Minimal Resources for Fixed and Variable Job Schedules
We treat the following problem: There are n jobs with given processing times and an interval for each job's starting time. Each job must be processed, without interruption, on any one of an unlimited set of identical machines. A machine may process any job, but no more than one job at any point in t... Ausführliche Beschreibung
1. Person:  Gertsbakh, Ilya 

Weitere Personen:  Stern, Helman I. verfasserin 
Quelle: 
in Operations research Vol. 26, No. 1 (1978), p. 6885 Weitere Artikel 
Format:  OnlineArtikel 
Sprache:  English 
Veröffentlicht: 
1978 
Beschreibung:  OnlineRessource 
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researcharticle

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Copyright: Copyright 1978 The Operations Research Society of America 
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100  1  a Gertsbakh, Ilya  
245  1  0  a Minimal Resources for Fixed and Variable Job Schedules h Elektronische Ressource 
300  a OnlineRessource  
500  a Copyright: Copyright 1978 The Operations Research Society of America  
520  a We treat the following problem: There are n jobs with given processing times and an interval for each job's starting time. Each job must be processed, without interruption, on any one of an unlimited set of identical machines. A machine may process any job, but no more than one job at any point in time. We want to find the starting time of each job such that the number of machines required to process all jobs is minimal. In addition, the assignment of jobs to each machine must be found. If every job has a fixed starting time (the interval is a point), the problem is wellknown as a special case of Dilworth's problem. We term it the fixed job schedule problem (FSP). When the job starting times are variable, the problem is referred to as the variable job schedule problem (VSP), for which no known exact solution procedure exists. We introduce the problems by reviewing previous solution methods to Dilworth's problem. We offer an approximate solution procedure for solving VSP based on the entropy principle of informational smoothing. We then formulate VSP as a pure integer programming problem and provide an exact algorithm. This algorithm examines a sequence of feasibility capacitated transportation problems with job splitting elimination side constraints. Our computational experience demonstrates the utility of the entropy approach.  
653  a researcharticle  
700  1  a Stern, Helman I. e verfasserin 4 aut  
773  0  8  i in t Operations research d Linthicum, Md : INFORMS g Vol. 26, No. 1 (1978), p. 6885 q 26:1<6885 w (DE601)JST063672286 x 15265463 
856  4  1  u https://www.jstor.org/stable/169892 3 Volltext 
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952  d 26 j 1978 e 1 h 6885 