Two game-based solution concepts for a two-agent scheduling problem

Gu, Yanhong; Ruan, Yuan; Chen, Quanle

doi:10.1007/s10586-016-0557-x

Cited by 5 publications

(4 citation statements)

References 26 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Cole et al 14 presented simple mechanisms that required only local information and used the game theoretic insights to obtain a new combinatorial approximation algorithm for the underlying optimization problem. Zhao et al 15 considered a two-agent scheduling problem on a single machine. They designed a Pareto-efficient solution set and used the Shapley value method to evaluate the job sequence of two agents by comparing the net profit and opportunity.…”

Section: Literature Reviewmentioning

confidence: 99%

A multi-agent scheduling problem for two identical parallel machines to minimize total tardiness time and makespan

Wen

2018

Advances in Mechanical Engineering

View full text Add to dashboard Cite

We study an agent-based scheduling problem of two identical parallel machines:. The machines and tasks are regarded as agents. A new multi-agent scheduling model is proposed to achieve the optimum from the two task agents, agent A and agent B. The objective is divided into two classes. The objectives of agent A and agent B are to minimize the total tardiness time and minimize the makespan, respectively. In this article, we research two identical parallel machines in which one job category can be processed by one machine agent only or two machine agents and propose a new multi-agent model for two identical parallel machines, divided into two subsystems. For subsystem 1, the shortest processing time order is used to solve job priorities. A single distribution strategy is proposed to assign jobs to machine agents and is applied to the dynamic scheduling environment. For subsystem 2, a centralized distribution strategy is applied to the static scheduling environment. The proposed model performs more efficiently and is better able to handle complex and dynamic scheduling environments.

show abstract

Section: Literature Reviewmentioning

confidence: 99%

A multi-agent scheduling problem for two identical parallel machines to minimize total tardiness time and makespan

Wen

2018

Advances in Mechanical Engineering

View full text Add to dashboard Cite

show abstract

“…Authors use the game-theoretic insights to obtain a new combinatorial approximation algorithm for the underlying optimization problem. Zhao et al 15 state two agents scheduling problem on single machine. They design the pareto efficient solution set and the Shapley value method and evaluate two agents' job sequence by comparing net profit and opportunity.…”

Section: Literature Reviewmentioning

confidence: 99%

A multi-agent scheduling problem for two identical parallel machines to minimize total tardiness time and makespan

Yu¹,

Wen²,

Sangbong³

2017

Advances in Mechanical Engineering

View full text Add to dashboard Cite

We study a base-agent scheduling problem of two identical parallel machines: P2jCoj P T A , C B max . The machines and tasks are regarded as agents. A new multi-agent scheduling model is proposed in order to achieve the optimum of task agents, which contains two agents: agent A and agent B. The objective is divided into two classes. The objective of agent A and agent B is to minimize total tardiness time and minimize makespan, respectively. In this article, we research character of two identical parallel machines that one category job can be processed by one machine agent only or two machine agents and propose a new multi-agent model on two identical parallel machines, divided into two subsystems. For subsystem 1, it is applied by a dynamic scheduling environment. Shortest processed time order is proposed to solve jobs' priorities. Single distribution strategy is proposed to solve assignment of jobs to machine agents. For subsystem 2, centralized distribution strategy applied to a static scheduling environment is addressed. The new model performs more efficiently and owns a stronger ability to deal with complex and dynamic scheduling environments.

show abstract

“…However, the success of cooperation cannot only depend on mutual trust and recommendation. Benefits and selfinterests could change the decision and outcome [9,10]. Due to autonomous attribute, the referral will judge gains and losses before promising to cooperate.…”

Section: Introductionmentioning

confidence: 99%

“…. , )(8) // Launch cooperation(9) Calculate interaction result and income results (0, op), ( − , ), (− , ) (10) end for (11) end for (12) Calculate executing cooperation revenues Algorithm 1: TR-DII. Moving state of agents in grids (solid color grid is initial position; plaid grid is terminal position).…”

mentioning

confidence: 99%

A Multiagent Cooperation Model Based on Trust Rating in Dynamic Infinite Interaction Environment

Fan

2018

Mathematical Problems in Engineering

View full text Add to dashboard Cite

To improve the liveness of agents and enhance trust and collaboration in multiagent system, a new cooperation model based on trust rating in dynamic infinite interaction environment (TR-DII) is proposed. TR-DII model is used to control agent’s autonomy and selfishness and to make agent do the rational decision. TR-DII model is based on two important components. One is dynamic repeated interaction structure, and the other is trust rating. The dynamic repeated interaction structure is formed with multistage inviting and evaluating actions. It transforms agents’ interactions into an infinity task allocation environment, where controlled and renewable cycle is a component most agent models ignored. Additionally, it influences the expectations and behaviors of agents which may not appear in one-shot time but may appear in long-time cooperation. Moreover, with rewards and punishments mechanism (RPM), the trust rating (TR) is proposed to control agent blindness in selection phase. However, RPM is the factor that directly influences decisions, not the reputation as other models have suggested. Meanwhile, TR could monitor agent’s statuses in which they could be trustworthy or untrustworthy. Also, it refines agent’s disrepute in a new way which is ignored by the others. Finally, grids puzzle experiment has been used to test TR-DII model and other five models are used as comparisons. The results show that TR-DII model can effectively adjust the trust level between agents and makes the solvers be more trustworthy and do choices that are more rational. Moreover, through interaction result feedback, TR-DII model could adjust the income function, to control cooperation reputation, and could achieve a closed-loop control.

show abstract

Two game-based solution concepts for a two-agent scheduling problem

Cited by 5 publications

References 26 publications

A multi-agent scheduling problem for two identical parallel machines to minimize total tardiness time and makespan

A multi-agent scheduling problem for two identical parallel machines to minimize total tardiness time and makespan

A multi-agent scheduling problem for two identical parallel machines to minimize total tardiness time and makespan

A Multiagent Cooperation Model Based on Trust Rating in Dynamic Infinite Interaction Environment

Contact Info

Product

Resources

About