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Author: Ashwani K Dhingra Publisher: ISBN: Category : Languages : en Pages : 0
Book Description
The paper makes an attempt to minimize the makespan and total tardiness in the flow shop scheduling using Artificial Neural Network (ANN). A feed forward back propagation neural network is implemented for the optimal solution of the problem. The network has been trained with the optimal sequences for different jobs on five machines problem. The trained network is further considered for solving the problem of flow shop scheduling. The analysis of all the algorithms that are implemented is carried out using Nawaz, Enscore and Ham (NEH) heuristic for 5 to 10 jobs with 5 machines under Sequence Dependent Set-up Time (SDST) environment with due dates and weights allotted to each job. With the help of NEH heuristic, different sequences have been generated for the considered problem. The number of sequences obtained is assembled in 270 × 10 matrix for the input of neural network. The network is trained with Baygon regression training algorithm and finally the results obtained from the neural network are found to be 93% accurate.
Author: Ashwani K Dhingra Publisher: ISBN: Category : Languages : en Pages : 0
Book Description
The paper makes an attempt to minimize the makespan and total tardiness in the flow shop scheduling using Artificial Neural Network (ANN). A feed forward back propagation neural network is implemented for the optimal solution of the problem. The network has been trained with the optimal sequences for different jobs on five machines problem. The trained network is further considered for solving the problem of flow shop scheduling. The analysis of all the algorithms that are implemented is carried out using Nawaz, Enscore and Ham (NEH) heuristic for 5 to 10 jobs with 5 machines under Sequence Dependent Set-up Time (SDST) environment with due dates and weights allotted to each job. With the help of NEH heuristic, different sequences have been generated for the considered problem. The number of sequences obtained is assembled in 270 × 10 matrix for the input of neural network. The network is trained with Baygon regression training algorithm and finally the results obtained from the neural network are found to be 93% accurate.
Author: Hamilton Emmons Publisher: Springer Science & Business Media ISBN: 1461451515 Category : Business & Economics Languages : en Pages : 346
Book Description
Using simplified notation and revealing unifying concepts, this book covers flow shop systems including two-machine, flexible and stochastic, and examines the reentrant flow shop, in which a job may be reprocessed at the same station or sequence of stations.
Author: Uday K. Chakraborty Publisher: Springer Science & Business Media ISBN: 3642028357 Category : Mathematics Languages : en Pages : 348
Book Description
For over fifty years now, the famous problem of flow shop and job shop scheduling has been receiving the attention of researchers in operations research, engineering, and computer science. Over the past several years, there has been a spurt of interest in computational intelligence heuristics and metaheuristics for solving this problem. This book seeks to present a study of the state of the art in this field and also directions for future research.
Author: Faruk Y?lmaz, Ömer Publisher: IGI Global ISBN: 1522529454 Category : Business & Economics Languages : en Pages : 480
Book Description
Today’s manufacturing systems are undergoing significant changes in the aspects of planning, production execution, and delivery. It is imperative to stay up-to-date on the latest trends in optimization to efficiently create products for the market. The Handbook of Research on Applied Optimization Methodologies in Manufacturing Systems is a pivotal reference source including the latest scholarly research on heuristic models for solving manufacturing and supply chain related problems. Featuring exhaustive coverage on a broad range of topics such as assembly ratio, car sequencing, and color constraints, this publication is ideally designed for practitioners seeking new comprehensive models for problem solving in manufacturing and supply chain management.
Author: John J. Grefenstette Publisher: Psychology Press ISBN: 1317760247 Category : Psychology Languages : en Pages : 345
Book Description
Computer solutions to many difficult problems in science and engineering require the use of automatic search methods that consider a large number of possible solutions to the given problems. This book describes recent advances in the theory and practice of one such search method, called Genetic Algorithms. Genetic algorithms are evolutionary search techniques based on principles derived from natural population genetics, and are currently being applied to a variety of difficult problems in science, engineering, and artificial intelligence.
Author: Igor V. Tetko Publisher: Springer Nature ISBN: 3030304876 Category : Computers Languages : en Pages : 848
Book Description
The proceedings set LNCS 11727, 11728, 11729, 11730, and 11731 constitute the proceedings of the 28th International Conference on Artificial Neural Networks, ICANN 2019, held in Munich, Germany, in September 2019. The total of 277 full papers and 43 short papers presented in these proceedings was carefully reviewed and selected from 494 submissions. They were organized in 5 volumes focusing on theoretical neural computation; deep learning; image processing; text and time series; and workshop and special sessions.
Author: Vasant, Pandian Publisher: IGI Global ISBN: 1522529918 Category : Computers Languages : en Pages : 948
Book Description
Modern optimization approaches have attracted an increasing number of scientists, decision makers, and researchers. As new issues in this field emerge, different optimization methodologies must be developed and implemented. The Handbook of Research on Emergent Applications of Optimization Algorithms is an authoritative reference source for the latest scholarly research on modern optimization techniques for solving complex problems of global optimization and their applications in economics and engineering. Featuring coverage on a broad range of topics and perspectives such as hybrid systems, non-cooperative games, and cryptography, this publication is ideally designed for students, researchers, and engineers interested in emerging developments in optimization algorithms.
Author: Xin-She Yang Publisher: Luniver Press ISBN: 1905986289 Category : Computers Languages : en Pages : 148
Book Description
Modern metaheuristic algorithms such as bee algorithms and harmony search start to demonstrate their power in dealing with tough optimization problems and even NP-hard problems. This book reviews and introduces the state-of-the-art nature-inspired metaheuristic algorithms in optimization, including genetic algorithms, bee algorithms, particle swarm optimization, simulated annealing, ant colony optimization, harmony search, and firefly algorithms. We also briefly introduce the photosynthetic algorithm, the enzyme algorithm, and Tabu search. Worked examples with implementation have been used to show how each algorithm works. This book is thus an ideal textbook for an undergraduate and/or graduate course. As some of the algorithms such as the harmony search and firefly algorithms are at the forefront of current research, this book can also serve as a reference book for researchers.
Author: Ashwani K Dhingra
Author: Ashwani K Dhingra
Author: Hamilton Emmons
Author: Uday K. Chakraborty
Author: Faruk Y?lmaz, Ömer
Author: 
Author: John J. Grefenstette
Author: Quang Chieu Ta
Author: Igor V. Tetko
Author: Vasant, Pandian
Author: Xin-She Yang