Multi-agent Workload Control and Flexible Job Shop Scheduling

Multi-agent Workload Control and Flexible Job Shop Scheduling PDF Author: Zuobao Wu
Publisher:
ISBN:
Category :
Languages : en
Pages :

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Book Description
Both new rules are nonparametric and easy to be implemented in practice. A job release mechanism is applied to reduce job flowtimes (up to 20.3%) and work-in-process inventory (up to 33.1%), without worsening earliness and tardiness, and lead time performances. Flexible job shop scheduling problems are an important extension of the classical job shop scheduling problems and present additional complexity. A multi-agent scheduling method with job earliness and tardiness objectives in a flexible job shop environment is proposed. A new job routing and sequencing mechanism is developed. In this mechanism, different criteria for two kinds of jobs are proposed to route these jobs. Two sequencing algorithms based on existing methods are developed to deal with these two kinds of jobs. The proposed methodology is implemented in a flexible job shop environment. The computational results indicate that the proposed methodology is extremely fast.

Multi-agent Workload Control and Flexible Job Shop Scheduling

Multi-agent Workload Control and Flexible Job Shop Scheduling PDF Author: Zuobao Wu
Publisher:
ISBN:
Category :
Languages : en
Pages :

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Book Description
Both new rules are nonparametric and easy to be implemented in practice. A job release mechanism is applied to reduce job flowtimes (up to 20.3%) and work-in-process inventory (up to 33.1%), without worsening earliness and tardiness, and lead time performances. Flexible job shop scheduling problems are an important extension of the classical job shop scheduling problems and present additional complexity. A multi-agent scheduling method with job earliness and tardiness objectives in a flexible job shop environment is proposed. A new job routing and sequencing mechanism is developed. In this mechanism, different criteria for two kinds of jobs are proposed to route these jobs. Two sequencing algorithms based on existing methods are developed to deal with these two kinds of jobs. The proposed methodology is implemented in a flexible job shop environment. The computational results indicate that the proposed methodology is extremely fast.

Generic Multi-Agent Reinforcement Learning Approach for Flexible Job-Shop Scheduling

Generic Multi-Agent Reinforcement Learning Approach for Flexible Job-Shop Scheduling PDF Author: Schirin Bär
Publisher: Springer Nature
ISBN: 3658391790
Category : Computers
Languages : en
Pages : 163

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Book Description
The production control of flexible manufacturing systems is a relevant component that must go along with the requirements of being flexible in terms of new product variants, new machine skills and reaction to unforeseen events during runtime. This work focuses on developing a reactive job-shop scheduling system for flexible and re-configurable manufacturing systems. Reinforcement Learning approaches are therefore investigated for the concept of multiple agents that control products including transportation and resource allocation.

Advances in Swarm Intelligence

Advances in Swarm Intelligence PDF Author: Ying Tan
Publisher: Springer
ISBN: 3319410091
Category : Computers
Languages : en
Pages : 639

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Book Description
This two-volume set LNCS 9712 and LNCS 9713 constitutes the refereed proceedings of the 7th International Conference on Swarm Intelligence, ICSI 2016, held in Bali, Indonesia, in June 2016. The 130 revised regular papers presented were carefully reviewed and selected from 231 submissions. The papers are organized in 22 cohesive sections covering major topics of swarm intelligence and related areas such as trend and models of swarm intelligence research; novel swarm-based optimization algorithms; swarming behaviour; some swarm intelligence algorithms and their applications; hybrid search optimization; particle swarm optimization; PSO applications; ant colony optimization; brain storm optimization; fireworks algorithms; multi-objective optimization; large-scale global optimization; biometrics; scheduling and planning; machine learning methods; clustering algorithm; classification; image classification and encryption; data mining; sensor networks and social networks; neural networks; swarm intelligence in management decision making and operations research; robot control; swarm robotics; intelligent energy and communications systems; and intelligent and interactive and tutoring systems.

Multi-Agent Based Beam Search for Real-Time Production Scheduling and Control

Multi-Agent Based Beam Search for Real-Time Production Scheduling and Control PDF Author: Shu Gang Kang
Publisher: Springer Science & Business Media
ISBN: 1447145763
Category : Technology & Engineering
Languages : en
Pages : 136

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Book Description
The Multi-Agent Based Beam Search (MABBS) method systematically integrates four major requirements of manufacturing production - representation capability, solution quality, computation efficiency, and implementation difficulty - within a unified framework to deal with the many challenges of complex real-world production planning and scheduling problems. Multi-agent Based Beam Search for Real-time Production Scheduling and Control introduces this method, together with its software implementation and industrial applications. This book connects academic research with industrial practice, and develops a practical solution to production planning and scheduling problems. To simplify implementation, a reusable software platform is developed to build the MABBS method into a generic computation engine. This engine is integrated with a script language, called the Embedded Extensible Application Script Language (EXASL), to provide a flexible and straightforward approach to representing complex real-world problems. Adopting an in-depth yet engaging and clear approach, and avoiding confusing or complicated mathematics and formulas, this book presents simple heuristics and a user-friendly software platform for system modelling. The supporting industrial case studies provide key information for students, lecturers, and industry practitioners alike. Multi-agent Based Beam Search for Real-time Production Scheduling and Control offers insights into the complex nature of and a practical total solution to production planning and scheduling, and inspires further research and practice in this promising research area.

Multi-Agent-Based Production Planning and Control

Multi-Agent-Based Production Planning and Control PDF Author: Jie Zhang
Publisher: John Wiley & Sons
ISBN: 111889006X
Category : Technology & Engineering
Languages : en
Pages : 420

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Book Description
At the crossroads of artificial intelligence, manufacturing engineering, operational research and industrial engineering and management, multi-agent based production planning and control is an intelligent and industrially crucial technology with increasing importance. This book provides a complete overview of multi-agent based methods for today’s competitive manufacturing environment, including the Job Shop Manufacturing and Re-entrant Manufacturing processes. In addition to the basic control and scheduling systems, the author also highlights advance research in numerical optimization methods and wireless sensor networks and their impact on intelligent production planning and control system operation. Enables students, researchers and engineers to understand the fundamentals and theories of multi-agent based production planning and control Written by an author with more than 20 years’ experience in studying and formulating a complete theoretical system in production planning technologies Fully illustrated throughout, the methods for production planning, scheduling and controlling are presented using experiments, numerical simulations and theoretical analysis Comprehensive and concise, Multi-Agent Based Production Planning and Control is aimed at the practicing engineer and graduate student in industrial engineering, operational research, and mechanical engineering. It is also a handy guide for advanced students in artificial intelligence and computer engineering.

Harmony Search and Nature Inspired Optimization Algorithms

Harmony Search and Nature Inspired Optimization Algorithms PDF Author: Neha Yadav
Publisher: Springer
ISBN: 981130761X
Category : Technology & Engineering
Languages : en
Pages : 1209

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Book Description
The book covers different aspects of real-world applications of optimization algorithms. It provides insights from the Fourth International Conference on Harmony Search, Soft Computing and Applications held at BML Munjal University, Gurgaon, India on February 7–9, 2018. It consists of research articles on novel and newly proposed optimization algorithms; the theoretical study of nature-inspired optimization algorithms; numerically established results of nature-inspired optimization algorithms; and real-world applications of optimization algorithms and synthetic benchmarking of optimization algorithms.

Bio-inspired Multi-agent Scheduling for Dynamic Flexible Job Shops with Sequence-dependent Setups

Bio-inspired Multi-agent Scheduling for Dynamic Flexible Job Shops with Sequence-dependent Setups PDF Author: Xuefeng Yu
Publisher:
ISBN:
Category : Biologically-inspired computing
Languages : en
Pages : 290

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Book Description
Addresses a multi-agent scheduling approach for dynamic flexible job shops with sequence-dependent setups. This includes studying, modeling, optimizing, and benchmarking this system. Proposes a multi-agent scheduling architecture and a novel coordination model, response threshold model for dynamic scheduling (RTM-DS).

Agent-Based Optimization

Agent-Based Optimization PDF Author: Ireneusz Czarnowski
Publisher: Springer
ISBN: 3642340970
Category : Technology & Engineering
Languages : en
Pages : 208

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Book Description
This volume presents a collection of original research works by leading specialists focusing on novel and promising approaches in which the multi-agent system paradigm is used to support, enhance or replace traditional approaches to solving difficult optimization problems. The editors have invited several well-known specialists to present their solutions, tools, and models falling under the common denominator of the agent-based optimization. The book consists of eight chapters covering examples of application of the multi-agent paradigm and respective customized tools to solve difficult optimization problems arising in different areas such as machine learning, scheduling, transportation and, more generally, distributed and cooperative problem solving.

Multiagent Scheduling

Multiagent Scheduling PDF Author: Alessandro Agnetis
Publisher: Springer Science & Business Media
ISBN: 3642418805
Category : Business & Economics
Languages : en
Pages : 281

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Book Description
Scheduling theory has received a growing interest since its origins in the second half of the 20th century. Developed initially for the study of scheduling problems with a single objective, the theory has been recently extended to problems involving multiple criteria. However, this extension has still left a gap between the classical multi-criteria approaches and some real-life problems in which not all jobs contribute to the evaluation of each criterion. In this book, we close this gap by presenting and developing multi-agent scheduling models in which subsets of jobs sharing the same resources are evaluated by different criteria. Several scenarios are introduced, depending on the definition and the intersection structure of the job subsets. Complexity results, approximation schemes, heuristics and exact algorithms are discussed for single-machine and parallel-machine scheduling environments. Definitions and algorithms are illustrated with the help of examples and figures.

Evolutionary Scheduling

Evolutionary Scheduling PDF Author: Keshav Dahal
Publisher: Springer Science & Business Media
ISBN: 3540485821
Category : Computers
Languages : en
Pages : 631

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Book Description
Evolutionary scheduling is a vital research domain at the interface of artificial intelligence and operational research. This edited book gives an overview of many of the current developments in the large and growing field of evolutionary scheduling. It demonstrates the applicability of evolutionary computational techniques to solve scheduling problems, not only to small-scale test problems, but also fully-fledged real-world problems.