Solving the Set Packing Problem via a Maximum Weighted Independent Set Heuristic

Li, Ruizhi; Wang, Yupan; Hu, Shuli; Jiang, Jianhua; Ouyang, Dantong; Yin, Minghao

doi:10.1155/2020/3050714

Cited by 4 publications

(2 citation statements)

References 43 publications

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“…Kwon et al (2008) and Kolokolov and Zaozerskaya (2009) also proposed new facets that strengthen the relaxed formulations of SPP. Li et al (2020) encoded SPP as a maximum weighted independent set and then used a Diversion Local Search based on the Weighted Configuration Checking (DLSWCC) algorithm to solve it. Since SPP is NPhard (Garey and Johnson, 2009), many heuristics have also been proposed to obtain a solution for SPP in a reasonable amount of time.…”

Section: Phase 2: Set Packingmentioning

confidence: 99%

xER: An Explainable Model for Entity Resolution using an Efficient Solution for the Clique Partitioning Problem

Vadrevu¹,

Nagi²,

Xiong³

et al. 2021

Proceedings of the First Workshop on Trustworthy Natural Language Processing

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In this paper, we propose a global, selfexplainable solution to solve a prominent NLP problem: Entity Resolution (ER). We formulate ER as a graph partitioning problem. Every mention of a real-world entity is represented by a node in the graph, and the pairwise similarity scores between the mentions are used to associate these nodes to exactly one clique, which represents a real-world entity in the ER domain. In this paper, we use Clique Partitioning Problem (CPP), which is an Integer Program (IP) to formulate ER as a graph partitioning problem and then highlight the explainable nature of this method. Since CPP is NP-Hard, we introduce an efficient solution procedure, the xER algorithm, to solve CPP as a combination of finding maximal cliques in the graph and then performing generalized set packing using a novel formulation. We discuss the advantages of using xER over the traditional methods and provide the computational experiments and results of applying this method to ER data sets.

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Section: Phase 2: Set Packingmentioning

confidence: 99%

xER: An Explainable Model for Entity Resolution using an Efficient Solution for the Clique Partitioning Problem

Vadrevu¹,

Nagi²,

Xiong³

et al. 2021

Proceedings of the First Workshop on Trustworthy Natural Language Processing

View full text Add to dashboard Cite

show abstract

“…A combinatorial auction problem is a winner determination problem which is still one of the main challenges of combinatorial auctions [8]. Indeed, WDP in combinatorial auctions is a complex problem, and it is an NP-complete problem, which is equivalent to a weighted set packing problem [9].…”

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confidence: 99%

An enhanced approach for solving winner determination problem in reverse combinatorial auctions

Abusalama

Razali

Choo

2022

IJEECS

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<span>When a disaster occurs, the single agent does not have complete knowledge about the circumstances of the disaster. Therefore, the rescue agents should coordinate with each other to perform their allocated tasks efficiently. However, the task allocation process among rescue agents is a complex problem, which is NP-complete problem, and determining the rescue agents that will perform the tasks efficiently is the main problem, which is called the winner determination problem (WDP). This paper proposed an enhanced approach to improve rescue agents’ tasks allocation processes for WDP in reverse combinatorial auctions. The main objective of the proposed approach is to determine the winning bids that will perform the corresponding tasks with minimum cost. The task allocation problem in this paper was transformed into a two-dimensional array, and then the proposed approach was applied to it. The main contribution of the proposed approach is to shorten the search space size to determine the winners and allocate the corresponding tasks for a combination of agents (i.e., more than two agents). The proposed approach was compared to the genetic algorithm regarding the execution time, and the results showed good performance and effectiveness of the proposed approach.</span>

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An Empirical Study on Interfaces for Presenting Large Sets of Point Features in Mobile Maps

Gedicke

Haunert

2023

The Cartographic Journal

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Solving the Set Packing Problem via a Maximum Weighted Independent Set Heuristic

Cited by 4 publications

References 43 publications

xER: An Explainable Model for Entity Resolution using an Efficient Solution for the Clique Partitioning Problem

xER: An Explainable Model for Entity Resolution using an Efficient Solution for the Clique Partitioning Problem

An enhanced approach for solving winner determination problem in reverse combinatorial auctions

An Empirical Study on Interfaces for Presenting Large Sets of Point Features in Mobile Maps

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