Lot Streaming In Hybrid Flow Shop Scheduling

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.

Lot Processing in Hybrid Flow Shop Scheduling Problem.

This book gathers peer-reviewed research papers based on selected contributions to the 13th Logistics Management Conference (LM 2023), held on 13.-15.09.2023, in Dresden, Germany. They report on cutting-edge methods and strategies for supply chain management, digitalisation, sustainable development, discussing their application in both manufacturing and service industries.

This book discusses the process of "Lot Streaming" and how it can significantly improve the overall performance of a production process, and thereby, make the operation of a manufacturing system lean. It provides a complete introduction to the Flow Shop Lot Streaming Problem and provides a historical perspective. It further presents algorithms for a variety of lot streaming problems with numerical illustrations for ease of understanding and implementation.

This two-volume set LNCS 10954 and LNCS 10955 constitutes - in conjunction with the volume LNAI 10956 - the refereed proceedings of the 14th International Conference on Intelligent Computing, ICIC 2018, held in Wuhan, China, in August 2018. The 275 full papers and 72 short papers of the three proceedings volumes were carefully reviewed and selected from 632 submissions. The papers are organized in topical sections such as Neural Networks.- Pattern Recognition.- Image Processing.- Intelligent Computing in Robotics.- Intelligent Control and Automation.- Intelligent Data Analysis and Prediction.- Fuzzy Theory and Algorithms.- Supervised Learning.- Unsupervised Learning.- Kernel Methods and Supporting Vector Machines.- Knowledge Discovery and Data Mining.- Natural Language Processing and Computational Linguistics.- Gene Expression Array Analysis.- Systems Biology.- Computational Genomics.- Computational Proteomics.- Gene Regulation Modeling and Analysis.- Protein-Protein Interaction Prediction.- Next-Gen Sequencing and Metagenomics.- Structure Prediction and Folding.- Evolutionary Optimization for Scheduling.- High-Throughput Biomedical Data Integration and Mining.- Machine Learning Algorithms and Applications.- Heuristic Optimization Algorithms for Real-World Applications.- Evolutionary Multi-Objective Optimization and Its Applications.- Swarm Evolutionary Algorithms for Scheduling and Combinatorial.- Optimization.- Swarm Intelligence and Applications in Combinatorial Optimization.- Advances in Metaheuristic Optimization Algorithm.- Advances in Image Processing and Pattern Recognition Techniques.- AI in Biomedicine.- Bioinformatics.- Biometrics Recognition.- Information Security.- Virtual Reality and Human-Computer Interaction.- Healthcare Informatics Theory and Methods.- Intelligent Computing in Computer Vision.- Intelligent Agent and Web Applications.- Reinforcement Learning.- Machine Learning.- Modeling, Simulation, and Optimization of Biological Systems.- Biomedical Data Modeling and Mining.- Cheminformatics.- Intelligent Computing in Computational Biology.- Protein Structure and Function Prediction.- Biomarker Discovery.- Hybrid Computational Intelligence: Theory and Application in Bioinformatics, Computational Biology and Systems Biology.- IoT and Smart Data.- Intelligent Systems and Applications for Bioengineering.- Evolutionary Optimization: Foundations and Its Applications to Intelligent Data Analytics.- Protein and Gene Bioinformatics: Analysis, Algorithms and Applications.

This book is dedicated to questions of production planning and scheduling activities both in general and in semiconductor manufacturing environments, which have the characteristics of high volume and high mixture. It explores topics such as shop models, work-in-process management, the treatment of setup times, basic techniques of lot batching and splitting, lot sizing and group technology approaches, as well as rescheduling questions. A number of directions for further research is suggested in the book, and a broad collection of references is provided.

Generally speaking, scheduling is the procedure of mapping a set of tasks or jobs (studied objects) to a set of target resources efficiently. More specifically, as a part of a larger planning and scheduling process, production scheduling is essential for the proper functioning of a manufacturing enterprise. This book presents ten chapters divided into five sections. Section 1 discusses rescheduling strategies, policies, and methods for production scheduling. Section 2 presents two chapters about flow shop scheduling. Section 3 describes heuristic and metaheuristic methods for treating the scheduling problem in an efficient manner. In addition, two test cases are presented in Section 4. The first uses simulation, while the second shows a real implementation of a production scheduling system. Finally, Section 5 presents some modeling strategies for building production scheduling systems. This book will be of interest to those working in the decision-making branches of production, in various operational research areas, as well as computational methods design. People from a diverse background ranging from academia and research to those working in industry, can take advantage of this volume.

This book – in conjunction with the volumes LNCS 8588 and LNBI 8590 – constitutes the refereed proceedings of the 10th International Conference on Intelligent Computing, ICIC 2014, held in Taiyuan, China, in August 2014. The 85 papers of this volume were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections such as soft computing; artificial bee colony algorithms; unsupervised learning; kernel methods and supporting vector machines; machine learning; fuzzy theory and algorithms; image processing; intelligent computing in computer vision; intelligent computing in communication networks; intelligent image/document retrievals; intelligent data analysis and prediction; intelligent agent and Web applications; intelligent fault diagnosis; knowledge representation/reasoning; knowledge discovery and data mining; natural language processing and computational linguistics; next gen sequencing and metagenomics; intelligent computing in scheduling and engineering optimization; advanced modeling, control and optimization techniques for complex engineering systems; complex networks and their applications; time series forecasting and analysis using artificial neural networks; computer human interaction using multiple visual cues and intelligent computing; biometric system and security for intelligent computing.