Two-agent scheduling to minimize the total cost

► We consider a two-agent single-machine scheduling problem to minimize the total costs of the agents. ► The cost of the first agent is the maximum weighted completion time of his jobs and the cost of the second agent is the total weighted completion time of his jobs. ► We provide a 2-approximation...

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Vydané v:	European journal of operational research Ročník 215; číslo 1; s. 39 - 44
Hlavní autori:	Nong, Q.Q., Cheng, T.C.E., Ng, C.T.
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Amsterdam Elsevier B.V 16.11.2011 Elsevier Elsevier Sequoia S.A
Edícia:	European Journal of Operational Research
Predmet:	Algorithmics. Computability. Computer arithmetics Algorithms Applied sciences Approximation Approximation algorithm Artificial intelligence Completion time Computer science; control theory; systems Cost engineering Exact sciences and technology Inventory control, production control. Distribution Mathematical analysis Multi-agent Operational research Operational research and scientific management Operational research. Management science Operations research Polynomial time approximation scheme Production scheduling Resource scheduling Scheduling Scheduling algorithms Scheduling Multi-agent Approximation algorithm Polynomial time approximation scheme Scheduling, sequencing Studies Theoretical computing Multi-agent Polynomial time approximation scheme Scheduling Approximation algorithm Costs Polynomial approximation Makespan Polynomial time Multiagent system NP hard problem Artificial intelligence Completion time Execution time
ISSN:	0377-2217, 1872-6860
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Abstract	► We consider a two-agent single-machine scheduling problem to minimize the total costs of the agents. ► The cost of the first agent is the maximum weighted completion time of his jobs and the cost of the second agent is the total weighted completion time of his jobs. ► We provide a 2-approximation algorithm for the problem. ► We show that the case where the number of jobs of the first agent is fixed is NP-hard. ► We devise a polynomial time approximation scheme for this case. Two agents, each having his own set of jobs, compete to perform their own jobs on a common processing resource. Each job of the agents has a weight that specifies its importance. The cost of the first agent is the maximum weighted completion time of his jobs while the cost of the second agent is the total weighted completion time of his jobs. We consider the scheduling problem of determining the sequence of the jobs such that the total cost of the two agents is minimized. We provide a 2-approximation algorithm for the problem, show that the case where the number of jobs of the first agent is fixed is NP-hard, and devise a polynomial time approximation scheme for this case.
AbstractList	Two agents, each having his own set of jobs, compete to perform their own jobs on a common processing resource. Each job of the agents has a weight that specifies its importance. The cost of the first agent is the maximum weighted completion time of his jobs while the cost of the second agent is the total weighted completion time of his jobs. We consider the scheduling problem of determining the sequence of the jobs such that the total cost of the two agents is minimized. We provide a 2-approximation algorithm for the problem, show that the case where the number of jobs of the first agent is fixed is NP-hard, and devise a polynomial time approximation scheme for this case. Two agents, each having his own set of jobs, compete to perform their own jobs on a common processing resource. Each job of the agents has a weight that specifies its importance. The cost of the first agent is the maximum weighted completion time of his jobs while the cost of the second agent is the total weighted completion time of his jobs. We consider the scheduling problem of determining the sequence of the jobs such that the total cost of the two agents is minimized. We provide a 2-approximation algorithm for the problem, show that the case where the number of jobs of the first agent is fixed is NP-hard, and devise a polynomial time approximation scheme for this case. [PUBLICATION ABSTRACT] ► We consider a two-agent single-machine scheduling problem to minimize the total costs of the agents. ► The cost of the first agent is the maximum weighted completion time of his jobs and the cost of the second agent is the total weighted completion time of his jobs. ► We provide a 2-approximation algorithm for the problem. ► We show that the case where the number of jobs of the first agent is fixed is NP-hard. ► We devise a polynomial time approximation scheme for this case. Two agents, each having his own set of jobs, compete to perform their own jobs on a common processing resource. Each job of the agents has a weight that specifies its importance. The cost of the first agent is the maximum weighted completion time of his jobs while the cost of the second agent is the total weighted completion time of his jobs. We consider the scheduling problem of determining the sequence of the jobs such that the total cost of the two agents is minimized. We provide a 2-approximation algorithm for the problem, show that the case where the number of jobs of the first agent is fixed is NP-hard, and devise a polynomial time approximation scheme for this case.
Author	Nong, Q.Q. Ng, C.T. Cheng, T.C.E.
Author_xml	– sequence: 1 givenname: Q.Q. surname: Nong fullname: Nong, Q.Q. organization: College of Mathematical Science, Ocean University of China, Qingdao, Shandong 266100, People’s Republic of China – sequence: 2 givenname: T.C.E. surname: Cheng fullname: Cheng, T.C.E. email: lgtcheng@inet.polyu.edu.hk organization: Department of Logistics and Maritime Studies, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong – sequence: 3 givenname: C.T. surname: Ng fullname: Ng, C.T. organization: Department of Logistics and Maritime Studies, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong
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SubjectTerms	Algorithmics. Computability. Computer arithmetics Algorithms Applied sciences Approximation Approximation algorithm Artificial intelligence Completion time Computer science; control theory; systems Cost engineering Exact sciences and technology Inventory control, production control. Distribution Mathematical analysis Multi-agent Operational research Operational research and scientific management Operational research. Management science Operations research Polynomial time approximation scheme Production scheduling Resource scheduling Scheduling Scheduling algorithms Scheduling Multi-agent Approximation algorithm Polynomial time approximation scheme Scheduling, sequencing Studies Theoretical computing
Title	Two-agent scheduling to minimize the total cost
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