Purchasing activities consume more than half of manufacturing and trading organizations sales capitals. Quality procurement is tied with efficient and highly accurate collection of data needed to purchasing the right ...
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(纸本)9780769550732
Purchasing activities consume more than half of manufacturing and trading organizations sales capitals. Quality procurement is tied with efficient and highly accurate collection of data needed to purchasing the right material at the right quality from right suppliers. Supply chain management (SCM) consists of complex networks of distributed actors in which the problem of identifying the appropriate suppliers based on specific criteria is strategically important. However, implementation of an autonomous assessment that can incorporate dynamics and uncertainty of the whole supply chain during the assessment period is not addressed in most of the previous research activities. In this paper, a review of the use and development of agent-basedmodeling and simulation (ABMS) approach in the supplier selection problem domain is provided. The main focus of this paper is to extract and analyze significant issues related to modeling and simulating supplier selection networks using Multi agent System (MAS) approach. Related research domain is evaluated and synthesized considering six different perspectives. The review also sheds light on the weak points of current research in this area. Also, it illuminates a number of key issues which need to be considered in advancing an agent-based assessment model for future applications in supplier selection problem.
Every weapon system operates in context with one or more system of systems (SoS). Generally, it is the SoS that provides warfighting capability. However, each system is managed independently by a program office with p...
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Every weapon system operates in context with one or more system of systems (SoS). Generally, it is the SoS that provides warfighting capability. However, each system is managed independently by a program office with program-centric priorities: requirements, funding and schedule. As needed, these systems must be interconnected and interoperable, so the program office must collaborate across the SoS with other program offices. Thus, the SoS and the constituent systems are always changing and evolving, triggered by users needs, new threats and various stakeholders demands. Acquisition program offices can be characterized with a set of inherent organizational behaviors that respond to the environment, are influenced by the SoS architecture, and can be described by their fitness and contribution to the SoS. Using Geert Hofstede's cultural dimensions, integrated with a modified version of the Bak- Sneppen biological evolutionary model, this research highlights which set of behaviors are significant in affecting the overall SoS fitness. Through the use of agentbasedmodeling, it was determined that the organizational behaviors of willingness and ability were significant factors to predict local fitness with a correlation of 0.548 and 0.535 respectively. Using these factors with local fitness, a regression model was built to better predict the local fitness of the system. Global fitness was highly dependent on the influence from connected systems, which surprisingly remained highly stable throughout different modeling variations in learning strategies, prior fitness contribution, trigger types, selection percentage, and fitness degradation efforts. This first-of-its-kind research provides a starting point into complex integration of organizational behavior and SoS architecture and their impact on acquiring and delivering warfighter capabilities.
Purpose - The purpose of this paper is to investigate the benefits and the barriers of agentbased decision support.(ABDS) systems in the supply chain context. Design/methodology/approach - Two ABDS systems have been ...
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Purpose - The purpose of this paper is to investigate the benefits and the barriers of agentbased decision support.(ABDS) systems in the supply chain context. Design/methodology/approach - Two ABDS systems have been developed and evaluated. The first system concerns a manufacturing supply chain while the second concerns a service supply chain. The systems are based on actual case companies. Findings - This research shows that the benefits of ABDS systems in the supply chain context include the possibility to increase versatility of system architecture, to improve supply chain visibility, to conduct experiments and what-if analyses, to improve the understanding of the real system, and the possibility to improve communication within and between organizations in the supply chain. The barriers of ABDS systems in the supply chain context include the difficulty to access data from partners in the supply chain, the difficulty to access data on a higher level of granularity, and the difficulty to retrieve data from other information systems. Research limitations/implications - The research is explorative in nature therefore empirical data from similar and other research settings should be gathered to reinforce the validity of the findings. Practical implications - This research provides knowledge and insights on how ABDS systems may be developed and used in the supply chain context and demonstrates its main benefits and barriers. Originality/value - This research expands the current research of benefits of ABDS systems to the supply chain domain and also addresses the barriers of ABDS systems to a larger extent than previous research. Comparisons to other simulationbased decision support systems are also given.
Although many meta-heuristic algorithms were developed for solving combinatorial optimization problems, very few of them were realized in an agentbased environment. Especially the algorithms which model dynamics of A...
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Although many meta-heuristic algorithms were developed for solving combinatorial optimization problems, very few of them were realized in an agentbased environment. Especially the algorithms which model dynamics of Artificial Immune Systems (AIS) are population based approaches with adaptability characteristics, therefore AIS can be better realized in an agentbasedmodeling environment. For this purpose first time in the literature a clonal selection algorithm which is an AIS based algorithm is modeled in a multi-agent environment for solving the travelling salesmen problem which is a combinatorial optimization problem. In order to observe the behavior of the algorithm, simulation experiments are carried out on several test problems. Netlogo software is utilized for developing agentbased models and simulation tests. Moreover, receptor change process and crossover mechanisms are integrated into the proposed model in order to improve the performance of the classical clonal selection algorithm. It is shown that there is a high potential to obtain good solution by making use of agent oriented approaches which more realistically model the natural phenomenon.
Force Transformation requires a much greater emphasis on testing joint warfighting capabilities. A unique challenge in assessing the effectiveness and suitability of systems in the joint environment is the multitude o...
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Force Transformation requires a much greater emphasis on testing joint warfighting capabilities. A unique challenge in assessing the effectiveness and suitability of systems in the joint environment is the multitude of possible interactions and outcomes in a system-of-systems construct. Because of resource constraints and the complexity of conducting live, virtual, and constructive testing in a joint mission environment, the Joint Test and Evaluation Methodology (JTEM) program is interested in determining if analytical techniques, like modeling and simulation, can be applied to understand the relationship between system- of-systems performance and joint mission effectiveness. As a proof of concept, a Network Enabled Weapon (NEW) was chosen as a framework for this study. This thesis uses an agent-based distillation, which is a type of computer simulation, to model the critical factors of interest in a NEW engagement without explicitly modeling all of the physical details. Using cutting-edge experimental design techniques, the computer model was run many tens of thousands of times, with the results being analyzed to determine the critical parameters required for mission success. The analysis determined key interactions in NEW system performance and provides JTEM with a framework for efficiently conducting testing in a live environment. Specifically, the results indicate sensor range of a third-party ground controller, target speed, NEW impact radius, and weapon accuracy as the key factors affecting system performance.
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