Automated negotiation by software agents is a key enabling technology for agent mediated e-commerce. To this end, this paper considers an important class of such negotiations -namely those in which an agent engages in multiple concurrent bilateral negotiations for a good or service. In particular, we consider the situation in which a buyer agent is looking for a single service provider from a number of available ones in its environment. By bargaining simultaneously with these providers and interleaving partial agreements that it makes with them, a buyer can reach good deals in an efficient manner. However, a key problem in such encounters is managing commitments since an agent may want to make intermediate deals (so that it has a definite agreement) with other agents before it gets to finalize a deal at the end of the encounter. To do this effectively, however, the agents need to have a flexible model of commitments that they can reason about in order to determine when to commit and to decommit. This paper provides and evaluates such a commitment model and integrates it into a concurrent negotiation model.
Virtual organisations (VOs) are composed of a number of individuals, departments or organisations each of which has a range of capabilities and resources at their disposal. These VOs are formed so that resources may be pooled and services combined with a view to exploiting a perceived market niche. However, in the modern commercial environment it is essential to respond rapidly to changes in the market to remain competitive. Thus, there is a need for robust, agile, flexible systems to support the process of VO management. Within the CONOISE (www.conoise.org) project, agent-based models and techniques are being developed for the automated formation and maintenance of virtual organisations. In this paper we focus on the former, namely how an effective VO may be formed rapidly for a specified purpose. q
Virtual organisations (VOs) are composed of a number of individuals, departments or organisations each of which has a range of capabilities and resources at their disposal. These VOs are formed so that resources may be pooled and services combined with a view to the exploitation of a perceived market niche. However, in the modern commercial environment it is essential to respond rapidly to changes in the market to remain competitive. Thus, there is a need for robust, flexible systems to support the process of VO management. Within the CONOISE (www.conoise.org) project, agent-based models and techniques are being developed for the automated formation and maintenance of virtual organisations. In this paper we focus on a critical element of VO management: how an effective VO may be formed rapidly for a specified purpose.
Highlights• We propose a new nested-LPs-based approach for finding the nucleolus• We resolve subtle issues in handling multiple optimal solutions in each LP• The approach involves fewer and smaller LPs compared to existing methods• The approach proves to work well in several large combinatorial games
AbstractThe nucleolus is one of the most important solution concepts in cooperative game theory as a result of its attractive properties -it always exists (if the imputation is non-empty), is unique, and is always in the core (if the core is non-empty). However, computing the nucleolus is very challenging because it involves the lexicographical minimization of an exponentially large number of excess values. We present a method for computing the nucleoli of large games, including some structured games with more than 50 players, using nested linear programs (LP). Although different variations of the nested LP formulation have been documented in the literature, they have not been used for large games because of the large size and number of LPs involved. In addition, subtle issues such as how to deal with multiple optimal solutions and with tight constraint sets need to be resolved in each LP in order to formulate and solve the subsequent ones. Unfortunately, this technical issue has been largely overlooked in the literature. We treat these issues rigorously and provide a new nested LP formulation that is smaller in terms of the number of large LPs and their sizes. We provide numerical tests for several games, including the general flow games, the coalitional skill games and the weighted voting games, with up to 100 players.
We present an optimization model for dragon fruit plantations in Vietnam. The timing of cultivating and harvesting decisions are taken into account as the dragon fruit plant has an approximately ten-year life cycle with maximum average yield in the fourth year. Another consideration also included is the prevalence of forward-buying contracts with locked-in prices. The dragon fruit supply chain faces several difficulties as yield, price, and demand are highly sensitive to weather conditions and global uncertainty factors. The risk factors in the dragon fruit supply chain also depend on species-for example, the red varieties, while more profitable than the white varieties, also have higher export risk because they are subject to global prices and adverse geopolitical conditions.
The short-term unit commitment and reserve scheduling decisions are made in the face of increasing supply-side uncertainty in power systems. This has mainly been caused by a higher penetration of renewable energy generation that is encouraged and enforced by the market and policy makers. In this paper, we propose a two-stage stochastic and distributionally robust modeling framework for the unit commitment problem with supply uncertainty. Based on the availability of the information on the distribution of the random supply, we consider two specific models: (a) a moment model where the mean values of the random supply variables are known, and (b) a mixture distribution model where the true probability distribution lies within the convex hull of a finite set of known distributions. In each case, we reformulate these models through Lagrange dualization as a semi-infinite program in the former case and a one-stage stochastic program in the latter case. We solve the reformulated models The research of this author is supported by EPSRC Grant EP/M003191/1. using sampling method and sample average approximation, respectively. We also establish exponential rate of convergence of the optimal value when the randomization scheme is applied to discretize the semi-infinite constraints. The proposed robust unit commitment models are applied to an illustrative case study, and numerical test results are reported in comparison with the two-stage non-robust stochastic programming model.
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