Effective meta-heuristics for scheduling on uniform machines with resource-dependent release dates

This paper considers a uniform machine scheduling problem in which the release date of a job can be compressed by additional resources. The objective is to minimise the total resource usage, subject to the constraint that the makespan does not exceed a given deadline. The problem is known to be stro...

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Published inInternational journal of production research Vol. 53; no. 19; pp. 5857 - 5872
Main Authors Li, Kai, Yang, Shan-lin, Leung, Joseph Y.-T., Cheng, Ba-yi
Format Journal Article
LanguageEnglish
Published London Taylor & Francis 02.10.2015
Taylor & Francis LLC
Subjects
Algorithms
Assignment problem
Exchange
Heuristic
heuristics
Lower bounds
makespan
Mathematical analysis
Operations research
Performance evaluation
Production scheduling
Release dates
resource allocation
Resource scheduling
Scheduling
Simulated annealing
strongly NP-hard
Studies
uniform machines
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Abstract This paper considers a uniform machine scheduling problem in which the release date of a job can be compressed by additional resources. The objective is to minimise the total resource usage, subject to the constraint that the makespan does not exceed a given deadline. The problem is known to be strongly NP-hard. We define two types of job moves - the right move and the left move - and analyse their effect on the resource usage. We discuss the calculation of total resource usage for two types of neighbourhood generation methods - the insertion method and exchange method. A variable neighbourhood search algorithm and a simulated annealing algorithm are developed as heuristics. To evaluate the performance of the heuristics, we develop a lower bound by relaxing the original problem to an assignment problem, which can be solved in time. Finally, we generate a large number of random data, and test the performance and efficiency of the proposed heuristics. Our results indicate that the heuristics are reasonably efficient and perform very well compared with the lower bound.
AbstractList This paper considers a uniform machine scheduling problem in which the release date of a job can be compressed by additional resources. The objective is to minimise the total resource usage, subject to the constraint that the makespan does not exceed a given deadline. The problem is known to be strongly NP-hard. We define two types of job moves - the right move and the left move - and analyse their effect on the resource usage. We discuss the calculation of total resource usage for two types of neighbourhood generation methods - the insertion method and exchange method. A variable neighbourhood search algorithm and a simulated annealing algorithm are developed as heuristics. To evaluate the performance of the heuristics, we develop a lower bound by relaxing the original problem to an assignment problem, which can be solved in time. Finally, we generate a large number of random data, and test the performance and efficiency of the proposed heuristics. Our results indicate that the heuristics are reasonably efficient and perform very well compared with the lower bound.
This paper considers a uniform machine scheduling problem in which the release date of a job can be compressed by additional resources. The objective is to minimise the total resource usage, subject to the constraint that the makespan does not exceed a given deadline. The problem is known to be strongly NP-hard. We define two types of job moves - the right move and the left move - and analyse their effect on the resource usage. We discuss the calculation of total resource usage for two types of neighbourhood generation methods - the insertion method and exchange method. A variable neighbourhood search algorithm and a simulated annealing algorithm are developed as heuristics. To evaluate the performance of the heuristics, we develop a lower bound by relaxing the original problem to an assignment problem, which can be solved in [Image omitted.] time. Finally, we generate a large number of random data, and test the performance and efficiency of the proposed heuristics. Our results indicate that the heuristics are reasonably efficient and perform very well compared with the lower bound.
This paper considers a uniform machine scheduling problem in which the release date of a job can be compressed by additional resources. The objective is to minimise the total resource usage, subject to the constraint that the makespan does not exceed a given deadline. The problem is known to be strongly NP-hard. We define two types of job moves -- the right move and the left move -- and analyse their effect on the resource usage. We discuss the calculation of total resource usage for two types of neighbourhood generation methods -- the insertion method and exchange method. A variable neighbourhood search algorithm and a simulated annealing algorithm are developed as heuristics. To evaluate the performance of the heuristics, we develop a lower bound by relaxing the original problem to an assignment problem, which can be solved in O(n3) time. Finally, we generate a large number of random data, and test the performance and efficiency of the proposed heuristics. Our results indicate that the heuristics are reasonably efficient and perform very well compared with the lower bound.
Author Li, Kai
Yang, Shan-lin
Cheng, Ba-yi
Leung, Joseph Y.-T.
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SubjectTerms Algorithms
Assignment problem
Exchange
Heuristic
heuristics
Lower bounds
makespan
Mathematical analysis
Operations research
Performance evaluation
Production scheduling
Release dates
resource allocation
Resource scheduling
Scheduling
Simulated annealing
strongly NP-hard
Studies
uniform machines
Title Effective meta-heuristics for scheduling on uniform machines with resource-dependent release dates
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