A theoretical and computational basis for CATNETS

The main content of this report is the identification and definition of market mechanisms for Application Layer Networks (ALNs). On basis of the structured Market Engineering process, the work comprises the identification of requirements which adequate market mechanisms for ALNs have to fulfill. Subsequently, two mechanisms for each, the centralized and the decentralized case are described in this document. These build the theoretical foundation for the work within the following two years of the CATNETS project. --Grid Computing

Supply Chain

Traditionally supply chain management has meant factories, assembly lines, warehouses, transportation vehicles, and time sheets. Modern supply chain management is a highly complex, multidimensional problem set with virtually endless number of variables for optimization. An Internet enabled supply chain may have just-in-time delivery, precise inventory visibility, and up-to-the-minute distribution-tracking capabilities. Technology advances have enabled supply chains to become strategic weapons that can help avoid disasters, lower costs, and make money. From internal enterprise processes to external business transactions with suppliers, transporters, channels and end-users marks the wide range of challenges researchers have to handle. The aim of this book is at revealing and illustrating this diversity in terms of scientific and theoretical fundamentals, prevailing concepts as well as current practical applications

Auctioning Bulk Mobile Messages

The search for enablers of continued growth of SMS traffic, as well asthe take-off of the more diversified MMS message contents, open up forenterprises the potential of bulk use of mobile messaging , instead ofessentially one-by-one use. In parallel, such enterprises or valueadded services needing mobile messaging in bulk - for spot use or foruse over a prescribed period of time - want to minimize totalacquisition costs, from a set of technically approved providers ofmessaging capacity.This leads naturally to the evaluation of auctioning for bulk SMS orMMS messaging capacity, with the intrinsic advantages therein such asreduction in acquisition costs, allocation efficiency, and optimality.The paper shows, with extensive results as evidence from simulationscarried out in the Rotterdam School of Management e-Auction room, howmulti-attribute reverse auctions perform for the enterprise-buyer, aswell as for the messaging capacity-sellers. We compare 1- and 5-roundauctions, to show the learning effect and the benefits thereof to thevarious parties. The sensitivity will be reported to changes in theenterprise's and the capacity providers utilities and prioritiesbetween message attributes (such as price, size, security, anddelivery delay). At the organizational level, the paper also considersalternate organizational deployment schemes and properties for anoff-line or spot bulk messaging capacity market, subject to technicaland regulatory constraints.MMS;EMS;Mobile commerce;SMS;multi-attribute auctions

Theoretical and Computational Basis for Economical Ressource Allocation in Application Layer Networks - Annual Report Year 1

This paper identifies and defines suitable market mechanisms for Application Layer Networks (ALNs). On basis of the structured Market Engineering process, the work comprises the identification of requirements which adequate market mechanisms for ALNs have to fulfill. Subsequently, two mechanisms for each, the centralized and the decentralized case are described in this document. --Grid Computing

Efficient coalition formation and stable coalition structures in a supply chain environment

We study a real supply chain environment from which specific information and knowledge can be extrapolated for other similar environments. We focus our research on the analysis of the interactions between members forming different teams (and between the teams themselves), and on the leader’s management of the supply chain. We note that there are many elements that contribute to the profitability of the network, which is dependent on the actions of the actors involved. We analyze certain characteristics that the actors have, such as their behavior, adaptation and learning levels, effort and willingness. Based on these components, we examine the performance of our actors and of the teams that the actors form. We provide specific calculations that take into account most of the components determining the added value to the system. One of the advantages of our main formula is that it can be used to monitor the progress of the actors, as well as it can help in the identification of problematic aspects impeding in the creation of value for the system. Our formula is very flexible and a modeler is able to adapt it to similar environments, providing him with great insight in the structures that he investigates. We study certain theoretical games from which we uncover certain information and characteristics of similar environments and settings. Moreover, we provide a real life example in order to truly understand the mechanism of the network, and validate our theoretical assessments. Moreover, we provide certain recommendations for a leader that is responsible for the supervision of actors (which have specific responsibilities) and the administration of a supply chain environment.coalition, supply chain management, core, value of the game, Coalition Factor Estimation

Collaborative Models for Supply Networks Coordination and Healthcare Consolidation

This work discusses the collaboration framework among different members of two complex systems: supply networks and consolidated healthcare systems. Although existing literature advocates the notion of strategic partnership/cooperation in both supply networks and healthcare systems, there is a dearth of studies quantitatively analyzing the scope of cooperation among the members and its benefit on the global performance. Hence, the first part of this dissertation discusses about two-echelon supply networks and studies the coordination of buyers and suppliers for multi-period procurement process. Viewing the issue from the same angel, the second part studies the coordination framework of hospitals for consolidated healthcare service delivery. Realizing the dynamic nature of information flow and the conflicting objectives of members in supply networks, a two-tier coordination mechanism among buyers and suppliers is modeled. The process begins with the intelligent matching of buyers and suppliers based on the similarity of users profiles. Then, a coordination mechanism for long-term agreements among buyers and suppliers is proposed. The proposed mechanism introduces the importance of strategic buyers for suppliers in modeling and decision making process. To enhance the network utilization, we examine a further collaboration among suppliers where cooperation incurs both cost and benefit. Coalitional game theory is utilized to model suppliers\u27 coalition formation. The efficiency of the proposed approaches is evaluated through simulation studies. We then revisit the common issue, the co-existence of partnership and conflict objectives of members, for consolidated healthcare systems and study the coordination of hospitals such that there is a central referral system to facilitate patients transfer. We consider three main players including physicians, hospitals managers, and the referral system. As a consequence, the interaction within these players will shape the coordinating scheme to improve the overall system performance. To come up with the incentive scheme for physicians and aligning hospitals activities, we define a multi-objective mathematical model and obtain optimal transfer pattern. Using optimal solutions as a baseline, a cooperative game between physicians and the central referral system is defined to coordinate decisions toward system optimality. The efficiency of the proposed approach is examined via a case study

Fairness in online vehicle-cargo matching: An intuitionistic fuzzy set theory and tripartite evolutionary game approach

This paper explores the concept of fairness and equitable matching in an on-line vehicle-cargo matching setting, addressing the varying degrees of satisfaction experienced by shippers and carriers. Relevant indicators for shippers and carriers in the on-line matching process are categorized as attributes, expectations, and reliability, which are subsequent quantified to form satisfaction indicators. Employing the intuitionistic fuzzy set theory, we devise a transformed vehicle-cargo matching optimization model by combining the fuzzy set's membership, non-membership, and uncertainty information. Through an adaptive interactive algorithm, the matching scheme with fairness concerns is solved using CPLEX. The effectiveness of the proposed matching mechanism in securing high levels of satisfaction is established by comparison with three benchmark methods. To further investigate the impact of considering fairness in vehicle-cargo matching, a shipper-carrier-platform tripartite evolutionary game framework is developed under the waiting response time cost (WRTC) sharing mechanism. Simulation results show that with fairness concerns in vehicle-cargo matching, all stakeholders are better off: The platform achieves positive revenue growth, and shippers and carriers receive positive subsidy. This study offers both theoretical insights and practical guidance for the long-term and stable operation of the on-line freight stowage industry.Comment: 36 pages, 15 figure

Intelligent Operation System for the Autonomous Vehicle Fleet

Modular vehicles are vehicles with interchangeable substantial components also known as modules. Fleet modularity provides extra operational flexibility through on-field actions, in terms of vehicle assembly, disassembly, and reconfiguration (ADR). The ease of assembly and disassembly of modular vehicles enables them to achieve real-time fleet reconfiguration, which is proven as beneficial in promoting fleet adaptability and in saving ownership costs. The objective of military fleet operation is to satisfy uncertain demands on time while providing vehicle maintenance. To quantify the benefits and burdens from modularity in military operation, a decision support system is required to yield autonomously operation strategies for comparing the (near) optimal fleet performance for different vehicle architectures under diverse scenarios. The problem is challenging because: 1) fleet operation strategies are numerous, especially when modularity is considered; 2) operation actions are time-delayed and time-varying; 3) vehicle damages and demands are highly uncertain; 4) available capacity for ADR actions and vehicle repair is constrained. Finally, to explore advanced tactics enabled by fleet modularity, the competition between human-like and adversarial forces is required, where each force is capable to autonomously perceive and analyze field information, learn enemy's behavior, forecast enemy's actions, and prepare an operation plan accordingly. Currently, methodologies developed specifically for fleet competition are only valid for single type of resources and simple operation rules, which are impossible to implement in modular fleet operation. This dissertation focuses on a new general methodology to yield decisions in operating a fleet of autonomous military vehicles/robots in both conventional and modular architectures. First, a stochastic state space model is created to represent the changes in fleet dynamics caused by operation actions. Then, a stochastic model predictive control is customized to manage the system dynamics, which is capable of real-time decision making. Including modularity increases the complexity of fleet operation problem, a novel intelligent agent based model is proposed to ensure the computational efficiency and also imitate the collaborative decisions making process of human-like commanders. Operation decisions are distributed to several agents with distinct responsibility. Agents are designed in a specific way to collaboratively make and adjust decisions through selectively sharing information, reasoning the causality between events, and learning the other's behavior, which are achieved by real-time optimization and artificial intelligence techniques. To evaluate the impacts from fleet modularity, three operation problems are formulated: (i) simplified logistic mission scenario: operate a fleet to guarantee the readiness of vehicles at battlefields considering the stochasticity in inventory stocks and mission requirements; (ii) tactical mission scenario: deliver resources to battlefields with stochastic requirements of vehicle repairs and maintenance; (iii) attacker-defender game: satisfy the mission requirements with minimized losses caused by uncertain assaults from an enemy. The model is also implemented for a civilian application, namely the real-time management of reconfigurable manufacturing systems (RMSs). As the number of RMS configurations increases exponentially with the size of the line and demand changes frequently, two challenges emerge: how to efficiently select the optimal configuration given limited resources, and how to allocate resources among lines. According to the ideas in modular fleet operation, a new mathematical approach is presented for distributing the stochastic demands and exchanging machines or modules among lines (which are groups of machines) as a bidding process, and for adaptively configuring these lines and machines for the resulting shared demand under a limited inventory of configurable components.PHDMechanical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/147588/1/lixingyu_2.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/147588/2/lixingyu_1.pd