Hybrid Adaptive Predictive Control For The Multi Vehicle Dynamic Pick Up And Delivery Problem Based On Genetic Algorithms And Fuzzy Clustering
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Hybrid Predictive Control for Dynamic Transport Problems
| Author | : Alfredo Nunez |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 183 |
| Release | : 2012-10-03 |
| Genre | : Technology & Engineering |
| ISBN | : 1447143515 |
Hybrid Predictive Control for Dynamic Transport Problems develops methods for the design of predictive control strategies for nonlinear-dynamic hybrid discrete-/continuous-variable systems. The methodology is designed for real-time applications, particularly the study of dynamic transport systems. Operational and service policies are considered, as well as cost reduction. The control structure is based on a sound definition of the key variables and their evolution. A flexible objective function able to capture the predictive behaviour of the system variables is described. Coupled with efficient algorithms, mainly drawn from area of computational intelligence, this is shown to optimize performance indices for real-time applications. The framework of the proposed predictive control methodology is generic and, being able to solve nonlinear mixed integer optimization problems dynamically, is readily extendable to other industrial processes. The main topics of this book are: · hybrid predictive control (HPC) design based on evolutionary multiobjective optimization (EMO); · HPC based on EMO for dial-a-ride systems; and · HPC based on EMO for operational decisions in public transport systems. Hybrid Predictive Control for Dynamic Transport Problems is a comprehensive analysis of HPC and its application to dynamic transport systems. Introductory material on evolutionary algorithms is presented in summary in an appendix. The text will be of interest to control and transport engineers working on the operational optimization of transport systems and to academic researchers working with hybrid systems. The potential applications of the generic methods presented here to other process fields will make the book of interest to a wider group of researchers, scientists and graduate students working in other control-related disciplines.
Pro-active Dynamic Vehicle Routing
| Author | : Francesco Ferrucci |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 356 |
| Release | : 2013-03-14 |
| Genre | : Business & Economics |
| ISBN | : 3642334725 |
This book deals with transportation processes denoted as the Real-time Distribution of Perishable Goods (RDOPG). The book presents three contributions that are made to the field of transportation. First, a model considering the minimization of customer inconvenience is formulated. Second, a pro-active real-time control approach is proposed. Stochastic knowledge is generated from past request information by a new forecasting approach and is used in the pro-active approach to guide vehicles to request-likely areas before real requests arrive there. Various computational results are presented to show that in many cases the pro-active approach is able to achieve significantly improved results. Moreover, a measure for determining the structural quality of request data sets is also proposed. The third contribution of this book is a method that is presented for considering driver inconvenience aspects which arise from vehicle en-route diversion activities. Specifically, this method makes it possible to restrict the number of performed vehicle en-route diversion activities.
Vehicle Routing
| Author | : Paolo Toth |
| Publisher | : SIAM |
| Total Pages | : 467 |
| Release | : 2014-12-05 |
| Genre | : Mathematics |
| ISBN | : 1611973597 |
Vehicle routing problems, among the most studied in combinatorial optimization, arise in many practical contexts (freight distribution and collection, transportation, garbage collection, newspaper delivery, etc.). Operations researchers have made significant developments in the algorithms for their solution, and Vehicle Routing: Problems, Methods, and Applications, Second Edition reflects these advances. The text of the new edition is either completely new or significantly revised and provides extensive and complete state-of-the-art coverage of vehicle routing by those who have done most of the innovative research in the area; it emphasizes methodology related to specific classes of vehicle routing problems and, since vehicle routing is used as a benchmark for all new solution techniques, contains a complete overview of current solutions to combinatorial optimization problems. It also includes several chapters on important and emerging applications, such as disaster relief and green vehicle routing.
Approximate Dynamic Programming for Dynamic Vehicle Routing
| Author | : Marlin Wolf Ulmer |
| Publisher | : Springer |
| Total Pages | : 209 |
| Release | : 2017-04-19 |
| Genre | : Business & Economics |
| ISBN | : 3319555111 |
This book provides a straightforward overview for every researcher interested in stochastic dynamic vehicle routing problems (SDVRPs). The book is written for both the applied researcher looking for suitable solution approaches for particular problems as well as for the theoretical researcher looking for effective and efficient methods of stochastic dynamic optimization and approximate dynamic programming (ADP). To this end, the book contains two parts. In the first part, the general methodology required for modeling and approaching SDVRPs is presented. It presents adapted and new, general anticipatory methods of ADP tailored to the needs of dynamic vehicle routing. Since stochastic dynamic optimization is often complex and may not always be intuitive on first glance, the author accompanies the ADP-methodology with illustrative examples from the field of SDVRPs. The second part of this book then depicts the application of the theory to a specific SDVRP. The process starts from the real-world application. The author describes a SDVRP with stochastic customer requests often addressed in the literature, and then shows in detail how this problem can be modeled as a Markov decision process and presents several anticipatory solution approaches based on ADP. In an extensive computational study, he shows the advantages of the presented approaches compared to conventional heuristics. To allow deep insights in the functionality of ADP, he presents a comprehensive analysis of the ADP approaches.
Intelligent Computing Theories and Application
| Author | : De-Shuang Huang |
| Publisher | : Springer Nature |
| Total Pages | : 859 |
| Release | : 2022-08-14 |
| Genre | : Technology & Engineering |
| ISBN | : 3031138708 |
This two-volume set of LNCS 13393 and LNCS 13394 constitutes - in conjunction with the volume LNAI 13395 - the refereed proceedings of the 18th International Conference on Intelligent Computing, ICIC 2022, held in Xi'an, China, in August 2022. The 209 full papers of the three proceedings volumes were carefully reviewed and selected from 449 submissions. This year, the conference concentrated mainly on the theories and methodologies as well as the emerging applications of intelligent computing. Its aim was to unify the picture of contemporary intelligent computing techniques as an integral concept that highlights the trends in advanced computational intelligence and bridges theoretical research with applications. Therefore, the theme for this conference was “Advanced Intelligent Computing Technology and Applications”. Papers focused on this theme were solicited, addressing theories, methodologies, and applications in science and technology.
Advances in Computer Science and Information Engineering
| Author | : David Jin |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 702 |
| Release | : 2012-05-16 |
| Genre | : Technology & Engineering |
| ISBN | : 3642301266 |
CSIE2012 is an integrated conference concentrating its focus on Computer Science and Information Engineering . In the proceeding, you can learn much more knowledge about Computer Science and Information Engineering of researchers from all around the world. The main role of the proceeding is to be used as an exchange pillar for researchers who are working in the mentioned fields. In order to meet the high quality of Springer, AISC series, the organization committee has made their efforts to do the following things. Firstly, poor quality paper has been refused after reviewing course by anonymous referee experts. Secondly, periodically review meetings have been held around the reviewers about five times for exchanging reviewing suggestions. Finally, the conference organizers had several preliminary sessions before the conference. Through efforts of different people and departments, the conference will be successful and fruitful.
Intelligent and Fuzzy Techniques: Smart and Innovative Solutions
| Author | : Cengiz Kahraman |
| Publisher | : Springer Nature |
| Total Pages | : 1701 |
| Release | : 2020-07-10 |
| Genre | : Technology & Engineering |
| ISBN | : 3030511561 |
This book gathers the most recent developments in fuzzy & intelligence systems and real complex systems presented at INFUS 2020, held in Istanbul on July 21–23, 2020. The INFUS conferences are a well-established international research forum to advance the foundations and applications of intelligent and fuzzy systems, computational intelligence, and soft computing, highlighting studies on fuzzy & intelligence systems and real complex systems at universities and international research institutions. Covering a range of topics, including the theory and applications of fuzzy set extensions such as intuitionistic fuzzy sets, hesitant fuzzy sets, spherical fuzzy sets, and fuzzy decision-making; machine learning; risk assessment; heuristics; and clustering, the book is a valuable resource for academics, M.Sc. and Ph.D. students, as well as managers and engineers in industry and the service sectors.
Model-Based Control of Logistics Processes in Volatile Environments
| Author | : Jörn Schönberger |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 186 |
| Release | : 2011-05-04 |
| Genre | : Business & Economics |
| ISBN | : 1441996826 |
This monograph presents results originating from a research project investigating autonomous adaptation of vehicle schedules and systematically develops and evaluates innovative ideas for the management of transportation processes in volatile scenarios. Showing the progress made in the development of the methodological toolbox for decision support in dynamic process management is the major motivation behind this book. The result is a new integrated approach to dynamic decision making. Existing process planning approaches for volatile environments and their application boundaries are investigated in Part I. Part II introduces the concept of feedback-controlled adaptive decision models and proposes the required extensions of the online decision making framework and of multi-agent systems. A comprehensive evaluation of the proposed decision model adaptation framework based on computational simulation experiments is reported in Part III and demonstrates the predominance of the new approach. Distinguishing features of this book are: -It provides the first contribution to the operational management of processes in supply networks that explicitly addresses the two challenges of dynamics and distributed decision making simultaneously. -It systematically approaches the limits of model-based process planning but also proposes methods to extend the application boundaries. -Software prototypes are developed and a comprehensive evaluation within numerical simulation experiments is executed. -The observed results are discussed with an explicit focus on specific performance indicators (flexibility, stability and robustness). -The strict interdisciplinary approach merging the requirements and needs of management sciences, operations research and computer sciences is pursued throughout the book.
Computational Science – ICCS 2021
| Author | : Maciej Paszynski |
| Publisher | : Springer Nature |
| Total Pages | : 815 |
| Release | : 2021-06-10 |
| Genre | : Computers |
| ISBN | : 3030779610 |
The six-volume set LNCS 12742, 12743, 12744, 12745, 12746, and 12747 constitutes the proceedings of the 21st International Conference on Computational Science, ICCS 2021, held in Krakow, Poland, in June 2021.* The total of 260 full papers and 57 short papers presented in this book set were carefully reviewed and selected from 635 submissions. 48 full and 14 short papers were accepted to the main track from 156 submissions; 212 full and 43 short papers were accepted to the workshops/ thematic tracks from 479 submissions. The papers were organized in topical sections named: Part I: ICCS Main Track Part II: Advances in High-Performance Computational Earth Sciences: Applications and Frameworks; Applications of Computational Methods in Artificial Intelligence and Machine Learning; Artificial Intelligence and High-Performance Computing for Advanced Simulations; Biomedical and Bioinformatics Challenges for Computer Science Part III: Classifier Learning from Difficult Data; Computational Analysis of Complex Social Systems; Computational Collective Intelligence; Computational Health Part IV: Computational Methods for Emerging Problems in (dis-)Information Analysis; Computational Methods in Smart Agriculture; Computational Optimization, Modelling and Simulation; Computational Science in IoT and Smart Systems Part V: Computer Graphics, Image Processing and Artificial Intelligence; Data-Driven Computational Sciences; Machine Learning and Data Assimilation for Dynamical Systems; MeshFree Methods and Radial Basis Functions in Computational Sciences; Multiscale Modelling and Simulation Part VI: Quantum Computing Workshop; Simulations of Flow and Transport: Modeling, Algorithms and Computation; Smart Systems: Bringing Together Computer Vision, Sensor Networks and Machine Learning; Software Engineering for Computational Science; Solving Problems with Uncertainty; Teaching Computational Science; Uncertainty Quantification for Computational Models *The conference was held virtually. Chapter “Deep Learning Driven Self-adaptive hp Finite Element Method” is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
