Efficiency Resource Allocation for Device-to-Device Underlay Communication Systems: A Reverse Iterative Combinatorial Auction Based Approach

Peer-to-peer communication has been recently considered as a popular issue for local area services. An innovative resource allocation scheme is proposed to improve the performance of mobile peer-to-peer, i.e., device-to-device (D2D), communications as an underlay in the downlink (DL) cellular networks. To optimize the system sum rate over the resource sharing of both D2D and cellular modes, we introduce a reverse iterative combinatorial auction as the allocation mechanism. In the auction, all the spectrum resources are considered as a set of resource units, which as bidders compete to obtain business while the packages of the D2D pairs are auctioned off as goods in each auction round. We first formulate the valuation of each resource unit, as a basis of the proposed auction. And then a detailed non-monotonic descending price auction algorithm is explained depending on the utility function that accounts for the channel gain from D2D and the costs for the system. Further, we prove that the proposed auction-based scheme is cheat-proof, and converges in a finite number of iteration rounds. We explain non-monotonicity in the price update process and show lower complexity compared to a traditional combinatorial allocation. The simulation results demonstrate that the algorithm efficiently leads to a good performance on the system sum rate.Comment: 26 pages, 6 fgures; IEEE Journals on Selected Areas in Communications, 201

Time-based combinatorial auction for timber allocation and delivery coordination

The timber auction system currently used in the province of Québec, Canada, is a single unit auction, in which timber users bid on the entire forest stands located within a specific area. In this procurement system, timber users (i.e., winners) are responsible for harvesting the entire stands and for reselling undesirable timber species to others. In order to improve the limits of this system, this paper proposes a sustainable auction system, referred to as time-based timber combinatorial auction. In this approach, time is not part of the definition of the goods for sale. It is used to valuate the good for sale with respect to their expected delivery period. Therefore, this system aims to simultaneously allocate multiple goods, or products in mixed forest stand, to multiple winners, and address the coordination of timber deliveries to their winners. The proposed timber combinatorial auction provides an open access allocation of timber, based on its intrinsic economic value, while allowing the Ministry of natural resources to exercise high standard for environmentally friendly forest operations. From a logistic point of view, a sensitive analysis is conducted in order to compare the proposed time-based combinatorial auction with a combinatorial auction with no delivery coordination. Both models are compared according to bidders' and seller's time flexibility. Experimental results illustrate the impact (i.e., cost) of delivery coordination on total revenue due to loss of value when time preference is not fully satisfied. This cost evaluation can then be used as an upper bound of the cost of coordination, when delivery coordination must be manually negotiated among multi-stakeholders

Robust distributed scheduling via time period aggregation

In this paper, we evaluate whether the robustness of a market mechanism that allocates complementary resources could be improved through the aggregation of time periods in which resources are consumed. In particular, we study a multi-round combinatorial auction that is built on a general equilibrium framework. We adopt the general equilibrium framework and the particular combinatorial auction design from the literature, and we investigate the benefits and the limitation of time-period aggregation when demand-side uncertainties are introduced. By using simulation experiments on a real-life resource allocation problem from a container port, we show that, under stochastic conditions, the performance variation of the process decreases as the time frame length (time frames are obtained by aggregating time periods) increases. This is achieved without causing substantial deterioration in the mean performance. The main driver for the increase in robustness is that longer time frames result in allocations where resources are assigned in longer contiguous time blocks. The resulting resource continuity allows bidders to shift schedules upon realization of stochasticity. To demonstrate the generality of the notion that resource continuity increases allocation robustness, we perform further experiments on a decentralized variant of the classical job shop scheduling problem. The experiment results demonstrate similar benefits

Timber Auction Simulation and Design

RÉSUMÉ : La commercialisation sous forme de vente aux enchères publique du bois provenant de forêts, comme dans la province de Québec, est une tâche difficile. En effet, il est crucial de déterminer les prix représentatifs de la vente aux enchères de bois dans toutes les régions du Québec afin de permettre à plus d'acheteurs potentiels d'accéder au marché. De même, il est également important de concevoir un système d'enchères qui est bénéfique pour les entreprises forestières et les gens de Québec. La vente unitaire, dans lequel les utilisateurs de bois autorisés à soumissionner pour le lot entier, est actuellement appliquée comme une méthode de vente aux enchères. Dans ce système de vente aux enchères du bois, les utilisateurs de bois sont responsables de la récolte de la totalité du lot et pour la revente espèces ligneuses indésirables à d'autres utilisateurs. Dans ce projet, nous analysons d'abord différentes configurations d’enchères à rondes multiples de type premier prix sous pli scellé, tel que proposé par le ministère des Ressources naturelles du Québec, afin de mieux comprendre la dynamique et les facteurs dominants de la réussite de ce type de mécanisme d'allocation de bois. Pour cela, nous utilisons la simulation à base d'agents pour modéliser et simuler des ventes aux enchères, en proposant notamment des comportements de soumissionnaires réalistes, incluant des stratégies d'adaptation et d'apprentissage, qui ont été simulées et comparées dans diverses configurations. Les comparaisons ont été menées en mesurant notamment le taux de succès de gagner l'enchère et le prix unitaire remporté en $/m3. Cette étude suggère également des configurations de paramètres permettant maximiser les recettes pour le commissaire-priseur. À l’étape suivante de la recherche, cette thèse présente la simulation de la vente de plusieurs sortes de bois rond en utilisant une méthode d’enchères combinatoires. Dans ce processus de vente, les soumissionnaires peuvent avoir besoin d’une combinaison des produits. En utilisant l'approche par simulation, les résultats montrent que les revenus générés par enchère combinatoire peuvent être plus élevés que le revenu de l’enchère unitaire. Afin d'effectuer une analyse de sensibilité, les expériences sont répétées et testés avec diverses combinaisons de quatre paramètres de configuration. Les résultats de l'analyse permettent d’évaluer dans quel contexte l’enchère combinatoire peut faire mieux que l’enchère unitaire, et cela dans différents marchés. Enfin, cette thèse présente un système d'enchères combinatoires qui alloue le bois aux soumissionnaires afin d'améliorer la coordination des dépendances entre les soumissionnaires retenus dans les zones forestières mixtes (c’est à dire avec plusieurs types de produits et utilisateurs potentiels). Pour supporter la coordination des opérations et améliorer la fraicheur du bois, nous proposons une vente aux enchères combinatoire, qui permet aux soumissionnaires d’ajuster la valeur des offres en fonction du temps, via une sorte de calendriers. Cette enchère combinatoire permet ainsi au commissaire-priseur de trouver les meilleures combinaisons de soumissions gagnantes maximisant ainsi les préférences temporelles des soumissionnaires. Pour cela, nous définissons un nouveau problème de détermination du vainqueur (WDP) qui utilise ces fonctions de valeur. Afin de comparer l’impact de diverses préférences temporelles, une analyse de sensibilité est menée. Mots-clés: enchères du bois, enchères séquentielles, la stratégie d'apprentissage, systèmes multi-agents, l'affectation enchères combinatoire, la coordination, la fraicheur du bois, et de problèmes de détermination du vainqueur.----------ABSTRACT : The marketing of wood obtained from forests in public auction, such as in the province of Québec, is a challenging task. Indeed, it is crucial to determine representative prices of the wood auction in all regions of Quebec in order to allow more potential buyers to access the market. Similarly, it is also important to design an auction system that is beneficial for forest companies and the people of Québec. Single-unit auction, in which timber users allowed to bid on the entire lot, is currently applied as a method of auction. In this timber auction system, timber users (i.e., winners) are responsible for harvesting the entire lot and for reselling unwanted timber species to other users. In this project, we first analyze various configurations of the multiple-round first-price sealed-bid auction of wood as proposed by the Québec Ministry of Natural Resources to better understand the dynamics and the dominant factors of success of this type of wood allocation mechanism. To do so, we use agent-based simulation to model and simulate auctions with realistic bidders’ behavior. Different bidding patterns including adaptive and learning strategies are then simulated and compared in various setup configurations. The comparisons have been conducted on the success rate of winning the auction and the winning price per m3. This study also suggests parameter configurations to maximize revenue for the auctioneer. In the next step of research, in the last part, this thesis presents the simulation of multiple-round timber combinatorial auction as the bidders may need variety of species and the size of timber companies may be different. Using simulation approach, the results shows the revenue generated by combinatorial auction can be higher than the revenue of a single unit auction. In order to do sensitive analysis of the comparison, the experiments are repeated and tested with different setup configuration of four parameters. The results of analysis help to evaluate how combinatorial auction can perform better than single auction in different markets. Finally, we intend to present an auction system, which allocates wood to bidders in order to improve the coordination of the dependencies between winning bidders in mixed forest areas (i.e., wood lots with multiple users). To achieve the coordination of procurement operations and improve the freshness of the wood, we propose an auction, by allowing the value of bids to be expressed as a function of time, via some sort of timetables, and by using a combinatorial auction that will allow the auctioneer to find the best combinations of winning bids. In order to do that, we define a new winner determination problem (WDP) that use these value functions for coordination procurement and delivery operations and wood freshness. In order to compare the proposed time-based combinatorial auction with combinatorial auction a sensitive analysis is conducted. The comparison is done according to bidders’ and seller’s time flexibility. Keywords: timber auction, sequential auction, learning strategy, multi agent system, allocation combinatorial auction, coordination, wood freshness, and winner determination problem

Decentralized and Dynamic Home Health Care Resource Scheduling Using an Agent-Based Model

The purpose of this thesis is to design an agent-based scheduling system, simulated in a dynamic environment that will reduce home healthcare service costs. The study focuses on situations where a health care agency needs to assign home visits among a group of independent healthcare practitioners. Each practitioner has different skill sets, time constraints, and cost structures, given the nature, time and location of each home visit. Each expects reasonable payment commensurate with their skill levels as well as the costs incurred. The healthcare agency in turn needs all planned visits performed by qualified practitioners while minimizing overall service costs. Decisions about scheduling are made both before and during the scheduling period, requiring the health care agency to respond to unexpected situations based on the latest scheduling information. This problem is examined in a multi-agent system environment where practitioners are modeled as self-interested agents. The study first analyzes the problem for insights into the combinatorial nature of such a problem occurring in a centralized environment, then discusses the decentralized and dynamic challenges. An iterated bidding mechanism is designed as the negotiation protocol for the system. The effectiveness of this system is evaluated through a computational study, with results showing the proposed multi-agent scheduling system is able to compute high quality schedules in the decentralized home healthcare environment. Following this, the system is also implemented in a simulation model that can accommodate unexpected situations. We presents different simulation scenarios which illustrate the process of how the system dynamically schedules incoming visits, and cost reduction can be observed from the results