An asymptotically optimal online algorithm to minimize the total completion time on two multipurpose machines with unit processing times

AbstractIn the majority of works on online scheduling on multipurpose machines the objective is to minimize the makespan. We, in contrast, consider the objective of minimizing the total completion time. For this purpose, we analyze an online-list scheduling problem of n jobs with unit processing times on a set of two machines working in parallel. Each job belongs to one of two sets of job types. Jobs belonging to the first set can be processed on either of the two machines while jobs belonging to the second set can only be processed on the second machine. We present an online algorithm with a competitive ratio of ρLB+O(1n), where ρLB is a lower bound on the competitive ratio of any online algorithm and is equal to 1+(−α+4α3−α2+2α−12α2+1)2 where α=13+16(116−678)1/3+(58+378)1/33(2)2/3≈1.918. This result implies that our online algorithm is asymptotically optimal

A survey of scheduling problems with setup times or costs

Author name used in this publication: C. T. NgAuthor name used in this publication: T. C. E. Cheng2007-2008 > Academic research: refereed > Publication in refereed journalAccepted ManuscriptPublishe

Heuristics Techniques for Scheduling Problems with Reducing Waiting Time Variance

In real computational world, scheduling is a decision making process. This is nothing but a systematic schedule through which a large numbers of tasks are assigned to the processors. Due to the resource limitation, creation of such schedule is a real challenge. This creates the interest of developing a qualitative scheduler for the processors. These processors are either single or parallel. One of the criteria for improving the efficiency of scheduler is waiting time variance (WTV). Minimizing the WTV of a task is a NP-hard problem. Achieving the quality of service (QoS) in a single or parallel processor by minimizing the WTV is a problem of task scheduling. To enhance the performance of a single or parallel processor, it is required to develop a stable and none overlap scheduler by minimizing WTV. An automated scheduler\u27s performance is always measured by the attributes of QoS. One of the attributes of QoS is ‘Timeliness’. First, this chapter presents the importance of heuristics with five heuristic-based solutions. Then applies these heuristics on 1‖WTV minimization problem and three heuristics with a unique task distribution mechanism on Qm|prec|WTV minimization problem. The experimental result shows the performance of heuristic in the form of graph for consonant problems

Bottleneck Management through Strategic Sequencing in Smart Manufacturing Systems

Nowadays, industries put a significant emphasis on finding the optimum order for carrying out jobs in sequence. This is a crucial element in determining net productivity. Depending on the demand criterion, all production systems, including flexible manufacturing systems, follow a predefined sequence of job-based machine operations. The complexity of the problem increases with increasing machines and jobs to sequence, demanding the use of an appropriate sequencing technique. The major contribution of this work is to modify an existing algorithm with a very unusual machine setup and find the optimal sequence which will really minimize the makespan. This custom machine setup completes all tasks by maintaining precedence and satisfying all other constraints. This thesis concentrates on identifying the most effective technique of sequencing which will be validated in a lab environment and a simulated environment. It illustrates some of the key methods of addressing a circular non permutation flow shop sequencing problem with some additional constraints. Additionally, comparisons among the various heuristics algorithms are presented based on different sequencing criteria. The optimum sequence is provided as an input to a real-life machine set up and a simulated environment for selecting the best performing algorithm which is the basic goal of this research. To achieve this goal, at first, a code using python programming language was generated to find an optimum sequence. By analyzing the results, the makespan is increasing with the number of jobs but additional pallet constraint shows, adding more pallets will help to reduce makespan for both flow shops and job shops. Though the sequence obtained from both algorithms is different, for flow shops the makespan remains same for both cases but in the job shop scenario Nawaz, Enscore and Ham (NEH) algorithms always perform better than Campbell Dudek Smith (CDS) algorithms. For job shops with different combinations the makespan decreases mostly for maximum percentage of easy category jobs combined with equal percentage of medium and complex category jobs

Reinforcement Learning

Brains rule the world, and brain-like computation is increasingly used in computers and electronic devices. Brain-like computation is about processing and interpreting data or directly putting forward and performing actions. Learning is a very important aspect. This book is on reinforcement learning which involves performing actions to achieve a goal. The first 11 chapters of this book describe and extend the scope of reinforcement learning. The remaining 11 chapters show that there is already wide usage in numerous fields. Reinforcement learning can tackle control tasks that are too complex for traditional, hand-designed, non-learning controllers. As learning computers can deal with technical complexities, the tasks of human operators remain to specify goals on increasingly higher levels. This book shows that reinforcement learning is a very dynamic area in terms of theory and applications and it shall stimulate and encourage new research in this field

Introduction to Production: Philosophies, Flow, and Analysis

Production is a fundamental societal and economic activity. Production has to do with the transformation of raw materials into useful objects and includes the knowledge to complete the transformation effectively. Thus, production is a board topic ranging from philosophies about how to approach production such as lean and quick response manufacturing, how to organize production facilities, how to analyze production operations, how to control the flow of materials during production, the devices used to move materials within a facility, and strategies for coordinating multiple production facilities. An integrated introduction to production is presented in a set of learning modules. In significant part, these learning modules are based on over 20 years of interactions with the professional production community in the West Michigan region where Grand Rapids and Holland are the principal cities. This community consists almost exclusively of small and medium size companies engaged primarily in high mix, low volume manufacturing. Students in the Bachelor of Science in Engineering and Master of Science in Engineering programs at Grand Valley State University often work in production for these companies. Thus, interactions are facilitated particularly though master’s degree capstone projects, several of which are referenced in the learning modules. The learning modules are well-grounded in established production concepts. Emphasis is placed on proven procedures such as systematic layout planning, factory physics, various production flow control techniques such as kanban and POLCA, and discrete event simulation. Professional practice is a focus of the learning modules. Material from processional groups such as the Lean Enterprise Institute and the Material Handling Institute (MHI) is integrated. The opportunity to read and discuss professional publications presenting production improvement projects is provided. Students are referred to professional videos and web sites throughout the learning modules. All materials provided are referenced are open access and free of charge. When downloading the main file, it is important to also download and use the Main File Support as it contains supplemental materials.https://scholarworks.gvsu.edu/books/1022/thumbnail.jp

Precision Agriculture Technology for Crop Farming

This book provides a review of precision agriculture technology development, followed by a presentation of the state-of-the-art and future requirements of precision agriculture technology. It presents different styles of precision agriculture technologies suitable for large scale mechanized farming; highly automated community-based mechanized production; and fully mechanized farming practices commonly seen in emerging economic regions. The book emphasizes the introduction of core technical features of sensing, data processing and interpretation technologies, crop modeling and production control theory, intelligent machinery and field robots for precision agriculture production