Download or read book Reactive Parallel Machine Scheduling Using Hybrid intelligence to Minimize Weighted Tardiness Makespan and Cost of Rescheduling written by Supphasak Phonganant and published by . This book was released on 2004 with total page 540 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book A Robust Reactive Scheduling System with Application to Parallel Machine Scheduling written by Jean-Paul M. Arnaout and published by . This book was released on 2006 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this turbulent world, scheduling role has become crucial in most manufacturing production, and service systems. It allows the allocation of limited resources to activities with the objective of optimizing one performance measure or more. Resources may be machines in a factory, operating rooms in a hospital, or employees in a company, while activities can be jobs in a manufacturing plant, surgeries in a hospital, or paper work in a company. The goal of each schedule is to optimize some performance measures, which could be the minimization of the schedule makespan, the jobs' completion times, jobs' earliness and tardiness, among others.

Download or read book Intelligent Scheduling Systems written by Donald E. Brown and published by Springer. This book was released on 1995 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: Scheduling is a resource allocation problem which exists in virtually every type of organization. Scheduling problems have produced roughly 40 years of research primarily within the OR community. This community has traditionally emphasized mathematical modeling techniques which seek exact solutions to well formulated optimization problems. While this approach produced important results, many contemporary scheduling problems are particularly difficult. Hence, over the last ten years operations researchers interested in scheduling have turned increasingly to more computer intensive and heuristic approaches. At roughly the same time, researchers in AI began to focus their methods on industrial and management science applications. The result of this confluence of fields has been a period of remarkable growth and excitement in scheduling research. Intelligent Scheduling Systems captures the results of a new wave of research at the forefront of scheduling research, of interest to researchers and practitioners alike. Presented are an array of the latest contemporary tools -- math modeling to tabu search to genetic algorithms -- that can assist in operational scheduling and solve difficult scheduling problems. The book presents the most recent research results from both operations research (OR) and artificial intelligence (AI) focusing their efforts on real scheduling problems.

Download or read book Heuristic Approaches to Minimize the Makespan and Tardiness written by and published by . This book was released on 2015 with total page 138 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Model and Algorithms for Scheduling Uniform Parallel Machines written by P Senthilkumar and published by Independently Published. This book was released on 2024-01-18 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Production scheduling helps businesses become more productive and efficiently satisfy consumer needs. Because it falls within the combinatorial category, scheduling work on uniform parallel computers to minimize the makespan measure is a difficult problem under single machine scheduling. The goal of this essay is to show how to design an effective algorithm for this particular situation. The introduction chapter of this text covers single machine scheduling with a single machine, single machine scheduling with parallel machines, and research gap of unform parallel machine scheduling. The goals of the challenge, the assumptions behind the scheduling of uniform parallel machines, and the plan for developing the algorithms are all presented in Chapter 2, which describes the problem. A model and an example of the model utilizing a small size problem are provided in Chapter 3 on the mathematical model for uniform parallel machines scheduling to minimize makespan. The simulated annealing algorithm to minimize makespan in the single machine scheduling problem with uniform parallel machines is presented in Chapter 4. It includes an overview of the algorithm, its skeleton, three newly developed simulated annealing algorithms, and a comparison of them to determine which is the best. The development of a GA-based strategy to reduce the uniform parallel machine scheduling makespan is presented in Chapter 5. This covers the basic structure of the genetic algorithm, factors that impact the GA algorithm, techniques for assigning tasks to machines, and crossover strategies. Additionally, it entails the creation of four GA-based heuristics to reduce makespan and a comparison of them to determine which GA-based heuristic is optimum for scheduling jobs on uniform parallel computers. In order to determine which is optimal, the best GA-based heuristic and the best simulated annealing technique are compared in Chapter 6 to minimize the makespan of scheduling jobs on uniform parallel computers. Appendix 1 for replication 1 and Appendix 2 for replication 2 contain the data needed to test the heuristics in Chapter 4, Chater 5, and Chapter 6. The author expresses gratitude to all of his university colleagues and academicians for their support in releasing this work. The writing style of this text is simple to read. P. Senthilkumar, B.E., M.E., Ph.D

Download or read book Minimize the Makespan in Resource constrained Parallel Machine Scheduling written by and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Constrained Scheduling to Minimize the Makespan on Two Parallel Machines with Job Classes and Setup Times written by J. Ahmadi and published by . This book was released on 1987 with total page 11 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Scheduling to Reduce Total Weighted Tardiness on Parallel Machines with Ready Times written by Amit Gadkari and published by . This book was released on 2003 with total page 194 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Unrelated Parallel Machine Scheduling with Sequence dependent Setup Times and Machine Eligibility Restrictions for Minimizing the Makespan written by Ameer Hassan Salem and published by . This book was released on 1999 with total page 420 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Parallel Branch and Price Algorithms for the Single Machine Total Weighted Tardiness Scheduling Problem with Sequence Dependent Setup Times written by Philipp Speckenmeyer and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Scheduling problems occur in a broad range of real-world application fields and have attracted a huge set of research articles. However, there is only little research on exact algorithms for scheduling problems, many of which are NP-hard in the strong sense. We investigate the problem on a single machine with a total weighted tardiness objective function and sequence-dependent setup times. First, we adopt a serial branch-and-bound algorithm from the literature and present a modified branching strategy and a primal heuristic. Second, we use the potential of parallel computing architectures by presenting two parallel versions of the branch-and-price algorithm. Third, we conduct extensive computational experiments to show that our parallelization approaches provide substantial parallel speedups on well-known benchmark instances from the literature. We further observe that the parallel speedups achieved by our parallel algorithms are very robust among all tested instances.

Download or read book Weighted tardiness Scheduling on Parallel Machines with Proportional Weights written by Cornell University. Department of Operations Research and Industrial Engineering and published by . This book was released on 1988 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Hybrid Job Shop and Parallel Machine Scheduling Problems Minimization of Total Tardiness Criterion written by Frederic Dugardin and published by . This book was released on 2007 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: In this chapter we have presented different results useful for scheduling tasks trough a hybrid job shop system. At first we have dealt with the parallel machine job shop since its structure is near from the multi processors stages of a Hybrid Job Shop. Then we have presented some theoretical results and their application in the industry. We have developed some examples of modeling industrial lines for a genetic application or an ant colony system application. After this step of modeling, the result show real improvements of the minimization of the total tardiness in an industrial case. These results could be very usefull in the semiconductor manufacturing or in the paper industries since the Hybrid Job Shop structure seem to be common in this area.

Download or read book Identical Parallel Machine Scheduling Problems written by Alexander Lawrinenko and published by . This book was released on 2017 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The work is about fundamental parallel machine scheduling problems which occur in manufacturing systems where a set of jobs with individual processing times has to be assigned to a set of machines with respect to several workload objective functions like makespan minimization, machine covering or workload balancing. In the first chapter of the work an up-to-date survey on the most relevant literature for these problems is given, since the last review dealing with these problems has been published almost 20 years ago. We also give an insight into the relevant literature contributed by the Artificial Intelligence community, where the problem is known as number partitioning. The core of the work is a universally valid characterization of optimal makespan and machine-covering solutions where schedules are evaluated independently from the processing times of the jobs. Based on these novel structural insights we derive several strong dominance criteria. Implemented in a branch-and-bound algorithm these criteria have proved to be effective in limiting the solution space, particularly in the case of small ratios of the number of jobs to the number of machines. Further, we provide a counter-example to a central result by Ho et al. (2009) who proved that a schedule which minimizes the normalized sum of squared workload deviations is necessarily a makespan-optimal one. We explain why their proof is incorrect and present computational results revealing the difference between workload balancing and makespan minimization. The last chapter of the work is about the minimum cardinality bin covering problem which is a dual problem of machine-covering with respect to bounding techniques. We discuss reduction criteria, derive several lower bound arguments and propose construction heuristics as well as a subset sum-based improvement algorithm. Moreover, we present a tailored branch-and-bound method which is able to solve instances with up to 20 bins.

Download or read book Hybrid Job Shop and Parallel Machine Scheduling Problems written by Frederic Dugardin and published by . This book was released on 2007 with total page 1 pages. Available in PDF, EPUB and Kindle. Book excerpt: Hybrid Job Shop and Parallel Machine Scheduling Problems: Minimization of Total Tardiness Criterion.

Download or read book Efficient Algorithms for Unrelated Parallel Machine Scheduling Considering Time of Use Pricing and Demand Changes written by Brady Collea and published by . This book was released on 2020 with total page 38 pages. Available in PDF, EPUB and Kindle. Book excerpt: "There is an ever-increasing focus on sustainability and energy consumption worldwide. Manufacturing is one of the major areas where energy reduction is not only environmentally beneficial, but also incredibly financially beneficial. These industrial consumers pay for their electricity according to prices that fluctuate throughout the day. These price fluctuations are in place to shift consumption away from “peak” times, when electricity is in the highest demand. In addition to this consumption cost, industrial consumers are charged according to their highest level of demand in a given window of time in the form of demand charges. This paper presents multiple solution methods to solve a parallel machine shop scheduling problem to minimize the total energy cost of the production schedule under Time of Use (TOU) and demand charge pricing. The greedy heuristic and genetic algorithm developed are designed to provide efficient solutions to this problem. The results of these methods are compared to a previously developed integer program (IP) solved using CPLEX with respect to the quality of the solution and the computational time required to solve it. Findings of these tests show that the greedy heuristic handles the test problems with only a small optimality gap to the genetic algorithm and optimal IP solution. The largest test problems could not be solved by the genetic algorithm in the provided time period due to difficulty generating an initial solution population. However, when successful the genetic algorithm performed comparably to the CPLEX solver in terms solution quality yet provided faster solve times."--Abstract.

Download or read book Scheduling Parallel and Single Batch Machines to Minimize Total Weighted Tardiness written by Amit Devpura and published by . This book was released on 2003 with total page 394 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Parallel Scheduling in the Cloud Systems written by Mohammed Albarra Hassan Abdeljabbar Hassan and published by . This book was released on 2016 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Cloud Computing appears as a strong concept to share costs and resources related to the use of end-users. As a consequence, several related models exist and are widely used (IaaS, PaaS, SaaS. . .). In this context, our research focused on the design of new methodologies and algorithms to optimize performances using the scheduling and combinatorial theories. We were interested in the performance optimization of a Cloud Computing environment where the resources are heterogeneous (operators, machines, processors...) but limited. Several scheduling problems have been addressed in this thesis. Our objective was to build advanced algorithms by taking into account all these additional specificities of such an environment and by ensuring the performance of solutions. Generally, the scheduling function consists in organizing activities in a specific system imposing some rules to respect. The scheduling problems are essential in the management of projects, but also for a wide set of real systems (telecommunication, computer science, transportation, production...). More generally, solving a scheduling problem can be reduced to the organization and the synchronization of a set of activities (jobs or tasks) by exploiting the available capacities (resources). This execution has to respect different technical rules (constraints) and to provide the maximum of effectiveness (according to a set of criteria). Most of these problems belong to the NP-Hard problems class for which the majority of computer scientists do not expect the existence of a polynomial exact algorithm unless P=NP. Thus, the study of these problems is particularly interesting at the scientific level in addition to their high practical relevance. In particular, we aimed to build new efficient combinatorial methods for solving parallel-machine scheduling problems where resources have different speeds and tasks are linked by precedence constraints. In our work we studied two methodological approaches to solve the problem under the consideration : exact and meta-heuristic methods. We studied three scheduling problems, where the problem of task scheduling in cloud environment can be generalized as unrelated parallel machines, and open shop scheduling problem with different constraints. For solving the problem of unrelated parallel machines with precedence constraints, we proposed a novel genetic-based task scheduling algorithms in order to minimize maximum completion time (makespan). These algorithms combined the genetic algorithm approach with different techniques and batching rules such as list scheduling (LS) and earliest completion time (ECT). We reviewed, evaluated and compared the proposed algorithms against one of the well-known genetic algorithms available in the literature, which has been proposed for the task scheduling problem on heterogeneous computing systems. Moreover, this comparison has been extended to an existing greedy search method, and to an exact formulation based on basic integer linear programming. The proposed genetic algorithms show a good performance dominating the evaluated methods in terms of problems' sizes and time complexity for large benchmark sets of instances. We also extended three existing mathematical formulations to derive an exact solution for this problem. These mathematical formulations were validated and compared to each other by extensive computational experiments. Moreover, we proposed an integer linear programming formulations for solving unrelated parallel machine scheduling with precedence/disjunctive constraints, this model based on the intervaland m-clique free graphs with an exponential number of constraints. We developed a Branch-and-Cut algorithm, where the separation problems are based on graph algorithms. [...].