Genetic And Hybrid Algorithm Approaches To Flow Shop Scheduling
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Genetic and Hybrid Algorithm Approaches to Flow Shop Scheduling
Master's Thesis from the year 2016 in the subject Engineering - Mechanical Engineering, grade: 5, Tallinn University (Department of Mechanical and Industrial Engineering - Chair of Production Engineering), course: Industrial Engineering and Management, language: English, abstract: Flow shop scheduling encompasses allocating a number of jobs in a previously ordered set of machines so that a determined objective function such as makespan is either minimized or maximized. Despite the apparent simplicity of the problem, there is no known non enumerative polynomial time algorithm capable of solving this type of optimization, except for in those cases that can be treated by the Johnson's algorithm or proportional flow shops. Indeed, understanding flow shop scheduling is proven to be mathematically intractable in the vast majority of cases. Considering this nature of flow shop scheduling, the primary objective of this dissertation was to develop algorithms capable of mitigating the computational burden associated with the problem. In this realm, three solutions were proposed. The first approach refers to a genetic algorithm that employed discrete event simulation and customized genetic operators as a means to eliminate the evaluation of unfeasible solutions and incorporate problem-specific knowledge. The second and third proposed solutions consisting of hybrid methods that have improved the aforementioned framework by including local search. Computational experiments that used the Kaplan-Meier estimator to evaluate the performance of the algorithms demonstrated that the hybrid versions were able, at a worst-case scenario, to achieve exact results by investigating no more than six percent of the total number of feasible schedules. Granted that the evidence gathered so far suggests that the hybrid versions of the proposed algorithms managed to substantially reduce the onus associated with the factorial complexity of the flow shop scheduling problem, expanding the framework
Proceedings of the Ninth International Conference on Management Science and Engineering Management
This is the Proceedings of the Ninth International Conference on Management Science and Engineering Management (ICMSEM) held from July 21-23, 2015 at Karlsruhe, Germany. The goals of the conference are to foster international research collaborations in Management Science and Engineering Management as well as to provide a forum to present current findings. These proceedings cover various areas in management science and engineering management. It focuses on the identification of management science problems in engineering and innovatively using management theory and methods to solve engineering problems effectively. It also establishes a new management theory and methods based on experience of new management issues in engineering. Readers interested in the fields of management science and engineering management will benefit from the latest cutting-edge innovations and research advances presented in these proceedings and will find new ideas and research directions. A total number of 132 papers from 15 countries are selected for the proceedings by the conference scientific committee through rigorous referee review. The selected papers in the first volume are focused on Intelligent System and Management Science covering areas of Intelligent Systems, Logistics Engineering, Information Technology and Risk Management. The selected papers in the second volume are focused on Computing and Engineering Management covering areas of Computing Methodology, Project Management, Industrial Engineering and Decision Making Systems.
Proceedings of the Eighth International Conference on Management Science and Engineering Management
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