An iterated greedy heuristic for no-wait flow shops with sequence dependent setup times, learning and forgetting effects

[EN] This paper addresses a sequence dependent setup times no-wait flowshop with learning and forgetting effects to minimize total flowtime. This problem is NP-hard and has never been considered before. A position-based learning and forgetting effects model is constructed. Processing times of operations change with the positions of corresponding jobs in a schedule. Objective increment properties are deduced and based on them three accelerated neighbourhood construction heuristics are presented. Because of the simplicity and excellent performance shown in flowshop scheduling problems, an iterated greedy heuristic is proposed. The proposed iterated greedy algorithm is compared with some existing algorithms for related problems on benchmark instances. Comprehensive computational and statistical tests show that the presented method obtains the best performance among the compared methods. (C) 2018 Elsevier Inc. All rights reserved.This work is supported by the National Natural Science Foundation of China (Nos. 61572127, 61272377), the Collaborative Innovation Center of Wireless Communications Technology and the Key Natural Science Fund for Colleges and Universities in Jiangsu Province (No. 12KJA630001). Ruben Ruiz is partially supported by the Spanish Ministry of Economy and Competitiveness(MINECO), under the project "SCHEYARD - Optimization of Scheduling Problems in Container Yards" with reference DPI2015-65895-R.Li, X.; Yang, Z.; Ruiz García, R.; Chen, T.; Sui, S. (2018). An iterated greedy heuristic for no-wait flow shops with sequence dependent setup times, learning and forgetting effects. Information Sciences. 453:408-425. https://doi.org/10.1016/j.ins.2018.04.038S40842545

Modified FOA Applied to Parameter Extraction of Flux-Gate Core

The accuracy of the magnetic core model is important to the analysis and design of the flux-gate sensor. The Jiles-Atherton model (J-A model) is the mostly used model to describe the hysteresis characteristics of the flux-gate core. But the parameters of J-A model are difficult to identify. In this paper, Fruit Fly Optimization Algorithm (FOA) is proposed to identify the parameters of the J-A model. In order to enhance the performance of the identification, a Modified Fruit Fly Optimization Algorithm (MFOA) is applied to extract the parameters of the flux-gate core. The effectiveness of MFOA is verified through five typical test functions. The influence of variation factor ℎ on the performance of MFOA is discussed. The impact of variation factor ℎ on parameters extraction of hysteresis loop is studied. It is shown that MFOA with appropriate selection of variation factor ℎ will get better performance in the accuracy, stability, and simulation time compared to those of PSO and FOA

Theoretical and Computational Research in Various Scheduling Models

Nine manuscripts were published in this Special Issue on “Theoretical and Computational Research in Various Scheduling Models, 2021” of the MDPI Mathematics journal, covering a wide range of topics connected to the theory and applications of various scheduling models and their extensions/generalizations. These topics include a road network maintenance project, cost reduction of the subcontracted resources, a variant of the relocation problem, a network of activities with generally distributed durations through a Markov chain, idea on how to improve the return loading rate problem by integrating the sub-tour reversal approach with the method of the theory of constraints, an extended solution method for optimizing the bi-objective no-idle permutation flowshop scheduling problem, the burn-in (B/I) procedure, the Pareto-scheduling problem with two competing agents, and three preemptive Pareto-scheduling problems with two competing agents, among others. We hope that the book will be of interest to those working in the area of various scheduling problems and provide a bridge to facilitate the interaction between researchers and practitioners in scheduling questions. Although discrete mathematics is a common method to solve scheduling problems, the further development of this method is limited due to the lack of general principles, which poses a major challenge in this research field

Evolutionary Computation 2020

Intelligent optimization is based on the mechanism of computational intelligence to refine a suitable feature model, design an effective optimization algorithm, and then to obtain an optimal or satisfactory solution to a complex problem. Intelligent algorithms are key tools to ensure global optimization quality, fast optimization efficiency and robust optimization performance. Intelligent optimization algorithms have been studied by many researchers, leading to improvements in the performance of algorithms such as the evolutionary algorithm, whale optimization algorithm, differential evolution algorithm, and particle swarm optimization. Studies in this arena have also resulted in breakthroughs in solving complex problems including the green shop scheduling problem, the severe nonlinear problem in one-dimensional geodesic electromagnetic inversion, error and bug finding problem in software, the 0-1 backpack problem, traveler problem, and logistics distribution center siting problem. The editors are confident that this book can open a new avenue for further improvement and discoveries in the area of intelligent algorithms. The book is a valuable resource for researchers interested in understanding the principles and design of intelligent algorithms

Advances in Manufacturing Technology XXVII: Proceedings of the 11th International Conference on Manufacturing Research (ICMR2013)

ICMR2013 was organised by Cranfield University on the 19-20 September 2013. The conference focuses on any aspects of product development, manufacturing technology, manufacturing systems, information systems and digital technologies. It provides an excellent avenue for researchers to present state-of-the-art multidisciplinary manufacturing research and exchange ideas. In addition to the four keynote speeches from Airbus and Rolls-Royce and three invited presentations, there are 108 papers in these proceedings. These papers are split into 24 technical sessions. The International Conference on Manufacturing Research is a major event for academics and industrialists engaged in manufacturing research. Held annually in the UK since the late 1970s, the conference is renowned as a friendly and inclusive environment that brings together a broad community of researchers who share a common goal; developing and managing the technologies and operations that are key to sustaining the success of manufacturing businesses. For over two decades, ICMR has been the main manufacturing research conference organised in the UK, successfully bringing researchers, academics and industrialists together to share their knowledge and experiences. Initiated a National Conference by the Consortium of UK University Manufacturing Engineering Heads (COMEH), it became an International Conference in 2003. COMEH is an independent body established in 1978. Its main aim is to promote manufacturing engineering education, training and research. To achieve this, the Consortium maintains a close liaison with government bodies concerned with the training and continuing development of professional engineers, while responding to the appropriate consultative and discussion documents and other initiatives. COMEH is represented on the Engineering Professor’s council (EPC) and it organises and supports national manufacturing engineering education research conferences and symposia