Job Shop Sequencing Problem on Two Machines with Time Lag Constraints

1973 ◽  
Vol 19 (9) ◽  
pp. 1063-1066 ◽  
Author(s):  
S. S. Panwalkar
2016 ◽  
Vol 50 (2) ◽  
pp. 223-232 ◽  
Author(s):  
Karim Amrouche ◽  
Mourad Boudhar
Keyword(s):  
Time Lag ◽  

Computing ◽  
2001 ◽  
Vol 67 (1) ◽  
pp. 83-90 ◽  
Author(s):  
E. J. Anderson ◽  
T. S. Jayram ◽  
T. Kimbrel

2020 ◽  
Author(s):  
Madiha Harrabi ◽  
Olfa Belkahla Driss ◽  
Khaled Ghedira

Abstract This paper addresses the job shop scheduling problem including time lag constraints. This is an extension of the job shop scheduling problem with many applications in real production environments, where extra (minimum and maximum) delays can be introduced between successive operations of the same job. It belongs to a category of problems known as NP-hard problem due to large solution space. Biogeography-based optimization is an evolutionary algorithm which is inspired by the migration of species between habitats, recently proposed by Simon in 2008 to optimize hard combinatorial optimization problems. We propose a hybrid biogeography-based optimization (HBBO) algorithm for solving the job shop scheduling problem with additional time lag constraints with minimization of total completion time. In the proposed HBBO, the effective greedy constructive heuristic is adapted to generate the initial population of habitat. Moreover, a local search metaheuristic is investigated in the mutation step in order to ameliorate the solution quality and enhance the diversity of the population. To assess the performance of HBBO, a series of experiments on well-known benchmark instances for job shop scheduling problem with time lag constraints is performed.


2021 ◽  
Vol 15 (5) ◽  
pp. 661-668
Author(s):  
Ryo Yonemoto ◽  
◽  
Haruhiko Suwa

Manufacturing systems are affected by uncertainties, such as machine failure or tool breakage, which result in system downtime and productivity deterioration. In machining processes, system downtime must be reduces. This study aims to establish an automated scheduling technique that flexibly responds to unforeseen events, such as machine failure, based on adaptive operations of the handling manipulator instead of an operation schedule for the machine tools. We propose an “adaptive manipulation” procedure for establishing a reactive revision policy. The reactive revision policy modifies a portion of the manipulator operation sequence, followed by the machine operation sequence. We conduct a physical scheduling simulation on a material-handling manipulator system imitating a job-shop manufacturing system. Through simulations involving machine breakdown scenarios, the applicability of the reactive revision policy based on adaptive manipulation is demonstrated.


2021 ◽  
Vol 8 (1) ◽  
pp. 8-21
Author(s):  
Radhakrishnan S ◽  
Saikeerthana D

This paper deals with sequencing problems for ‘n’ jobs on single machine, ‘n’ jobs on two machines, ‘n’ jobs on three machines and ‘n’ jobs on ‘m’ machines. Here, we consider the sequencing problem where the processing time, due dates, weights are taken as intervals. An algorithm is provided for obtaining an optimal sequence and also for determining the minimum duration taken to complete all the jobs. To illustrate this, numerical examples are provided.


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