A Branch and Bound Algorithm for Job-Shop Scheduling

1991 ◽  
Vol 3 (1) ◽  
pp. 201-209 ◽  
Author(s):  
A. HARIRI ◽  
C. Pons
Keyword(s):  
Branch And Bound ◽  
Job Shop ◽  
Job Shop Scheduling ◽  
Branch And Bound Algorithm ◽  
Shop Scheduling

Branch and bound algorithm in optimizing job shop scheduling problems

2008 ◽  
Author(s):  
Erna Budhiarti Nababan ◽  
Abdul Razak Hamdan ◽  
Salwani Abdullah ◽  
Mohamad Shanudin Zakaria
Keyword(s):  
Branch And Bound ◽  
Job Shop ◽  
Job Shop Scheduling ◽  
Branch And Bound Algorithm ◽  
Scheduling Problems ◽  
Shop Scheduling

scholarly journals Job Shop Scheduling by Branch and Bound Using Genetic Programming

2019 ◽  
Vol 39 ◽  
pp. 1112-1118
Author(s):  
Katsumi Morikawa ◽  
Keisuke Nagasawa ◽  
Katsuhiko Takahashi
Keyword(s):  
Genetic Programming ◽  
Branch And Bound ◽  
Job Shop ◽  
Job Shop Scheduling ◽  
Shop Scheduling

scholarly journals A Branch and Bound Algorithm and Iterative Reordering Strategies for Inserting Additional Trains in Real Time: A Case Study in Germany

2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Yuyan Tan ◽  
Zhibin Jiang
Keyword(s):  
Real Time ◽  
Branch And Bound ◽  
Job Shop ◽  
Job Shop Scheduling ◽  
Branch And Bound Algorithm ◽  
Job Shop Scheduling Problem ◽  
Numerical Investigations ◽  
Railway Infrastructure ◽  
Fixed Order

With the aim of supporting the process of adapting railway infrastructure and future traffic needs, we have developed a method to insert additional trains efficiently to an existing timetable without introducing large consecutive delays to scheduled trains. In this work, the problem is characterized as a job-shop scheduling problem. In order to meet the limited time requirement and minimize deviations to the existing timetable, the modification that consists of retiming or reordering trains is implemented if and only if it potentially leads to a better solution. With these issues in mind, the problem of adding train paths is decomposed into two subproblems. One is finding the optimal insertion for a fixed order timetable and the other is reordering trains. The two subproblems are solved iteratively until no improvement is possible within a time limit of computation. An innovative branch and bound algorithm and iterative reordering strategy are proposed to solve this problem in real time. Unoccupied capacities are utilized as primary resources for additional trains and the transfer connections for passengers can be guaranteed in the new timetable. From numerical investigations, the proposed framework and associated techniques are tested and shown to be effective.

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