Using binary particle swarm optimization to search for maximal successful coalition

Zhang, Guofu; Yang, Renzhi; Su, Zhaopin; Feng, Yulin; Fan, Yuqi; Qi, Meibin; Jiang, Jianguo

doi:10.1007/s10489-014-0589-y

Cited by 10 publications

(7 citation statements)

References 32 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…To verify the proposed TOH, we now present empirical results against AOH on the basis of three popular binary MHAs: genetic algorithm (GA) [35], BPSO [39], and binary differential evolution (BDE) [45]. To make the comparisons as fair as possible, we adopt the basic algorithmic parameters of GA, BPSO, and BDE that were recommended in [35], [39], [45]. In common, the population size is 30 and the maximal generation number is 500.…”

Section: Resultsmentioning

confidence: 99%

“…Moreover, in some cases the optimal solution to the problem with appropriate size may even be found [32], [33]. In such optimization methods, meta-heuristic algorithms (MHAs) have become powerful and popular for solving varieties of coalition formation problems [34]- [39]. MHAs can be defined as a set of nature-inspired and population-based stochastic optimization techniques through the reproduction of generations [43], [44].…”

Section: Literature Reviewmentioning

confidence: 99%

See 1 more Smart Citation

A Task-Oriented Heuristic for Repairing Infeasible Solutions to Overlapping Coalition Structure Generation

Zhang

et al. 2020

IEEE Trans. Syst. Man Cybern, Syst.

Self Cite

View full text Add to dashboard Cite

Overlapping coalition formation (OCF), which provides a natural framework for modeling scenarios where each agent can join and allocate their resources to several completely different coalitions at the same time, has become a very active topic in multi-agent systems (MAS). For OCF in resourceconstrained and subadditive task oriented domains, an agent may not possess sufficient resources to meet the needs of multiple coalitions simultaneously. As a result, there may exist many potential resource conflicts among the rival overlapping coalitions. To tackle such situations, we first present a natural variation of the traditional OCF model and analyze the size of the solution space and the computational complexity of the overlapping coalition structure generation (OCSG) problem. Next, we develop a generic task-oriented heuristic (TOH) for individual repairs that can be used in binary meta-heuristic algorithms (MHAs) to generate overlapping coalitions in a parallel manner. Moreover, we show how the proposed TOH repairs a two-dimensional individual to resolve resource conflicts and discuss several basic properties. Finally, to evaluate the effectiveness of TOH, we compare it with the existing agent-oriented heuristic (AOH) for the OCSG problem. The empirical results demonstrate that TOH is of high efficiency and effectiveness in harsh environments with fierce competition over scarce resources.

show abstract

Section: Resultsmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

A Task-Oriented Heuristic for Repairing Infeasible Solutions to Overlapping Coalition Structure Generation

Zhang

et al. 2020

IEEE Trans. Syst. Man Cybern, Syst.

Self Cite

View full text Add to dashboard Cite

show abstract

“…, x n ), namely the position of search agent, is a binary vector. Similar to the binary PSO [9], the velocities of the search agents are mapped to probability values in [0, 1]. Based on the obtained probability values, the positions switch between 0 and 1 to achieve the updating.…”

Section: Binary Encodingmentioning

confidence: 99%

BMM: A Binary Metaheuristic Mapping Algorithm for Mesh-Based Network-on-Chip

Wang

Sun

2019

IEICE Trans. Inf. & Syst.

View full text Add to dashboard Cite

The mapping optimization problem in Network-on-Chip (NoC) is constraint and NP-hard, and the deterministic algorithms require considerable computation time to find an exact optimal mapping solution. Therefore, the metaheuristic algorithms (MAs) have attracted great interests of researchers. However, most MAs are designed for continuous problems and suffer from premature convergence. In this letter, a binary metaheuristic mapping algorithm (BMM) with a better exploration-exploitation balance is proposed to solve the mapping problem. The binary encoding is used to extend the MAs to the constraint problem and an adaptive strategy is introduced to combine Sine Cosine Algorithm (SCA) and Particle Swarm Algorithm (PSO). SCA is modified to explore the search space effectively, while the powerful exploitation ability of PSO is employed for the global optimum. A set of well-known applications and large-scale synthetic cores-graphs are used to test the performance of BMM. The results demonstrate that the proposed algorithm can improve the energy consumption more significantly than some other heuristic algorithms. key words: network-on-chip, application mapping, particle swarm algorithm, sine cosine algorithm

show abstract

“…41 Using game theory to study the conditions under which the collaboration is formed is the main issue investigated in these proposals. 42 Hedonic games and fractional hedonic games are of particular interest where the efficiency of a player in a community depends on the identity of the other members of the community and the value this player ascribes to those members. It provides powerful techniques for strategic decision-making, particularly cooperative and coalition formation games.…”

Section: Related Workmentioning

confidence: 99%

“…Optimization techniques are also used, for instance, to search for maximal successful coalition. 42 Hedonic games and fractional hedonic games are of particular interest where the efficiency of a player in a community depends on the identity of the other members of the community and the value this player ascribes to those members. In the following, we introduce the related research work regarding the engineering, management, and formation of virtual service communities.…”

Section: Related Workmentioning

confidence: 99%

Dynamic formation of service communities in the cloud under distribution and incomplete information settings

Khosrowshahi-Asl¹,

Estrada

Otrok

et al. 2017

Concurrency and Computation

View full text Add to dashboard Cite

Communities that gather functionally identical or complementary cloud services aim to provide better visibility, efficiency, and market share. This paper investigates the issue of forming these communities in distributed decision-making settings under incomplete information. By incomplete information, we mean only partial information about the individual performance of cloud services within communities and about how they will behave within these communities is available. Forming communities in these particular settings is still an open problem. Most of the existing models require real-time global knowledge about the services and high computational complexity, which makes the community formation extremely hard and time-consuming. In this paper, we propose a strategic Distributed Decision-making Mechanism (DDM) that regulates the cloud services decision-making process. DDM first generates an initial set of data based on information obtained from existing cloud services regarding their single and cooperative efficiency. By analyzing this set and on the basis of a distance function, the decision-making mechanism with regard to which community to form is implemented as a decision profile of strategies and their expected utility computed in terms of computational efficiency. DDM efficiently and systematically helps 1) communities find appropriate cloud services to invite as new members and 2) single services find suitable communities to join. To evaluate the proposed mechanism, we performed experiments using real data including 142 users and 4,000 cloud services obtained from the CloudArmor, CloudHarmony, and WS-DREAM datasets. The experimental results show that our algorithms outperform the existing solutions. KEYWORDScloud services, community of services, distributed decision-making INTRODUCTIONModern applications are nowadays developed using service-oriented architecture and web services technology where the cloud's software as a service (SaaS) is de facto model for software delivery. To make these applications more efficient and adaptive to the new requirements of being flexible, cloud services including SaaS, platform as a service (PaaS), infrastructure as a service (IaaS), and backend as a service (BaaS) are shifted, from the perspective of design and engineering, from passive and individual components to intelligent, autonomous, and collaborative-based components having common goals. 1-4 Being collaborative entails new challenges towards analyzing the overall system's performance in achieving these common goals. 5-8 One of the initiatives towards strengthening this collaboration among services is capitalizing on the concept of virtual communities. 9-11 A virtual community of services is defined as a group of services offering similar and complementary functionalities with diverse non-functional properties that can ensure the inter-community and intra-community interactions.Despite the existence of the current services technologies (e.g., WSDL and SOAP) and cloud developments that enable developing virtual commun...

show abstract

Using binary particle swarm optimization to search for maximal successful coalition

Cited by 10 publications

References 32 publications

A Task-Oriented Heuristic for Repairing Infeasible Solutions to Overlapping Coalition Structure Generation

A Task-Oriented Heuristic for Repairing Infeasible Solutions to Overlapping Coalition Structure Generation

BMM: A Binary Metaheuristic Mapping Algorithm for Mesh-Based Network-on-Chip

Dynamic formation of service communities in the cloud under distribution and incomplete information settings

Contact Info

Product

Resources

About