Flowshop/no-idle or no-wait scheduling to minimize the sum of completion times

1982 ◽  
Vol 29 (3) ◽  
pp. 495-504 ◽  
Author(s):  
I. Adiri ◽  
D. Pohoryles
Keyword(s):  
No Wait ◽  
Completion Times ◽  
Sum Of Completion Times

Stochastic flowshop no-wait scheduling

1985 ◽  
Vol 22 (1) ◽  
pp. 240-246 ◽  
Author(s):  
E. Frostig ◽  
I. Adiri
Keyword(s):  
Independent Random Variable ◽  
Processing Time ◽  
Random Variables ◽  
Random Variable ◽  
Schedule Length ◽  
Special Cases ◽  
No Wait ◽  
Completion Times ◽  
Sum Of Completion Times

This paper deals with special cases of stochastic flowshop, no-wait, scheduling. n jobs have to be processed by m machines . The processing time of job Ji on machine Mj is an independent random variable Ti. It is possible to sequence the jobs so that , . At time 0 the realizations of the random variables Ti, (i are known. For m (m ≧ 2) machines it is proved that a special SEPT–LEPT sequence minimizes the expected schedule length; for two (m = 2) machines it is proved that the SEPT sequence minimizes the expected sum of completion times.

Stochastic flowshop no-wait scheduling

1985 ◽  
Vol 22 (01) ◽  
pp. 240-246
Author(s):  
E. Frostig ◽  
I. Adiri
Keyword(s):  
Independent Random Variable ◽  
Processing Time ◽  
Random Variables ◽  
Random Variable ◽  
Schedule Length ◽  
Special Cases ◽  
No Wait ◽  
Completion Times ◽  
Sum Of Completion Times

This paper deals with special cases of stochastic flowshop, no-wait, scheduling. n jobs have to be processed by m machines . The processing time of job Ji on machine Mj is an independent random variable Ti . It is possible to sequence the jobs so that , . At time 0 the realizations of the random variables Ti , ( i are known. For m (m ≧ 2) machines it is proved that a special SEPT–LEPT sequence minimizes the expected schedule length; for two (m = 2) machines it is proved that the SEPT sequence minimizes the expected sum of completion times.

An Efficient Batch Scheduling Model for Hospital Sterilization Services Using Genetic Algorithm

2021 ◽  
pp. 928-946
Author(s):  
Shubin Xu ◽  
John Wang
Keyword(s):  
Genetic Algorithm ◽  
Medical Devices ◽  
Programming Model ◽  
Flow Time ◽  
Nonlinear Integer Programming ◽  
Batch Scheduling ◽  
Scheduling Problem ◽  
Work In Process ◽  
Completion Times ◽  
Sum Of Completion Times

A major challenge faced by hospitals is to provide efficient medical services. The problem studied in this article is motivated by the hospital sterilization services where the washing step generally constitutes a bottleneck in the sterilization services. Therefore, an efficient scheduling of the washing operations to reduce flow time and work-in-process inventories is of great concern to management. In the washing step, different sets of reusable medical devices may be washed together as long as the washer capacity is not exceeded. Thus, the washing step is modeled as a batch scheduling problem where washers have nonidentical capacities and reusable medical device sets have different sizes and different ready times. The objective is to minimize the sum of completion times for washing operations. The problem is first formulated as a nonlinear integer programming model. Given that this problem is NP-hard, a genetic algorithm is then proposed to heuristically solve the problem. Computational experiments show that the proposed algorithm is capable of consistently obtaining high-quality solutions in short computation times.

scholarly journals Tabu search for a parallel-machine scheduling problem with periodic maintenance, job rejection and weighted sum of completion times

2021 ◽  
Author(s):  
Hanane Krim ◽  
Nicolas Zufferey ◽  
Jean-Yves Potvin ◽  
Rachid Benmansour ◽  
David Duvivier
Keyword(s):  
Tabu Search ◽  
Parallel Machines ◽  
Mixed Integer ◽  
Weighted Sum ◽  
Scheduling Problem ◽  
Maintenance Policy ◽  
Mixed Integer Linear Program ◽  
Job Rejection ◽  
Completion Times ◽  
Sum Of Completion Times

AbstractWe consider in this work a bicriteria scheduling problem on two different parallel machines with a periodic preventive maintenance policy. The two objectives considered involve minimization of job rejection costs and weighted sum of completion times. They are handled through a lexicographic approach, due to a natural hierarchy among the two objectives in the applications considered. The main contributions of this paper are first to present a new problem relevant to practice, second, to develop a mixed-integer-linear-program model for the problem, and third, to introduce two generalizable tabu-search metaheuristics relying on different neighborhood structures and solution spaces. Computational results for 120 instances (generated from a real case) are reported to empirically demonstrate the effectiveness of the proposed metaheuristics.

scholarly journals Scheduling a proportionate flow shop of batching machines

2020 ◽  
Vol 23 (5) ◽  
pp. 575-593
Author(s):  
Christoph Hertrich ◽  
Christian Weiß ◽  
Heiner Ackermann ◽  
Sandy Heydrich ◽  
Sven O. Krumke
Keyword(s):  
Polynomial Time ◽  
Flow Shop ◽  
Fixed Number ◽  
Release Dates ◽  
Proportionate Flow Shop ◽  
Weighted Number ◽  
Late Jobs ◽  
Two Machines ◽  
Completion Times ◽  
Sum Of Completion Times

Abstract In this paper we study a proportionate flow shop of batching machines with release dates and a fixed number $$m \ge 2$$ m ≥ 2 of machines. The scheduling problem has so far barely received any attention in the literature, but recently its importance has increased significantly, due to applications in the industrial scaling of modern bio-medicine production processes. We show that for any fixed number of machines, the makespan and the sum of completion times can be minimized in polynomial time. Furthermore, we show that the obtained algorithm can also be used to minimize the weighted total completion time, maximum lateness, total tardiness and (weighted) number of late jobs in polynomial time if all release dates are 0. Previously, polynomial time algorithms have only been known for two machines.

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