Reputation-guided Evolutionary Scheduling Algorithm for Independent Tasks in inter-Clouds Environments

Self-adaptation provides software with flexibility to different behaviours (configurations) it incorporates and the (semi-) autonomous ability to switch between these behaviours in response to changes. To empower clouds with the ability to capture and respond to quality feedback provided by users at runtime, we propose a reputation guided genetic scheduling algorithm for independent tasks. Current resource management services consider evolutionary strategies to improve the performance on resource allocation procedures or tasks scheduling algorithms, but they fail to consider the user as part of the scheduling process. Evolutionary computing offers different methods to find a near-optimal solution. In this paper we extended previous work with new optimisation heuristics for the problem of scheduling. We show how reputation is considered as an optimisation metric, and analyse how our metrics can be considered as upper bounds for others in the optimisation algorithm. By experimental comparison, we show our techniques can lead to optimised results.Peer Reviewe

A hybrid simulated annealing for scheduling in dual-resource cellular manufacturing system considering worker movement

This paper presents a novel linear mathematical model for integrated cell formation and task scheduling in the cellular manufacturing system (CMS). It is suitable for the dual-resource constrained setting, such as garment process, component assembly, and electronics manufacturing. The model can handle the manufacturing project composing of some tasks with precedence constraints. It provides a method to assign the multi-skilled workers to appropriate machines. The workers are allowed to move among the machines such that the processing time of tasks might be reduced. A hybrid simulated annealing (HSA) is proposed to minimize the makespan of manufacturing project in the CMS. The approach combines the priority rule based heuristic algorithm (PRBHA) and revised forward recursion algorithm (RFRA) with conventional simulated annealing (SA). The result of extensive numerical experiments shows that the proposed HSA outperforms the conventional SA accurately and efficiently

Linking Scheduling Criteria to Shop Floor Performance in Permutation Flowshops

The goal of manufacturing scheduling is to allocate a set of jobs to the machines in the shop so these jobs are processed according to a given criterion (or set of criteria). Such criteria are based on properties of the jobs to be scheduled (e.g., their completion times, due dates); so it is not clear how these (short-term) criteria impact on (long-term) shop floor performance measures. In this paper, we analyse the connection between the usual scheduling criteria employed as objectives in flowshop scheduling (e.g., makespan or idle time), and customary shop floor performance measures (e.g., work-in-process and throughput). Two of these linkages can be theoretically predicted (i.e., makespan and throughput as well as completion time and average cycle time), and the other such relationships should be discovered on a numerical/empirical basis. In order to do so, we set up an experimental analysis consisting in finding optimal (or good) schedules under several scheduling criteria, and then computing how these schedules perform in terms of the different shop floor performance measures for several instance sizes and for different structures of processing times. Results indicate that makespan only performs well with respect to throughput, and that one formulation of idle times obtains nearly as good results as makespan, while outperforming it in terms of average cycle time and work in process. Similarly, minimisation of completion time seems to be quite balanced in terms of shop floor performance, although it does not aim exactly at work-in-process minimisation, as some literature suggests. Finally, the experiments show that some of the existing scheduling criteria are poorly related to the shop floor performance measures under consideration. These results may help to better understand the impact of scheduling on flowshop performance, so scheduling research may be more geared towards shop floor performance, which is sometimes suggested as a cause for the lack of applicability of some scheduling models in manufacturing

A Simulation Analysis of Constrained Rate and Line Assembly Processes

Simulation presents a way to analyze the performance of a system with zone capacity constraints, operator constraints, and precedence constraints in an assembly line using takt analysis. A small-scale model of an aircraft assembly line is built in Simio and precedence constraints are modified in independent simulations. The primary performance metric is traveled work, for which a definition is given. A method of calculating traveled work is presented, as well as an interpretation that states the effect on throughput. These results show that, ceteris paribus, traveled work increases flowtime, which decreases throughput. Modifications to the system are suggested that can reduce traveled work

The impact of tool allocation policies on selected performance measures for flexible manufacturing systems

The allocation of cutting tools to machines is an important concern for managers of flexible manufacturing systems. This research was conducted to study the impact of four tool allocation strategies on five performance measures, contingent upon three part-type selection rules. In addition, the average tool inventory and tool consumption rates were evaluated for each tool policy and selection rule. The four tool allocation policies consisted of the bulk exchange, tool migration, tool sharing, and resident tooling. The five performance measures consisted of the average flowtime of parts, the average machine utilization, the robot utilization, the percentage of parts late, and the mean lateness. Simulation was used to study the impact of the tooling strategies on the performance measures. Analysis of variance procedures, graphical comparison charts and Bonferroni multiple comparison tests were used to analyze the data. The results show that clustering tools, based on group technology, is the preferred method for allocating cutting tools to machines. Tool sharing was the preferred tool allocation strategy. Also, tool allocation policies that require tool changes, after a part\u27s machining cycle, increase part flowtimes because parts are delayed in the system due to the increase in tool changing activities. In addition, tool allocation strategies based on tool clustering methods reduced the utilization of resources. The results of this study show that bulk exchange produced lower tool consumption rates per production period during the early periods of production. During the middle and later production periods, tool sharing produced lower tool consumption rates. This study concluded that grouping tools based on the commonality of tool usage results in a lower average inventory per production period. Furthermore, this study showed that the uneven distribution of part-types to machine, under tool clustering methods, affected the average mean lateness of part-type. Moreover, no part-type selection rule outperformed another on ail performance measures. The earliest due date rule produced the lowest mean lateness values for all tool policies. Tool policies that produce low mean flowtimes may not produce low mean lateness values. Managerial implications are discussed with respect to the findings from this study. Further research is needed to evaluate flexible manufacturing systems, which include using different part-type selection rules, machine failures, and hybrids of tool allocation strategies

An application of an ethernet based protocol for communication and control in automated manufacturing

The exchange of information in the industrial environment is essential in order to achieve complete integration and control of manufacturing processes. At present the majority of devices present in the shop floor environment are still used as stand alone machines. They do not take advantage of the possibilities offered by a communication link to improve the manufacturing process. The subject of this research has been centered on the development of a simple, flexible and inexpensive support system for communication and control of manufacturing processes. As a result, a system with these features has been proposed and implemented on a simulated workcell. The area footwear manufacturing was chosen for modelling the workcell. The components of the manufacturing support system were developed using an object oriented approach which allowed modularity and software reuse. In order to achieve communication between the components, a communication protocol was developed following the process defined in the rapid protocol implementation framework. Ethernet was selected for implementing the lower levels of the protocol. Java, a new object oriented programming language used for the implementation of the system, showed that it could became a promising language for the implementation of manufacturing applications. In particular the platform independence feature of the language allows the immediate porting of applications to systems with different features. The manufacturing cell simulation had shown that the times associated with the manufacturing support system operations are compatible for its use in applications where the response times are in the order of one second

Robustness and stability measures for scheduling: Single-machine environment

This paper addresses the issue of finding robust and stable schedules with respect to random disruptions. Specifically, two surrogate measures for robustness and stability are developed. The proposed surrogate measures, which consider both busy and repair time distributions, are embedded in a tabu-search-based scheduling algorithm, which generates schedules in a single-machine environment subject to machine breakdowns. The performance of the proposed scheduling algorithm and the surrogate measures are tested under a wide range of experimental conditions. The results indicate that one of the proposed surrogate measures performs better than existing methods for the total tardiness and total flowtime criteria in a periodic scheduling environment. A comprehensive bibliography is also presented

Coordination of Multirobot Systems Under Temporal Constraints

Multirobot systems have great potential to change our lives by increasing efficiency or decreasing costs in many applications, ranging from warehouse logistics to construction. They can also replace humans in dangerous scenarios, for example in a nuclear disaster cleanup mission. However, teleoperating robots in these scenarios would severely limit their capabilities due to communication and reaction delays. Furthermore, ensuring that the overall behavior of the system is safe and correct for a large number of robots is challenging without a principled solution approach. Ideally, multirobot systems should be able to plan and execute autonomously. Moreover, these systems should be robust to certain external factors, such as failing robots and synchronization errors and be able to scale to large numbers, as the effectiveness of particular tasks might depend directly on these criteria. This thesis introduces methods to achieve safe and correct autonomous behavior for multirobot systems. Firstly, we introduce a novel logic family, called counting logics, to describe the high-level behavior of multirobot systems. Counting logics capture constraints that arise naturally in many applications where the identity of the robot is not important for the task to be completed. We further introduce a notion of robust satisfaction to analyze the effects of synchronization errors on the overall behavior and provide complexity analysis for a fragment of this logic. Secondly, we propose an optimization-based algorithm to generate a collection of robot paths to satisfy the specifications given in counting logics. We assume that the robots are perfectly synchronized and use a mixed-integer linear programming formulation to take advantage of the recent advances in this field. We show that this approach is complete under the perfect synchronization assumption. Furthermore, we propose alternative encodings that render more efficient solutions under certain conditions. We also provide numerical results that showcase the scalability of our approach, showing that it scales to hundreds of robots. Thirdly, we relax the perfect synchronization assumption and show how to generate paths that are robust to bounded synchronization errors, without requiring run-time communication. However, the complexity of such an approach is shown to depend on the error bound, which might be limiting. To overcome this issue, we propose a hierarchical method whose complexity does not depend on this bound. We show that, under mild conditions, solutions generated by the hierarchical method can be executed safely, even if such a bound is not known. Finally, we propose a distributed algorithm to execute multirobot paths while avoiding collisions and deadlocks that might occur due to synchronization errors. We recast this problem as a conflict resolution problem and characterize conditions under which existing solutions to the well-known drinking philosophers problem can be used to design control policies that prevents collisions and deadlocks. We further provide improvements to this naive approach to increase the amount of concurrency in the system. We demonstrate the effectiveness of our approach by comparing it to the naive approach and to the state-of-the-art.PHDElectrical Engineering: SystemsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/162921/1/ysahin_1.pd

Serial-batch scheduling – the special case of laser-cutting machines

The dissertation deals with a problem in the field of short-term production planning, namely the scheduling of laser-cutting machines. The object of decision is the grouping of production orders (batching) and the sequencing of these order groups on one or more machines (scheduling). This problem is also known in the literature as "batch scheduling problem" and belongs to the class of combinatorial optimization problems due to the interdependencies between the batching and the scheduling decisions. The concepts and methods used are mainly from production planning, operations research and machine learning