With the increasing importance of electronic commerce across the Internet it is becoming increasingly evident that in a few years the Internet will host large numbers of interacting software agents. A vast number of t...
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(纸本)9780769519326
With the increasing importance of electronic commerce across the Internet it is becoming increasingly evident that in a few years the Internet will host large numbers of interacting software agents. A vast number of them will be economically motivated, and will exchange a variety of goods and services. It is therefore important to consider the economic incentives and behaviours of economic software agents, and to use every available means to anticipate their collective interactions. We address this concern by presenting a market simulator designed for analysing agent market strategies based on a complete understanding of buyer and seller behaviours, preference model and pricing algorithms.
As electric utility systems around the world continue to move towards open, competitive markets, the need for new modeling techniques will become more obvious. To study electricity markets behaviour and evolution we p...
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As electric utility systems around the world continue to move towards open, competitive markets, the need for new modeling techniques will become more obvious. To study electricity markets behaviour and evolution we propose a multi-agent simulator where agents represent several entities that can be found in electricity markets, such as generators, consumers, market operators and network operators, but also entities that are emerging with the advent of liberalization, such as traders. The simulator probes the possible effects of market rules and conditions by simulating the strategic behaviour of participants. In this paper a special attention is devoted to the strategic decision processes of seller, buyer and trader agents, in order to gain advantage facing the new emerging competitive market.
Scheduling algorithms that achieve good or near optimal solutions and can efficiently adapt them to perturbations are, in most cases, preferable to those that achieve optimal ones but that cannot implement such an ada...
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Scheduling algorithms that achieve good or near optimal solutions and can efficiently adapt them to perturbations are, in most cases, preferable to those that achieve optimal ones but that cannot implement such an adaptation. In fact, in real world, where problems are essentially of dynamic and stochastic nature, these methods or algorithms are of very little use. This is the case with most algorithms for solving the so-called static scheduling problem for different setting of both single and multi-machine systems arrangements. This paper is concerned with a scheduling system, based on Genetic Algorithms, for the resolution of the dynamic version of the same problem. An additional constraint will be considered in our approach for the JSSP, the existence of different job release and due dates and different assembly levels for the jobs.
This paper is concerned with the implementation of Simultaneous Manufacturing philosophy in batch production of job-shop like manufacturing systems. It addresses the processing of jobs, either simple, requiring the ma...
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This paper is concerned with the implementation of Simultaneous Manufacturing philosophy in batch production of job-shop like manufacturing systems. It addresses the processing of jobs, either simple, requiring the manufacture of a batch of parts, i.e. simple products, or complex, comprehending the parts fabrication and their multistage assembly into a batch of products. In this work the simultaneous manufacturing philosophy was implemented through the widespread use of batch overlapping, which proved particularly effective in reducing job throughput time, maintaining operating simplicity and requiring reduced coordination.
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