Fairs for e-commerce: the benefits of aggregating buyers and sellers

In recent years, many new and interesting models of successful online business have been developed. Many of these are based on the competition between users, such as online auctions, where the product price is not fixed and tends to rise. Other models, including group-buying, are based on cooperation between users, characterized by a dynamic price of the product that tends to go down. There is not yet a business model in which both sellers and buyers are grouped in order to negotiate on a specific product or service. The present study investigates a new extension of the group-buying model, called fair, which allows aggregation of demand and supply for price optimization, in a cooperative manner. Additionally, our system also aggregates products and destinations for shipping optimization. We introduced the following new relevant input parameters in order to implement a double-side aggregation: (a) price-quantity curves provided by the seller; (b) waiting time, that is, the longer buyers wait, the greater discount they get; (c) payment time, which determines if the buyer pays before, during or after receiving the product; (d) the distance between the place where products are available and the place of shipment, provided in advance by the buyer or dynamically suggested by the system. To analyze the proposed model we implemented a system prototype and a simulator that allow to study effects of changing some input parameters. We analyzed the dynamic price model in fairs having one single seller and a combination of selected sellers. The results are very encouraging and motivate further investigation on this topic

Agent-based coalitions in dynamic supply chains

Coalition formation is an important issue in multi-agent systems. Recent work in the area has focused on reducing the complexity of forming coalitions, i.e., each agent deliberately searches for potential coalition members before negotiating with them. We propose a framework for coalition formation of agents in a dynamic supply chain environment. The framework is composed of a negotiation protocol and a decision mechanism. The negotiation protocol allows thorough communication among agents across sectors (buyers, sellers, logistic providers). With the decision mechanism, agents take two steps to form coalitions: i) agents in each sector form loosely-coupled coalitions in order to decrease the complexity of the negotiation, and ii) agents form coalitions across sectors in order to deliver goods to end customers. We provide an example of how they can help agents form coalitions successfully

A Framework to Support Coalition Formation in Supply Chain Collaboration

This paper proposes a framework for agents in globally collaborative supply chain by applying the concept of coalition formation, a cooperation game in game theory. This framework provides mutual benefits to every party involved buyers, sellers and logistics providers. It provides a common gateway that allows individual parties to locate the right partners, negotiate with them, and form coalition in the best possible ways. The framework is applicable to real world e-business models, including B2C, B2B, supply chain and logistics, SME, etc. We firstly discuss common needs existing in today e-business. We then discuss about our framework, i.e., negotiation protocol and decision mechanism

A genetic algorithm for group formation in elderly communities

Over the last few years, agent technology has proposed different approaches for the development of systems that support the formation and dynamic management of teams or groups. Following this idea, this paper proposes a model for group formation in elderly communities defining it as a Coalition Structure Generation Problem. Specifically, the proposal has been used to analyse which is the best way to organize older people into activity groups in elderly communities. The model parameters are physical requirements, preferences and social relationships, being the model able to learn from each execution and improve the future configurations. The results show near-optimal solutions to all proposed scenarios, beating greatly the computational time of CPLEX, and flexibility to deal with different scenarios and configurations.- This work has been supported by COMPETE: POCI-01-0145-FEDER-007043 and FCT - Fundacao para a Ciencia e Tecnologia within the Project Scope: UID/CEC/00319/2013. A. Costa thanks the FCT - Fundacao para a Ciencia e Tecnologia the Post-Doc scholarship with the Ref. SFRH/BPD/102696/2014. This work is also partially supported by the MINECO/FEDER TIN2017-89156-R and the Post-Doc scholarship with the Ref. SP20170057

Heuristic methods for coalition structure generation

The Coalition Structure Generation (CSG) problem requires finding an optimal partition of a set of n agents. An optimal partition means one that maximizes global welfare. Computing an optimal coalition structure is computationally hard especially when there are externalities, i.e., when the worth of a coalition is dependent on the organisation of agents outside the coalition. A number of algorithms were previously proposed to solve the CSG problem but most of these methods were designed for systems without externalities. Very little attention has been paid to finding optimal coalition structures in the presence of externalities, although externalities are a key feature of many real world multiagent systems. Moreover, the existing methods, being non-heuristic, have exponential time complexity which means that they are infeasible for any but systems comprised of a small number of agents. The aim of this research is to develop effective heuristic methods for finding optimal coalition structures in systems with externalities, where time taken to find a solution is more important than the quality of the solution. To this end, four different heuristics methods namely tabu search, simulated annealing, ant colony search and particle swarm optimisation are explored. In particular, neighbourhood operators were devised for the effective exploration of the search space and a compact representation method was formulated for storing details about the multiagent system. Using these, the heuristic methods were devised and their performance was evaluated extensively for a wide range of input data

Coalition structure generation over graphs

We give the analysis of the computational complexity of coalition structure generation over graphs. Given an undirected graph G = (N,E) and a valuation function v : P(N) → R over the subsets of nodes, the problem is to find a partition of N into connected subsets, that maximises the sum of the components values. This problem is generally NP-complete; in particular, it is hard for a defined class of valuation functions which are independent of disconnected members — that is, two nodes have no effect on each others marginal contribution to their vertex separator. Nonetheless, for all such functions we provide bounds on the complexity of coalition structure generation over general and minor free graphs. Our proof is constructive and yields algorithms for solving corresponding instances of the problem. Furthermore, we derive linear time bounds for graphs of bounded treewidth. However, as we show, the problem remains NP-complete for planar graphs, and hence, for any Kk minor free graphs where k ≥ 5. Moreover, a 3-SAT problem with m clauses can be represented by a coalition structure generation problem over a planar graph with O(m2) nodes. Importantly, our hardness result holds for a particular subclass of valuation functions, termed edge sum, where the value of each subset of nodes is simply determined by the sum of given weights of the edges in the induced subgraph

Tasks for Agent-Based Negotiation Teams:Analysis, Review, and Challenges

An agent-based negotiation team is a group of interdependent agents that join together as a single negotiation party due to their shared interests in the negotiation at hand. The reasons to employ an agent-based negotiation team may vary: (i) more computation and parallelization capabilities, (ii) unite agents with different expertise and skills whose joint work makes it possible to tackle complex negotiation domains, (iii) the necessity to represent different stakeholders or different preferences in the same party (e.g., organizations, countries, and married couple). The topic of agent-based negotiation teams has been recently introduced in multi-agent research. Therefore, it is necessary to identify good practices, challenges, and related research that may help in advancing the state-of-the-art in agent-based negotiation teams. For that reason, in this article we review the tasks to be carried out by agent-based negotiation teams. Each task is analyzed and related with current advances in different research areas. The analysis aims to identify special challenges that may arise due to the particularities of agent-based negotiation teams.Comment: Engineering Applications of Artificial Intelligence, 201

Social Games: Matching and the Play of Finitely Repeated Games

We examine a new class of games, which we call social games, where players not only choose strategies but also choose with whom they play. A group of players who are dissatisfied with the play of their current partners can join together and play a new equilibrium. This imposes new refinements on equilibrium play, where play depends on the relative populations of players in different roles, among other things. We also examine finite repetitions of games where players may choose to rematch in any period. Some equilibria of fixed-player repeated games cannot be sustained as equilibria in a repeated social game. Conversely, the set of repeated matching (or social) equilibria also includes some plays that are not part of any subgame perfect equilibrium of the corresponding fixed-player repeated games. We explore existence under different equilibrium definitions, as well as the relationship to renegotiation-proof equilibrium. It is possible for repeated matching equilibria to be completely distinct from renegotiation-proof equilibria, and even to be Pareto inefficient.Social games, Matching, Games, Repeated games, Renegotiation

CO-EVOLUTIONARY BIDDING AND COOPERATION STRATEGIES FOR BUYERS IN POWER MARKETS

Master'sMASTER OF ENGINEERIN

HedN Game, a Relational Framework for Network Based Cooperation

This paper proposes a new framework for cooperative games based on mathematical relations. Here cooperation is defined as a supportive partnerships represented by a directed network between players (aka hedonic relation). We examine in a specific context, modeled by abstract games how a change of supports induces a modification of strategic interactions between players. Two levels of description are considered: the first one describes the support network formation whereas the second one models the strategic interactions between players. Both are described in a unified formalism, namely CP~game. Stability conditions are stated, emphasizing the connection between these two levels. We also stress the interaction between updates of supports and their impact on the evolution of the context.Cooperative Game, Network, Stability, Hedonic Relation