Ricardo del Olmo Martínez

Price Updating in Combinatorial Auctions for Coordination of Manufacturing Multiagent Systems

In this work we use the paradigm of multiagent systems to solve the Job Shop problem. Job Shop problem is a particular problem of scheduling in which we try to find an schedule that optimize a objective and is subject to certain constraints. We propose a combinatorial auction mechanism to coordinate agents. The “items” to be sold are the time slots that we divide the time horizon into. In tasks scheduling problems tasks need a combination of time slots of multiple resources to do the operations. The use of auctions in which different valuations of interdependent items are considered (e.g. combinatorial auctions) is necessary. A certain time slot will be more valuated to the extent that it enables task to finish the job on time, together with the other time slot bought. Job-agents are price-takers in the model. The auctioneer fixes prices comparing the demand over a time slot of a resource with the capacity of the resource in this time slot. There are many ways to update prices (e.g. constant increase or decrease of prices, proportional to the demand, proportional to the excess of demand). Our objective is to compare the different methods of updating prices based on those of the lagrangian relaxation solving method.

Easing knowledge management in the power sector by means of a neuro-genetic system

A hybrid intelligent system that combines neural networks and genetic algorithms for feature selection is proposed in this paper. In the world of companies, it is widely acknowledged the importance of knowledge management KM in terms of organisation survival and maintenance of competitive strength. Furthermore, in the energy sector, it is even more critical as energy is a strategic national industry for most countries. However, there are not enough tools with which to systematise the work of KM and to provide support for decision-making. The present study proposes a tool that addresses the problem of selecting the features of KM from the immense amount of available data that would provide managers with most valuable information. The developed system has been applied to real-world data from a power plant, to mine deep knowledge on that KM data, and to select the most informative features. Experimental results justify a meaningful subset of features in the opinion of KM experts, and validate the proposed hybrid system.

Knowledge and Innovation in the New Industrial Organization

The objective of this work is to study “The New Industrial Organization” (Hernandez 1997) and its implications for knowledge, cooperative relations and business innovation. This objective implies understanding the close and meaningful connection between Economics, Business Organization and Strategic Management. In doing so, we point out that two intangible factors, knowledge and cooperative relations between the agents of the firm are the basis of business profitability, through their impact on innovation. Innovation exists to convert knowledge into products and services that will attract the customers. Competitiveness emerges here, when those goods and services are unique and generate value for the customers, who are willing not only to acquire them, but also to pay the set price, and ultimate being an agent of the firm. The challenge consists in offering, today as ever, products and services that are yet to be found on the market, so that the firm will not be marginalized and abandoned by the customers, now a an agent of the firm´s network. Knowledge, together with the innovative capabilities of people, opens up an enormous space for the firm, which leads to continuous progress full of opportunities and future.

The New Industrial Organization

Economic Activity takes two alternative forms: the Market and the Firm. Economics is a social science that tries to explain how to generate wealth and how it is distributed. The firm is a social organization whose members decide to cooperate to generate wealth and its distribution among the stakeholders. They certainly share a common goal. However, to translate economic principles to management is an open challenge. Traditional IO as understood among the economists deals with the generation of wealth through the market, which if it is well designed will achieve a fair distribution through endogenous dynamics towards equilibrium. On the other hand, a proper theory of the firm needs explicit rules of governance and operations. This fact requires a New I.O dealing with uncertainty far beyond probability; individual and collective bounded rational agents; specialization and heterogeneity; imperfect information and variety; incentives and penalties to avoid free riding, and how to develop core competences such as entrepreneurship, innovation and knowledge management. The paper revised I.O and ends up with a map of Management Sciences to help designing the Management Engineering curricula and the range of specific skills and competences demanded by different institutions.

Price-Setting Combinatorial Auctions for Coordination and Control of Manufacturing Multiagent Systems: Updating Prices Methods

Combinatorial auctions are used as a distributed coordination mechanism in Multiagent Systems. The use of combinatorial auctions as negotiation and coordination mechanism is especially appropriate in systems with interdependencies and complementarities such as manufacturing scheduling systems. In this work we review some updating price mechanisms for combinatorial auctions based on the Lagrangian Relaxation Method. We focus our research to solve the optimization scheduling problem in the shop floor, taking into account the objectives of resource allocation in dynamic environments, i.e. -robustness, stability, adaptability, and efficiency-.

Combinatorial Auctions for Coordination and Control of Manufacturing MAS: Updating Prices Methods

We use the paradigm of multiagent systems to solve the Job Shop problem. It concerns the allocation of machines to operations of some production process over time periods and its goal is the optimization of one or several objectives. We propose a combinatorial auction mechanism to coordinate agents. The “items” to be sold are the time slots that we divide the time horizon into. In tasks scheduling problems tasks need a combination of time slots of multiple resources to do the operations. The use of auctions in which different valuations of interdependent items are considered (e.g. combinatorial auctions) is necessary. The auctioneer fixes prices comparing the demand over a time slot of a resource with the capacity of the resource in this time slot. Our objective is to find an updating price method for combinatorial auctions that meet the needings of scheduling manufacturing systems in dynamic environments, e.g. robustness, stability, adaptability, and efficient use of available resources.