditions (300 g·kg-1) approaching zero liquid discharge (ZLD). A sensitivity analysis is performed to evaluate the system’s behavior under different uncertainty sources such as the heat source availability and inlet salinity conditions. The results emphasize the applicability of this promising technology, especially with low steam cost or waste heat, and reveal variable costs and system configurations depending on inlet conditions. Within the second objective, large-scale multi-period water management problems, and collaborative water management models have been studied. Thus, to address water planning decisions in shale gas operations, in a first stage a new non-convex MINLP optimization model is presented that explicitly takes into account the effect of high concentration of total dissolved solids (TDS) and its temporal variations in the impaired water. The model comprises different water management strategies: direct reuse, treatment or send to Class II disposal wells. The objective is to maximize the “sustainability profit” to find a compromise solution among the three pillars of sustainability: economic, environmental and social criteria. The solution determines freshwater consumption, flowback destination, the fracturing schedule, fracturing fluid composition and the number of tanks leased at each time period. Because of the rigorous determination of TDS in all water streams, the model is a nonconvex MINLP model that is tackled in two steps: first, an MILP model is solved on the basis of McCormick relaxations for the bilinear terms; next, the binary variables that determine the fracturing schedule are fixed, and a smaller MINLP is solved. Finally, several case studies based on Marcellus Shale Play are optimized to illustrate the effectiveness of the proposed formulation. Later, a simplified version of the shale gas water management model developed in the previous work has been used to study possible cooperative strategies among companies. This model allows increasing benefits and reduces costs and environmental impacts of water management in shale gas production. If different companies are working in the same shale zone and their shale pads are relatively close (under 50 km), they might adopt a cooperative strategy, which can offer economic and environmental advantages. The objective is to compute a distribution of whatever quantifiable unit among the stakeholders to achieve a stable agreement on cooperation among them. To allocate the cost, profit and/or environmental impact among stakeholders, the Core and Shapley value are applied. Finally, the impact of cooperation among companies is shown by two examples involving three and eight players, respectively. The results show that adopting cooperative strategies in shale water management, companies are allowed to improve their benefits and to enhance the sustainability of their operations. The results obtained in this thesis should help to make cost-effective and environmentally-friendly water management decisions in the eventual development of shale gas wells.

Diese Dissertation präsentiert Modelle zur Lösung von Verhandlungsproblemen mit diskreten Strukturen. Hauptgrundlage der Betrachtung ist dabei die Erweiterung und Anwendung von Theorien der kooperativen Spieltheorie. Insbesondere der Shapley-Wert spielt eine wichtige Rolle. Als erste Problemklasse werden kooperative Spiele präsentiert, bei denen einige Spiele feste Auszahlungen erhalten. Als zweite Problemklasse werden kooperative Spiele untersucht, deren Lösungen ausschließlich ganzzahlig sein dürfen.