Combinatorial Double Auction Research Articles

Solving WDP in combinatorial double auction based on trading strategy

Abstract A solution for winner determination problem (WDP) in combinatorial double auction (CDA) was presented. Different from determining winner by solving optimization model which was non-deterministic polynomial (NP)-hard when the number of participants or resource types amounted to a large scale, the solution put the WDP goal–social welfare maximization into design of the trading strategy and determined winners by the process of resource allocation and pricing. In its corresponding allocation and pricing algorithm, sellers were allowed partially trading their bundles; the transaction path was approximated to Marshallian path; the utility for each winner was non-negative. Simulations show, compared to the WDP optimization model, the proposed algorithm can generate larger social welfare and it is particularly time efficient in conducting large-scale CDA.

Hybrid Genetic Algorithms for Solving Winner Determination Problem in Combinatorial Double Auction in Grid

Nowadays, since grid has been turned to commercialization, using economic methods such as auction methods are appropriate for resource allocation because of their decentralized nature. Combinatorial double auction has emerged as a major model in the economy and is a good approach for resource allocation in which participants of grid, give their requests once to the combination of resources instead of giving them to different resources multiple times. One problem with the combinatorial double auction is the efficient allocation of resources to derive the maximum benefit. This problem is known as winner determination problem (WDP) and is an NP-hard problem. So far, many methods have been proposed to solve this problem and genetic algorithm is one of the best ones. In this paper, two types of hybrid genetic algorithms were presented to improve the efficiency of genetic algorithm for solving the winner determination problem. The results showed that the proposed algorithms had good efficiency and led to better answers. DOI: http://dx.doi.org/10.11591/ij-ai.v1i2.443

Multi-round Combinatorial Double Auction with Virtual Seller for Grid Economy

Multi-round Combinatorial Double Auction with Virtual Seller for Grid Economy

Pricing in combinatorial double auction-based grid allocation model

Abstract This article proposes a novel grid resource allocation model, in which the users and the grid service providers participate in the combinatorial double auction for the resource allocation. To obtain the detailed resource allocation status and the price information, a novel pricing algorithm is designed for the allocation model. Simulation results demonstrate that the proposed algorithm completes the resource allocation and pricing efficiently, and exhibits incentive compatible characteristic. Moreover, users with the higher average price and providers with the lower average price get compensation during the pricing process.

Electronic BushBroker Exchange: Designing a Combinatorial Double Auction for Native Vegetation Offsets

In Victoria, Australia individuals or firms wishing to proceed with development that involves the clearing of native vegetation are required to obtain an offset to replace the vegetation destroyed. This paper focuses on the design and testing of the electronic BushBroker exchange and the evaluation of alternative market institutions, while briefly describing the metric, trading rules and contracts used in the Victorian native vegetation offset scheme. The purpose of the design is to facilitate efficient trades of offsets between developers and landowners and to overcome the complexities inherent in the native vegetation market. Four different types of policy and economic complexities were identified: policy, transaction, strategic, and time complexities. The market design recommended includes 'smart market' features (optimization constrained by the offset trading rules), combinatorial bidding preferences (or package bidding) on both the buyers' and the sellers' side, and strategic tools (including search and query functions and 'market making'), to encourage competitive trading activity. This paper seeks to elucidate the rationale behind these design features. We use two types of tests to assess the performance of the system. A series of experimental tests were used to evaluate the software performance, usability and to elucidate specific bidding behaviour and to assess efficiency. Simulations using actual data were employed to test the robustness of the system by increasing the complexity and scale of the data.

Solving the combinatorial double auction problem

Abstract This paper studies the solution of several types of combinatorial (double) auctions. Such auctions have recently been used in business-to-business trading in a centralized marketplace, or in multi-agent coordination systems in artificial intelligence. When the goods are indivisible, solving the winner determination problem (WDP) is an integer programming problem and NP-hard in its general form. We show that a general combinatorial double auction can be reduced to a combinatorial single-sided auction, which is a multi-dimensional knapsack problem. Next, we compare the performance of several solution approaches for this type of problem. We contrast the branch-and-bound method with the intelligent search method proposed separately in three well-referenced papers. We found that theoretically the LP relaxation bounds always dominate the bounds used in the specialized intelligent searches. We also found empirically that the performance of this branch-and-bound method is superior to the specialized search methods that have been proposed for this class of problems.