Download or read book A Genetic Algorithm based Scheduling System for Dynamic Job Shop Scheduling Problems written by Shyh-Chang Lin and published by . This book was released on 1997 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Intelligent and Evolutionary Systems written by Mitsuo Gen and published by Springer Science & Business Media. This book was released on 2009-03-12 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers fourteen select papers presented at the recent Asia-Pacific Symposia on Intelligent and Evolutionary Systems. They illustrate the breadth of research in the field with applications ranging from business to medicine to network optimization.

Download or read book A Promising Genetic Algorithm Approach to Job shop Scheduling Rescheduling and Open shop Scheduling Problems written by Hsiao-Lan Fang and published by . This book was released on 1993 with total page 9 pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract: "The general job-shop scheduling problem is known to be extremely hard. We describe a GA approach which produces reasonably good results very quickly on standard benchmark job-shop scheduling problems, better than previous efforts using genetic algorithms for this task, and comparable to existing conventional search-based methods. The representation used is a variant of one known to work moderately well for the traveling salesman problem. It has the considerable merit that crossover will always produce legal schedules. A novel method for performance enhancement is examined based on dynamic sampling of the convergence rates in different parts of the genome. Our approach also promises to effectively address the open-shop scheduling problem and the job-shop rescheduling problem."

Download or read book Intelligent Quality Systems written by Duc T. Pham and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 212 pages. Available in PDF, EPUB and Kindle. Book excerpt: Although the tenn quality does not have a precise and universally accepted definition, its meaning is generally well understood: quality is what makes the difference between success and failure in a competitive world. Given the importance of quality, there is a need for effective quality systems to ensure that the highest quality is achieved within given constraints on human, material or financial resources. This book discusses Intelligent Quality Systems, that is quality systems employing techniques from the field of Artificial Intelligence (AI). The book focuses on two popular AI techniques, expert or knowledge-based systems and neural networks. Expert systems encapsulate human expertise for solving difficult problems. Neural networks have the ability to learn problem solving from examples. The aim of the book is to illustrate applications of these techniques to the design and operation of effective quality systems. The book comprises 8 chapters. Chapter 1 provides an introduction to quality control and a general discussion of possible AI-based quality systems. Chapter 2 gives technical information on the key AI techniques of expert systems and neural networks. The use of these techniques, singly and in a combined hybrid fonn, to realise intelligent Statistical Process Control (SPC) systems for quality improvement is the subject of Chapters 3-5. Chapter 6 covers experimental design and the Taguchi method which is an effective technique for designing quality into a product or process. The application of expert systems and neural networks to facilitate experimental design is described in this chapter.

Download or read book Soft Computing and Industry written by Rajkumar Roy and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 862 pages. Available in PDF, EPUB and Kindle. Book excerpt: Soft computing embraces various methodologies for the development of intelligent systems that have been successfully applied to a large number of real-world problems. Soft Computing in Industry contains a collection of papers that were presented at the 6th On-line World Conference on Soft Computing in Industrial Applications that was held in September 2001. It provides a comprehensive overview of recent theoretical developments in soft computing as well as of successful industrial applications. It is divided into seven parts covering material on: keynote papers on various subjects ranging from computing with autopoietic systems to the effects of the Internet on education; intelligent control; classification, clustering and optimization; image and signal processing; agents, multimedia and Internet; theoretical advances; prediction, design and diagnosis. The book is aimed at researchers and professional engineers who develop and apply intelligent systems in computer engineering.

Download or read book Multiobjective Scheduling by Genetic Algorithms written by Tapan P. Bagchi and published by Springer Science & Business Media. This book was released on 1999-08-31 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multiobjective Scheduling by Genetic Algorithms describes methods for developing multiobjective solutions to common production scheduling equations modeling in the literature as flowshops, job shops and open shops. The methodology is metaheuristic, one inspired by how nature has evolved a multitude of coexisting species of living beings on earth. Multiobjective flowshops, job shops and open shops are each highly relevant models in manufacturing, classroom scheduling or automotive assembly, yet for want of sound methods they have remained almost untouched to date. This text shows how methods such as Elitist Nondominated Sorting Genetic Algorithm (ENGA) can find a bevy of Pareto optimal solutions for them. Also it accents the value of hybridizing Gas with both solution-generating and solution-improvement methods. It envisions fundamental research into such methods, greatly strengthening the growing reach of metaheuristic methods. This book is therefore intended for students of industrial engineering, operations research, operations management and computer science, as well as practitioners. It may also assist in the development of efficient shop management software tools for schedulers and production planners who face multiple planning and operating objectives as a matter of course.

Download or read book Computational Intelligence in Flow Shop and Job Shop Scheduling written by Uday K. Chakraborty and published by Springer. This book was released on 2009-09-30 with total page 348 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book A Genetic Algorithm for the Flexible Job shop Scheduling Problem written by F. Pezzella and published by . This book was released on 2008 with total page 11 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Multiobjective Scheduling by Genetic Algorithms written by Tapan P. Bagchi and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 369 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multiobjective Scheduling by Genetic Algorithms describes methods for developing multiobjective solutions to common production scheduling equations modeling in the literature as flowshops, job shops and open shops. The methodology is metaheuristic, one inspired by how nature has evolved a multitude of coexisting species of living beings on earth. Multiobjective flowshops, job shops and open shops are each highly relevant models in manufacturing, classroom scheduling or automotive assembly, yet for want of sound methods they have remained almost untouched to date. This text shows how methods such as Elitist Nondominated Sorting Genetic Algorithm (ENGA) can find a bevy of Pareto optimal solutions for them. Also it accents the value of hybridizing Gas with both solution-generating and solution-improvement methods. It envisions fundamental research into such methods, greatly strengthening the growing reach of metaheuristic methods. This book is therefore intended for students of industrial engineering, operations research, operations management and computer science, as well as practitioners. It may also assist in the development of efficient shop management software tools for schedulers and production planners who face multiple planning and operating objectives as a matter of course.

Download or read book Online Scheduling in Manufacturing written by Haruhiko Suwa and published by Springer Science & Business Media. This book was released on 2012-10-11 with total page 157 pages. Available in PDF, EPUB and Kindle. Book excerpt: Online scheduling is recognized as the crucial decision-making process of production control at a phase of “being in production" according to the released shop floor schedule. Online scheduling can be also considered as one of key enablers to realize prompt capable-to-promise as well as available-to-promise to customers along with reducing production lead times under recent globalized competitive markets. Online Scheduling in Manufacturing introduces new approaches to online scheduling based on a concept of cumulative delay. The cumulative delay is regarded as consolidated information of uncertainties under a dynamic environment in manufacturing and can be collected constantly without much effort at any points in time during a schedule execution. In this approach, the cumulative delay of the schedule has the important role of a criterion for making a decision whether or not a schedule revision is carried out. The cumulative delay approach to trigger schedule revisions has the following capabilities for the practical decision-making: 1. To reduce frequent schedule revisions which do not necessarily improve a current situation with much expense for its operation; 2. To avoid overreacting to disturbances dependent on strongly an individual shop floor circumstance; and 3. To simplify the monitoring process of a schedule status. Online Scheduling in Manufacturing will be of interest to both practitioners and researchers who work in planning and scheduling in manufacturing. Readers will find the importance of when-to-revise policies during a schedule execution and their influences on scheduling results.

Download or read book Dynamic Scheduling and Sequencing of Machines and Automated Guided Vehicles Using Genetic Algorithms written by Amirabbas Tabatabaei and published by . This book was released on 2019 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Scheduling of machines has been interested in flexible manufacturing systems due to the flexibility and simultaneous task process capability of such production systems. Advanced material handling systems such as automated guided vehicles are being used in flexible manufacturing systems. Automated guided vehicles are flexible and easy to utilize in flexible manufacturing systems. Therefore, dynamic simultaneous scheduling and sequencing of flexible manufacturing systems and automated guided vehicles, are considered as the main focus of this study. Scheduling of machines and automated guided vehicles, if considered separately, are NP-Hard problems. Similarly, simultaneous scheduling of machines and automated vehicles are NP-Hard. Although there are some studies on static scheduling of machines and vehicles, dynamic scheduling has not been studied thoroughly in the literature. Population based search algorithms have been used to solve complex problems and in order to find solution sets. In this study, a genetic algorithm is designed to propose solutions for simultaneous scheduling and sequencing of machines and automated guided vehicles in flexible manufacturing systems environments in dynamic situation. In order to assist designers of manufacturing systems, two design variables were added to mathematical model presented in this study. These two design variables were battery charge capacity and number of active automated guided vehicles in the system. A specific time frame was assumed for each job set to schedule machines and automated guided vehicles dynamically. The genetic algorithm was initially validated by bench mark problems from previous studies. Ten job sets previously scheduled by other researchers using heuristic ii and meta heuristic approaches were used. Precedence constrain connects tasks by a network. There are 4 layouts which define machine locations and automated guided vehicle paths. Through solving the static scheduling problem of previous studies, the genetic algorithm was validated. Thereafter, a set of dynamic scheduling problem was developed from previous bench mark problems and solved using the modified model proposed and validated in this study. Dynamic scheduling problem results show that the genetic algorithm is not limited by the number of components to schedule in the mathematical model. In addition, it was found that as the number of active automated guided vehicles increase in the system, the total completion time decreases. This fact is due to the availability of automated guided vehicle to travel demand. Although having more vehicles in the system may increase the costs of production, one could argue the advantages and disadvantages. According to the results, the total completion time for the first static and dynamic scheduling problems (Job set 1, Layout 1) for one to four vehicles are 161 to 76 and 481 to 186 respectively. Another observation was finding best vehicle type based on the battery charge capacity. Automated guided vehicles maintenance and costs are related to the type and their ability to run with a single charge. Therefore, it is important to choose vehicles which fulfill the needs and requirements of the system. The battery charge capacities were from 25 to 100 which affects the total completion times for static and dynamic scheduling problems relatively. The total completion times for static scheduling problems are 100 to 96 for battery capacities 25 to 100. Likewise dynamic scheduling problem completion times are 291.5 to 272.5.

Download or read book A Job shop Scheduling Problem JSSP Using Genetic Algorithm GA written by Mahanim Omar and published by . This book was released on 2006 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Genetic Programming for Production Scheduling written by Fangfang Zhang and published by Springer Nature. This book was released on 2021-11-12 with total page 357 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces readers to an evolutionary learning approach, specifically genetic programming (GP), for production scheduling. The book is divided into six parts. In Part I, it provides an introduction to production scheduling, existing solution methods, and the GP approach to production scheduling. Characteristics of production environments, problem formulations, an abstract GP framework for production scheduling, and evaluation criteria are also presented. Part II shows various ways that GP can be employed to solve static production scheduling problems and their connections with conventional operation research methods. In turn, Part III shows how to design GP algorithms for dynamic production scheduling problems and describes advanced techniques for enhancing GP’s performance, including feature selection, surrogate modeling, and specialized genetic operators. In Part IV, the book addresses how to use heuristics to deal with multiple, potentially conflicting objectives in production scheduling problems, and presents an advanced multi-objective approach with cooperative coevolution techniques or multi-tree representations. Part V demonstrates how to use multitask learning techniques in the hyper-heuristics space for production scheduling. It also shows how surrogate techniques and assisted task selection strategies can benefit multitask learning with GP for learning heuristics in the context of production scheduling. Part VI rounds out the text with an outlook on the future. Given its scope, the book benefits scientists, engineers, researchers, practitioners, postgraduates, and undergraduates in the areas of machine learning, artificial intelligence, evolutionary computation, operations research, and industrial engineering.

Download or read book An Adaptive Representation for a Genetic Algorithm in Solving Flexible Job shop Scheduling and Rescheduling Problems written by Prakarn Unachak and published by . This book was released on 2010 with total page 204 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Evolutionary Computation in Scheduling written by Amir H. Gandomi and published by John Wiley & Sons. This book was released on 2020-04-09 with total page 323 pages. Available in PDF, EPUB and Kindle. Book excerpt: Presents current developments in the field of evolutionary scheduling and demonstrates the applicability of evolutionary computational techniques to solving scheduling problems This book provides insight into the use of evolutionary computations (EC) in real-world scheduling, showing readers how to choose a specific evolutionary computation and how to validate the results using metrics and statistics. It offers a spectrum of real-world optimization problems, including applications of EC in industry and service organizations such as healthcare scheduling, aircraft industry, school timetabling, manufacturing systems, and transportation scheduling in the supply chain. It also features problems with different degrees of complexity, practical requirements, user constraints, and MOEC solution approaches. Evolutionary Computation in Scheduling starts with a chapter on scientometric analysis to analyze scientific literature in evolutionary computation in scheduling. It then examines the role and impacts of ant colony optimization (ACO) in job shop scheduling problems, before presenting the application of the ACO algorithm in healthcare scheduling. Other chapters explore task scheduling in heterogeneous computing systems and truck scheduling using swarm intelligence, application of sub-population scheduling algorithm in multi-population evolutionary dynamic optimization, task scheduling in cloud environments, scheduling of robotic disassembly in remanufacturing using the bees algorithm, and more. This book: Provides a representative sampling of real-world problems currently being tackled by practitioners Examines a variety of single-, multi-, and many-objective problems that have been solved using evolutionary computations, including evolutionary algorithms and swarm intelligence Consists of four main parts: Introduction to Scheduling Problems, Computational Issues in Scheduling Problems, Evolutionary Computation, and Evolutionary Computations for Scheduling Problems Evolutionary Computation in Scheduling is ideal for engineers in industries, research scholars, advanced undergraduates and graduate students, and faculty teaching and conducting research in Operations Research and Industrial Engineering.

Download or read book Algorithms for Scheduling Problems written by FrankWerner and published by MDPI. This book was released on 2018-08-24 with total page 209 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a printed edition of the Special Issue " Algorithms for Scheduling Problems" that was published in Algorithms

Download or read book A Genetic Algorithm for Job Shop Scheduling Problem with Fuzzy Processing Times and Fuzzy Due Dates written by Narasimharao Konduri and published by . This book was released on 2003 with total page 118 pages. Available in PDF, EPUB and Kindle. Book excerpt: