Approximation algorithms for multi-agent scheduling to minimize total weighted completion time

We consider a multi-agent scheduling problem on a single machine in which each agent is responsible for his own set of jobs and wishes to minimize the total weighted completion time of his own set of jobs. It is known that the unweighted problem with two agents is NP-hard in the ordinary sense. For...

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Vydané v:	Information processing letters Ročník 109; číslo 16; s. 913 - 917
Hlavní autori:	Lee, Kangbok, Choi, Byung-Cheon, Leung, Joseph Y.-T., Pinedo, Michael L.
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Amsterdam Elsevier B.V 31.07.2009 Elsevier Elsevier Sequoia S.A
Predmet:	Algorithmics. Computability. Computer arithmetics Applied sciences Approximation Approximation algorithm Approximations and expansions Computer science; control theory; systems Computer systems performance. Reliability Exact sciences and technology FPTAS Mathematical analysis Mathematics Miscellaneous Multi-agent scheduling Multi-Objective Shortest-Path problem Optimization Production scheduling Scheduling algorithms Sciences and techniques of general use Shortest path algorithms Software Studies Theoretical computing Total weighted completion time Total weighted completion time Multi-agent scheduling Approximation algorithm FPTAS Multi-Objective Shortest-Path problem Polynomial Computer theory Polynomial approximation Shortest path Scheduling Polynomial time Completion Information processing Algorithm analysis Single machine
ISSN:	0020-0190, 1872-6119
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Abstract	We consider a multi-agent scheduling problem on a single machine in which each agent is responsible for his own set of jobs and wishes to minimize the total weighted completion time of his own set of jobs. It is known that the unweighted problem with two agents is NP-hard in the ordinary sense. For this case, we can reduce our problem to a Multi-Objective Shortest-Path (MOSP) problem and this reduction leads to several results including Fully Polynomial Time Approximation Schemes (FPTAS). We also provide an efficient approximation algorithm with a reasonably good worst-case ratio.
AbstractList	We consider a multi-agent scheduling problem on a single machine in which each agent is responsible for his own set of jobs and wishes to minimize the total weighted completion time of his own set of jobs. It is known that the unweighted problem with two agents is NP-hard in the ordinary sense. For this case, we can reduce our problem to a Multi-Objective Shortest-Path (MOSP) problem and this reduction leads to several results including Fully Polynomial Time Approximation Schemes (FPTAS). We also provide an efficient approximation algorithm with a reasonably good worst-case ratio. We consider a multi-agent scheduling problem on a single machine in which each agent is responsible for his own set of jobs and wishes to minimize the total weighted completion time of his own set of jobs. It is known that the unweighted problem with two agents is NP-hard in the ordinary sense. For this case, we can reduce our problem to a Multi-Objective Shortest-Path (MOSP) problem and this reduction leads to several results including Fully Polynomial Time Approximation Schemes (FPTAS). We also provide an efficient approximation algorithm with a reasonably good worst-case ratio. [PUBLICATION ABSTRACT]
Author	Choi, Byung-Cheon Pinedo, Michael L. Lee, Kangbok Leung, Joseph Y.-T.
Author_xml	– sequence: 1 givenname: Kangbok surname: Lee fullname: Lee, Kangbok email: klee3@stern.nyu.edu organization: Department of Information, Operations & Management Sciences, Stern School of Business, New York University, 44 West 4th Street, New York, NY 10012-1126, USA – sequence: 2 givenname: Byung-Cheon surname: Choi fullname: Choi, Byung-Cheon email: byungcheon.choi@gmail.com organization: Department of Information, Operations & Management Sciences, Stern School of Business, New York University, 44 West 4th Street, New York, NY 10012-1126, USA – sequence: 3 givenname: Joseph Y.-T. surname: Leung fullname: Leung, Joseph Y.-T. email: leung@cis.njit.edu organization: Department of Computer Science, New Jersey Institute of Technology, Newark, NJ 07102, USA – sequence: 4 givenname: Michael L. surname: Pinedo fullname: Pinedo, Michael L. email: mpinedo@stern.nyu.edu organization: Department of Information, Operations & Management Sciences, Stern School of Business, New York University, 44 West 4th Street, New York, NY 10012-1126, USA
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Keywords	Total weighted completion time Multi-agent scheduling Approximation algorithm FPTAS Multi-Objective Shortest-Path problem Polynomial Computer theory Polynomial approximation Shortest path Scheduling Polynomial time Completion Information processing Algorithm analysis Single machine
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SubjectTerms	Algorithmics. Computability. Computer arithmetics Applied sciences Approximation Approximation algorithm Approximations and expansions Computer science; control theory; systems Computer systems performance. Reliability Exact sciences and technology FPTAS Mathematical analysis Mathematics Miscellaneous Multi-agent scheduling Multi-Objective Shortest-Path problem Optimization Production scheduling Scheduling algorithms Sciences and techniques of general use Shortest path algorithms Software Studies Theoretical computing Total weighted completion time
Title	Approximation algorithms for multi-agent scheduling to minimize total weighted completion time
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