Auctions have been used to deal with resource allocation in multiagent environments, especially in serviceoriented electronic markets. In this type of market, resources are perishable and auctions are repeated over time with the same or a very similar set of agents. In this scenario it is advisable to use recurrent auctions: a sequence of auctions of any kind where the result of one auction may influence the following one. Some problems do appear in these situations, as for instance, the bidder drop problem, the asymmetric balance of negotiation power or resource waste, which could cause the market to collapse. Fair mechanisms can be useful to minimize the effects of these problems. With this aim, we have analyzed four previous fair mechanisms under dynamic scenarios and we have proposed a new one that takes into account changes in the supply as well as the presence of alternative marketplaces. We experimentally show how the new mechanism presents a higher average performance under all simulated conditions, resulting in a higher profit for the auctioneer than with the previous ones, and in most cases avoiding the waste of resources.

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When selfish industries are competing for limited shared resources, they need to coordinate their activities to handle possible conflicting situations. Moreover, this coordination should not affect the activities already planned by the industries, since this could have negative effects on their performance. Although agents may have buffers that allow them to delay the use of resources, these are of a finite capacity, and therefore cannot be used indiscriminately. Thus, we are faced with the problem of coordinating schedules that have already been generated by the agents. To address this task, we propose to use a recurrent auction mechanism to mediate between the agents. Through this auction mechanism, the agents can express their interest in using the resources, thus helping the scheduler to find the best distribution. We also introduce a priority mechanism to add fairness to the coordination process. The proposed coordination mechanism has been applied to a waste water treatment system scenario, where different industries need to discharge their waste. We have simulated the behavior of the system, and the results show that using our coordination mechanism the waste water treatment plant can successfully treat most of the discharges, while the production activity of the industries is almost not affected by it.

Immobile Location-Allocation (ILA) is a combinatorial problem which consists in, given a set of facilities and a set of demand points, determining the optimal service each facility has to offer and allocating the demand to such facilities. The applicability of optimization methods is tied up to the dimensionality of the problem, but since the distance between data points is a key factor, clustering techniques to partition the data space can be applied, converting the large initial problem into several simpler ILA problems that can be solved separately. This paper presents a novel method that combines clustering and heuristic methods to solve an ILA problem, which reduces the elapsed time keeping the quality of the solution found compared with other heuristics methods.

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