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Every major industry except construction uses logistics to improve its bottom line… Poor logistics is costing the construction industry at least £3 billion a year according to a report – ‘Improving Construction Logistics’ – published by the Strategic Forum for Construction.  Additional costs arise as a result of operatives waiting for materials, and skilled craftsmen being used for unskilled jobs. Inadequate management of logistics also has an adverse effect on quality, causes delays to projects, and adds to the health and safety risks on site.  This practical book highlights the benefits of good logistics as well as the use of consolidation centres on projects. It shows how reduction in transport movements, less money tied up in stock, less waste, and the more efficient use of skilled craftsmen will reduce the cost of projects, reduce construction time, improve quality, reduce risks to health and safety, improve environmental performance and generally improve the image of the industry. The authors offer practical ways of achieving these benefits through integrated project teams and supply chains and the increased adoption of information technology including electronic communications, bar coding, and electronic tagging for tracing products. They also show how specific roles for each part of the industry can help to improve logistics. • Practical, clear and accessible • First book to address logistics in construction • Written by the industry-recognized logistics experts • Tackles issues of key concern: efficient use of labour; sustainability; waste and supply chain management

A unified, systematic approach to applying mixed integer programming solutions to integrated scheduling in customer-driven supply chains Supply chain management is a rapidly developing field, and the recent improvements in modeling, preprocessing, solution algorithms, and mixed integer programming (MIP) software have made it possible to solve large-scale MIP models of scheduling problems, especially integrated scheduling in supply chains. Featuring a unified and systematic presentation, Scheduling in Supply Chains Using Mixed Integer Programming provides state-of-the-art MIP modeling and solutions approaches, equipping readers with the knowledge and tools to model and solve real-world supply chain scheduling problems in make-to-order manufacturing. Drawing upon the author's own research, the book explores MIP approaches and examples-which are modeled on actual supply chain scheduling problems in high-tech industries-in three comprehensive sections: Short-Term Scheduling in Supply Chains presents various MIP models and provides heuristic algorithms for scheduling flexible flow shops and surface mount technology lines, balancing and scheduling of Flexible Assembly Lines, and loading and scheduling of Flexible Assembly Systems Medium-Term Scheduling in Supply Chains outlines MIP models and MIP-based heuristic algorithms for supplier selection and order allocation, customer order acceptance and due date setting, material supply scheduling, and medium-term scheduling and rescheduling of customer orders in a make-to-order discrete manufacturing environment Coordinated Scheduling in Supply Chains explores coordinated scheduling of manufacturing and supply of parts as well as the assembly of products in supply chains with a single producer and single or multiple suppliers; MIP models for a single- or multiple-objective decision making are also provided Two main decision-making approaches are discussed and compared throughout. The integrated (simultaneous) approach, in which all required decisions are made simultaneously using complex, monolithic MIP models; and the hierarchical (sequential) approach, in which the required decisions are made successively using hierarchies of simpler and smaller-sized MIP models. Throughout the book, the author provides insight on the presented modeling tools using AMPL® modeling language and CPLEX solver. Scheduling in Supply Chains Using Mixed Integer Programming is a comprehensive resource for practitioners and researchers working in supply chain planning, scheduling, and management. The book is also appropriate for graduate- and PhD-level courses on supply chains for students majoring in management science, industrial engineering, operations research, applied mathematics, and computer science.

This book describes the potentialities of metaheuristics for solving production scheduling problems and the relationship between these two fields.For the past several years, there has been an increasing interest in using metaheuristic methods to solve scheduling problems.

This is your practical guide to setting up a working environment and using Oracle Scheduler. Packed with simple examples and clear explanations, real-life scenarios are discussed to make you comfortable in implementing them in your own system. This book is intended for Administrators and Developers who currently use tools like cron, DBMS_JOB, and the task manager, but who now want more control or who have a need to scale up to tools that can handle the network. Complex tasks can be built that easily control business process and enable the completion of important tasks in limited time. The reader is expected to have some experience of Oracle Database Management, and a working knowledge of SQL and PL/SQL.

In \"Mastering Oracle Scheduler in Oracle 11g Databases\", you will unlock the full potential of Oracle Scheduler (DBMS_SCHEDULER), a powerful tool for automating and managing database tasks. This book provides a comprehensive guide with practical examples to help you optimize database performance and automate your workflows.What this Book will help me doUnderstand how to create and manage job schedules using Oracle Scheduler, catering to both simple and complex automation needs.Learn to integrate platform-independent execution of jobs into your Oracle database management strategies.Gain practical insights into debugging, monitoring, and optimizing jobs for enhanced database performance.Explore event-driven scheduling to develop intelligent automation solutions for your business processes.Master resource management techniques to handle large-scale job scheduling effectively.Author(s)Ronald Rood is a seasoned database administrator and developer specializing in Oracle technologies. With extensive experience in database performance tuning and automation, Ronald shares practical insights and expert guidance in his writing. His passion for teaching complex concepts in an engaging manner makes his books valuable resources for professionals.Who is it for?This book is ideal for Oracle Database administrators and developers who want to advance their automation and scheduler management skills. With a basic understanding of Oracle Database Management and proficiency in SQL and PL/SQL, readers aim to optimize jobs and improve overall performance. It's perfect for those transitioning from tools like cron or DBMS_JOB for more robust scheduling capabilities.

This book describes the potentialities of metaheuristics for solving production scheduling problems and the relationship between these two fields. For the past several years, there has been an increasing interest in using metaheuristic methods to solve scheduling problems. The main reasons for this are that such problems are generally hard to solve to optimality, as well as the fact that metaheuristics provide very good solutions in a reasonable time. The first part of the book presents eight applications of metaheuristics for solving various mono-objective scheduling problems. The second part is itself split into two, the first section being devoted to five multi-objective problems to which metaheuristics are adapted, while the second tackles various transportation problems related to the organization of production systems. Many real-world applications are presented by the authors, making this an invaluable resource for researchers and students in engineering, economics, mathematics and computer science. Contents 1. An Estimation of Distribution Algorithm for Solving Flow Shop Scheduling Problems with Sequence-dependent Family Setup Times, Mansour Eddaly, Bassem Jarboui, Radhouan Bouabda, Patrick Siarry and Abdelwaheb Rebaï. 2. Genetic Algorithms for Solving Flexible Job Shop Scheduling Problems, Imed Kacem. 3. A Hybrid GRASP-Differential Evolution Algorithm for Solving Flow Shop Scheduling Problems with No-Wait Constraints, Hanen Akrout, Bassem Jarboui, Patrick Siarry and Abdelwaheb Rebaï. 4. A Comparison of Local Search Metaheuristics for a Hierarchical Flow Shop Optimization Problem with Time Lags, Emna Dhouib, Jacques Teghem, Daniel Tuyttens and Taïcir Loukil. 5. Neutrality in Flow Shop Scheduling Problems: Landscape Structure and Local Search, Marie-Eléonore Marmion. 6. Evolutionary Metaheuristic Based on Genetic Algorithm: Application to

\"I believe that constructors ignore this book at their peril. These techniques will soon be core to every construction business. The only question for industry decision-makers is to decide whether they want to get ahead of the curve by changing now, or wait until a streamlined and competitive industry forces them to adapt just to remain viable. As a client, I know what I'd recommend.\" -Peter Rogers, CBE, Chairman of the Green Building Council Poor logistics is costing the construction industry at least £3 billion a year. Additional costs arise as a result of operatives waiting for materials, and skilled craftsmen being used for unskilled jobs. Inadequate management of logistics also has an adverse effect on quality, causes delays to projects, and adds to the health and safety risks on site. Every major industry except construction uses logistics to improve its bottom line. This practical, clear and accessible book highlights the benefits of good logistics in construction as well explaining the use of consolidation centres for projects. It shows how reduction in transport movements, less money tied up in stock, less waste, and the more efficient use of skilled craftsmen will reduce the cost of projects, reduce construction time, improve quality, reduce risks to health and safety, improve environmental performance and generally improve the image of the industry. The authors - industry-recognized logistics experts - offer tried-and-tested ways of achieving these benefits through integrated project teams and supply chains, and the increased adoption of information technology. Managing Construction Logistics includes a wide range of lively and detailed case studies - from Terminal 5 to the Tate Gallery - showing how good logistics tackles the 'hot potato' issues within the construction industry: efficient use of labour; sustainability; waste

We obtain an optimal operation policy for a general n -server (channel, machine) stand-by system involving preventive maintenance and operating in real time . We show that such a policy is achieved by successive total use of each server capacity, and does not depend on the arrival pattern of processed data and task duration. We show also that this policy is optimal for any finite, initial period of time, and not only in the sense of long-run availability. The analysis is performed in two stages: a worst-case analysis is performed, and then, a general case is treated. Such a consecutive approach also seems to be useful in the analysis of more complicated systems. Rigorous mathematical proofs are provided. Actual and possible applications of results to military and production control systems are discussed.

Cloud computing is an emerging distributed system that provides flexible and dynamically scalable computing resources for use at low cost. Task scheduling in cloud computing environment is one of the main problems that need to be addressed in order to improve system performance and increase cloud consumer satisfaction. Although there are many task scheduling algorithms, existing approaches mainly focus on minimizing the total completion time while ignoring workload balancing. Moreover, managing the quality of service (QoS) of the existing approaches still needs to be improved. In this paper, we propose a novel algorithm named MGGS (modified genetic algorithm (GA) combined with greedy strategy). The proposed algorithm leverages the modified GA algorithm combined with greedy strategy to optimize task scheduling process. Different from existing algorithms, MGGS can find an optimal solution using fewer number of iterations. To evaluate the performance of MGGS, we compared the performance of the proposed algorithm with several existing algorithms based on the total completion time, average response time, and QoS parameters. The results obtained from the experiments show that MGGS performs well as compared to other task scheduling algorithms.