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Minimizing the makespan in a flow shop environment under minimum and maximum time-lag constraints

COMPUTERS & INDUSTRIAL ENGINEERING 2019年 136卷 614-634页

作者： Samarghandi, Hamed Univ Saskatchewan Edwards Sch Business Dept Finance & Management Sci Saskatoon SK S7N 5A7 Canada

This paper considers the flow shop scheduling problem with minimum and maximum time-lag requirements. According to the time-lag constraints, the starting time of each operation of a job must be within a specified time-window after the completion of its previous operation. The considered objective function is makespan and the problem is strongly NP-hard. In this article, a mixed integer linear programming (MILP) and two constraint programming (CP) models are proposed for the problem. To deal with the larger instances of this problems, it is decomposed into a sequencing and a timetabling sub-problem. A tabu search (TS) is developed to handle the sequencing sub-problem. Furthermore, an exact method based on the developed MILP as well as a greedy algorithm are proposed to deal with the timetabling sub-problem. A large number of test cases with different time-lag settings are solved to assess the performance of the proposed algorithm. Computational results confirm that the proposed TS is efficient and competitive. Moreover, the greedy timetabling method proves to be significantly faster than the exact method without sacrificing the solution quality.

关键词： Scheduling Flow shop Time-lags Mixed integer programming Constraint programming Tabu search Timetabling greedy algorithm

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Rationalization of Decision-Making Process in Selection of Suppliers with Use of the greedy and Tabu Search algorithms 2nd

Rationalization of Decision-Making Process in Selection of S...

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2nd International Conference on Intelligent Systems in Production Engineering and Maintenance (ISPEM)

作者： Kochanska, Joanna Musial, Kamil Burduk, Anna Wroclaw Univ Sci & Technol Fac Mech Engn Wybrzeze Wyspianskiego 27 PL-50370 Wroclaw Poland

ISBN: (纸本)9783319974903;9783319974897

The paper raises the issue of evaluation and selection of suppliers in a large manufacturing company. Till now, the decision-making process in the company was based on the human factor. The presented work was aimed at developing new suppliers selection system. That would make it possible to minimize costs of ordered materials. Solving the problem of optimization is offered by Tabu Search and greedy algorithms. The tuning process of algorithms and the verification of algorithm performance are reported in the paper.

关键词： Suppliers selection Decision-making processes greedy algorithm Tabu Search Meta-heuristics Intelligent optimization methods of production systems

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Improved Encryption algorithm for Digital Image of Knight Tour Based on Cell Block

Improved Encryption Algorithm for Digital Image of Knight To...

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32nd Chinese Control And Decision Conference (CCDC)

作者： Xin Liping Wang Xi North Minzu Univ Acad Elect & Informat Engn Yinchuan 750021 Ningxia Peoples R China

ISBN: (数字)9781728158556

ISBN: (纸本)9781728158556

This paper presents an improved algorithm based on digital image encryption of knight tour. The efficient greedy algorithm is used to generate the knight tour matrix to improve the time efficiency of image encryption;the process of image encryption is specifically improved, and two different knight tour matrices are used to encrypt the image. Firstly, every pixel of the image is scrambled one by one, then the scrambled dense image is divided into cell array blocks, and the cell array is used as the operation object to scramble the blocks, and the image is encrypted again. The algorithm is simple, easy to implement, and has strong real-time operability, which can be used for real-time sharing of images;only the combination of the knight patrol matrix used for encryption and scrambling is properly matched, then a better encryption effect picture can be obtained, just like random noise, which cannot be distinguished. The experimental results show that the improved algorithm has strong ability of anti cutting attack and anti noise attack, good image restoration, high security performance and good reliability.

关键词： Knight Tour Image Encryption greedy algorithm Cell Block

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FROG: A Fast and Reliable Crowdsourcing Framework

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IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING 2019年第5期31卷 894-908页

作者： Cheng, Peng Lian, Xiang Jian, Xun Chen, Lei Hong Kong Univ Sci & Technol Dept Comp Sci & Engn Kowloon Hong Kong Peoples R China Kent State Univ Dept Comp Sci Kent OH 44240 USA

For decades, the crowdsourcing has gained much attention from both academia and industry, which outsources a number of tasks to human workers. Typically, existing crowdsourcing platforms include CrowdFlower, Amazon Mechanical Turk (AMT), and so on, in which workers can autonomously select tasks to do. However, due to the unreliability of workers or the difficulties of tasks, workers may sometimes finish doing tasks either with incorrect/incomplete answers or with significant time delays. Existing studies considered improving the task accuracy through voting or learning methods, they usually did not fully take into account reducing the latency of the task completion. This is especially critical, when a task requester posts a group of tasks (e.g., sentiment analysis), and one can only obtain answers of all tasks after the last task is accomplished. As a consequence, the time delay of even one task in this group could delay the next step of the task requester's work from minutes to days, which is quite undesirable for the task requester. Inspired by the importance of the task accuracy and latency, in this paper, we will propose a novel crowdsourcing framework, namely Fast and Reliable crOwdsourcin G framework (FROG), which intelligently assigns tasks to workers, such that the latencies of tasks are reduced and the expected accuracies of tasks are met. Specifically, our FROG framework consists of two important components, task schedulerand notification modules. For the task scheduler module, we formalize a FROG task scheduling (FROG-TS) problem, in which the server actively assigns workers to tasks to achieve high task reliability and low task latency. We prove that the FROG-TS problem is NP-hard. Thus, we design two heuristic approaches, request-based and batch-based scheduling. For the notification module, we define an efficient worker notifying (EWN) problem, which only sends task invitations to those workers with high probabilities of accepting the tasks. To tackle

关键词： Crowdsourcing framework scheduling algorithm greedy algorithm EM algorithm

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FastRule: Efficient Flow Entry Updates for TCAM-Based OpenFlow Switches

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IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS 2019年第3期37卷 484-498页

作者： Qiu, Kun Yuan, Jing Zhao, Jin Wang, Xin Secci, Stefano Fu, Xiaoming Fudan Univ Sch Comp Sci Shanghai 201203 Peoples R China Fudan Univ Shanghai Key Lab Intelligent Informat Proc Shanghai 200433 Peoples R China Cnam Cedric F-75003 Paris France Univ Gottingen Inst Comp Sci D-37077 Gottingen Germany

With an increasing demand for flexible management in software-defined networks (SDNs), it becomes critical to minimize the network policy update time. Although major SDN controllers are now optimized for rapid network update at the control plane, there is still room for data plane optimization in terms of update time, when using TCAM-based physical SDN commodity-off-the-shelf switches. A slow update directly affects network performance and creates bottlenecks. To minimize the flow entry update time, a dependency graph, a kind of directed acyclic graph (DAG), can be used for the access management of flow entries at the switch. Thanks to the DAG, unnecessary entry movements, which are the main factor slowing down flow entry updates, can be avoided. However, existing algorithms show limitations when updates become very frequent. We propose a new flow entry update algorithm, called FastRule, that exploits a greedy strategy with an efficient data structure to accelerate flow entry update with a DAG approach. Moreover, we also adjust our algorithm for other flow table layouts to make it scalable. We elaborate on the correctness of FastRule and test our algorithm using a hardware switch. Compared with existing algorithms, the evaluation shows that our algorithm is about 100x faster than state-of-the-art solutions with a flow table of 1k size.

关键词： Software-defined networks TCAM OpenFlow greedy algorithm flow update

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Effective Periodic Feedback CSI Channel Allocation Under Possible Circumstances in Modern Broadband Wireless Networks

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WIRELESS PERSONAL COMMUNICATIONS 2019年第3期104卷 1133-1148页

作者： Kilaru, Seetaiah BVRIT Hyderabad Coll Engn Women Hyderabad Telangana India

The capacity of the radio link can be improved a lot by using modern wireless technologies like Multiple Input and Multiple Output (MIMO) technology. Successful and efficient implementation of MIMO is possible only when there is a lot of feedback from the mobile station to the base station from time to time. This continuous feedback consumes a lot of uplink bandwidth. Bandwidth is very expensive in the current scenario. Hence, MIMO became expensive setup and viewed as a major obstacle in the deployment. As of our knowledge, this paper is the first to propose a novel scheme for efficient allocation of periodic feedback channel to the wireless network. In this paper, we defined various practical problems in the optimization of network and provided a solution by efficient algorithms. We defined two problems in the allocation process and given a solution with the help of an optimal polynomial-time algorithm. We also proposed a scheme when the base station should adopt the best algorithm among different algorithms. We also proposed combined scheme when Base station limit the resources and unable to execute the defined algorithms. The performances of the algorithms were shown through simulation results.

关键词： MIMO CSI channel greedy algorithm Profit ratio

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Minimizing the average searching time for an object within a graph

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COMPUTATIONAL OPTIMIZATION AND APPLICATIONS 2019年第2期74卷 517-545页

作者： Teller, Ron Zofi, Moshe Kaspi, Moshe Ben Gurion Univ Negev Dept Ind Engn & Management Beer Sheva Israel Sapir Coll Dept Ind Management Sderot Israel

This paper presents a new graph search problem for which a searcher wishes to find an object that may be found at a set of locations. The searcher doesn't know the object's exact location, but does know the a-prior probability of finding the object at each location. He wishes to build a searching path for reaching the object that starts from a given location and ends when reaching the object (or after searching the entire set with a false result). The objective is to find a searching path which will minimize the average searching time. We consider two scenarios for this problem: one when there is an unknown number of objects on the set and another when there is exactly one object on the set (the sum of probabilities is equal to 1). We show that this problem is NP-Hard, and supply a branch and bound algorithm for finding an optimal solution for large scale problems. We also study greedy approaches and other heuristics and compare the performance of these algorithms in various situations.

关键词： Graph search algorithms Object searching Branch and bound Dynamic programming greedy algorithm Heuristic search TSP Ant colony optimization

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Sparse signal reconstruction via expanded subspace pursuit

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JOURNAL OF APPLIED REMOTE SENSING 2019年第4期13卷

作者： Han, Xiaodong Zhao, Guanghui Li, Xiaoming Shu, Ting Yu, Wenxian Shanghai Jiao Tong Univ Shanghai Key Lab Intelligent Sensing & Recognit Shanghai Peoples R China AVIC Leihua Elect Technol Res Inst Wuxi Jiangsu Peoples R China Xidian Univ Sch Elect Engn Xian Shaanxi Peoples R China

Due to their low computational complexity, greedy pursuit algorithms are widely used in sparse signal reconstruction. An improved greedy iterative algorithm, called the expanded subspace pursuit, is proposed. By incorporating a simple backtracking technique, the proposed algorithm removes the mismatching atoms to refine the estimated support set effectively. Furthermore, the proposed algorithm can achieve blind sparse reconstruction even without the prior of the sparsity degree. Compared with other greedy algorithms, the proposed algorithm exhibits superior reconstruction accuracy and lower computational complexity. Finally, numerical results are presented to demonstrate the validity of the proposed algorithm. (C) 2019 Society of Photo-Optical Instrumentation Engineers (SPIE)

关键词： compressed sensing greedy algorithm reconstruction algorithm sparse recovery

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A topology optimization method for electric machines and devices through submodular maximization

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ELECTRONICS AND COMMUNICATIONS IN JAPAN 2019年第6期102卷 3-11页

作者： Sato, Takahiro Fujita, Masafumi Toshiba Energy Syst & Solut Corp Tsurumi Ku 2-4 Suehiro Cho Yokohama Kanagawa Japan

This paper presents a topology optimization method using a greedy algorithm for submodular maximization. This method is based on a shape representation using the normalized Gaussian network. The weight coefficients of Gaussians are discretized to +1/-1, and then their values are greedily inverted. Hence, the computational cost of the present method is relatively smaller than that of evolutionary algorithms. The present method is applied to a magnetic shield optimization problem. It is shown that Pareto solutions can be obtained by the present method. In addition, it can be found from the numerical results that the stochastic greedy algorithm can effectively reduce the computational time compared with the conventional greedy algorithm. As a result, it is shown that a 3-D optimization problem with over 3000 design variables can be solved within acceptable computational time.

关键词： greedy algorithm submodular function topology optimization

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Acceleration of Inverse Molecular Design by Using Predictive Techniques

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JOURNAL OF CHEMICAL INFORMATION AND MODELING 2019年第6期59卷 2587-2599页

作者： Teunissen, Jos L. De Proft, Frank De Vleeschouwer, Freija Vrije Univ Brussel Res Grp Gen Chem ALGC Pl Laan 2 B-1050 Brussels Belgium

This study addresses one of the most important drawbacks inherently related to molecular searches in chemical compound space by greedy algorithms such as Best First Search and Genetic algorithm, i.e., the large computational cost required to optimize one or more quantum-chemical properties. Significant speed-ups are obtained by initial property screening via predictive techniques starting already from very small databases. It is shown that the attainable acceleration depends heavily on the molecular properties, the predictive model, the molecular descriptor, and the current size of the database. We discuss the implementation and performance of predictive techniques in molecular searches based on a fixed molecular framework with a selection of sites to be filled with groups from a chemical fragment library. It is shown that for some properties speed-ups of a factor of 5 to even 20 can be obtained, while inverse design procedures on more complex properties still reach speed-ups of a factor of 2 without losing performance.

关键词： Genetic algorithm (GA) Site location chemical compounds Inverse acceleration Predictive Searches greedy algorithm design process Database Technology factor A

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