Studying the effect of different combinations of timetabling with sequencing algorithms to solve the no-wait job shop scheduling problem

Samarghandi, Hamed; ElMekkawy, Tarek Y.; Ibrahem, Almehdi M.

doi:10.1080/00207543.2013.784410

Cited by 13 publications

(1 citation statement)

References 35 publications

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“…Furthermore, a modified complete local search with memory was devised by authors as sequencing algorithm. Samarghandi et al [28] investigated the relative importance of sequencing and timetabling parts. To this end, three different sequencing algorithms, i.e., a TS, a hybrid of tabu search and variable neighborhood search, and a hybrid of tabu search and particle swarm optimization were designed and combined with four different timetabling methods.…”

Section: Introductionmentioning

confidence: 99%

A two-stage no-wait job shop scheduling problem by using a neuro-evolutionary variable neighborhood search

Mokhtari

2014

Int J Adv Manuf Technol

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A two-stage order scheduling problem with an additional no-wait condition is studied in this article. All orders must be processed from start to completion without any waiting between operations and any interruption within operations. Examples of such a problem occur in steel production and pharmaceutical, chemical, and construction industries. A new optimization method which is based on a combination of an enhanced variable neighborhood search (VNS) and an artificial neural network (ANN) is devised in this paper. The aim is to simultaneously employ the key characteristics of two approaches to achieve superior solutions in solving the addressed optimization problem. In proposed algorithm, the VNS performs a global search whereas the ANN plays the role of intensive initial solution. The individual obtained by feed forward back-propagation ANN is improved within enhanced VNS iterations. The two techniques complement each other when ANN feeds its best solution to the VNS algorithm. Furthermore, to establish the best sequence of order pairs, a team process algorithm is also embedded into the VNS to enhance the search diversification as well as its intensification. The performance of proposed neuro-evolutionary algorithm is investigated via computational experiments, and the results prove the appropriate performance of suggested VNS-ANN algorithm.

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Section: Introductionmentioning

confidence: 99%

A two-stage no-wait job shop scheduling problem by using a neuro-evolutionary variable neighborhood search

Mokhtari

2014

Int J Adv Manuf Technol

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Minimizing the makespan in a flow shop environment under minimum and maximum time-lag constraints

Samarghandi

2019

Computers & Industrial Engineering

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Solving the no-wait job shop scheduling problem with due date constraints: A problem transformation approach

Samarghandi

2019

Computers & Industrial Engineering

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Studying the effect of different combinations of timetabling with sequencing algorithms to solve the no-wait job shop scheduling problem

Cited by 13 publications

References 35 publications

A two-stage no-wait job shop scheduling problem by using a neuro-evolutionary variable neighborhood search

A two-stage no-wait job shop scheduling problem by using a neuro-evolutionary variable neighborhood search

Minimizing the makespan in a flow shop environment under minimum and maximum time-lag constraints

Solving the no-wait job shop scheduling problem with due date constraints: A problem transformation approach

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