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A heuristic algorithm for Task Scheduling Based on Mean Load on Grid

Journal of Computer Science & Technology 2006年第4期21卷 559-564页

作者：倪丽娜张金泉闫春钢蒋昌俊 Department of Computer Science Tongji University Shanghai 200092 P.R. China College of Information Science & Engineering Shandong University of Science & Technology Qingdao 266510 P.R. China

Efficient task scheduling is critical to achieving high performance on grid computing environment. The task scheduling on grid is studied as optimization problem in this paper. A heuristic task scheduling algorithm satisfying resources load balancing on grid environment is presented. The algorithm schedules tasks by employing mean load based on task predictive execution time as heuristic information to obtain an initial scheduling strategy. Then an optimal scheduling strategy is achieved by selecting two machines satisfying condition to change their loads via reassigning their tasks under the heuristic of their mean load. Methods of selecting machines and tasks are given in this paper to increase the throughput of the system and reduce the total waiting time. The efficiency of the algorithm is analyzed and the performance of the proposed algorithm is evaluated via extensive simulation experiments. Experimental results show that the heuristic algorithm performs significantly to ensure high load balancing and achieve an optimal scheduling strategy almost all the time. Furthermore, results show that our algorithm is high efficient in terms of time complexity.

关键词： heuristic algorithm task scheduling load balancing knowledge grid

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A new meta-heuristic algorithm for continuous engineering optimization: harmony search theory and practice

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COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING 2005年第36-38期194卷 3902-3933页

作者： Lee, KS Geem, ZW NIST Mat & Construct Res Div Bldg & Fire Res Lab Gaithersburg MD 20899 USA Univ Maryland Dept Civil & Environm Engn College Pk MD 20742 USA

Most engineering optimization algorithms are based on numerical linear and nonlinear programming methods that require substantial gradient information and usually seek to improve the solution in the neighborhood of a starting point. These algorithms, however, reveal a limited approach to complicated real-world optimization problems. If there is more than one local optimum in the problem, the result may depend on the selection of an initial point, and the obtained optimal solution may not necessarily be the global optimum. This paper describes a new harmony search (HS) meta-heuristic algorithm-based approach for engineering optimization problems with continuous design variables. This recently developed HS algorithm is conceptualized using the musical process of searching for a perfect state of harmony. It uses a stochastic random search instead of a gradient search so that derivative information is unnecessary. Various engineering optimization problems, including mathematical function minimization and structural engineering optimization problems, are presented to demonstrate the effectiveness and robustness of the HS algorithm. The results indicate that the proposed approach is a powerful search and optimization technique that may yield better solutions to engineering problems than those obtained using current algorithms. (c) 2004 Elsevier B.V. All rights reserved.

关键词： harmony search heuristic algorithm continuous design variables mathematical function minimization structural engineering optimization

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High speed ghost imaging based on a heuristic algorithm and deep learning

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Chinese Physics B 2021年第6期30卷 287-293页

作者： Yi-Yi Huang Chen Ou-Yang Ke Fang Yu-Feng Dong Jie Zhang Li-Ming Chen Ling-An Wu Institute of Physics Chinese Academy of SciencesBeijing 100190China University of Chinese Academy of Sciences Beijing 100049China IFSA Collaborative Innovation Center and School of Physics and Astronomy Shanghai Jiao Tong UniversityShanghai 200240China College of Engineering Physics Shenzhen Technology UniversityShenzhen 518118China

We report an overlapping sampling scheme to accelerate computational ghost imaging for imaging moving targets,based on reordering a set of Hadamard modulation matrices by means of a heuristic algorithm. The new condensed overlapped matrices are then designed to shorten and optimize encoding of the overlapped patterns, which are shown to be much superior to the random matrices. In addition, we apply deep learning to image the target, and use the signal acquired by the bucket detector and corresponding real image to train the neural network. Detailed comparisons show that our new method can improve the imaging speed by as much as an order of magnitude, and improve the image quality as well.

关键词： high speed computational ghost imaging heuristic algorithm deep learning

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Robust operating room planning considering upstream and downstream units: A new two-stage heuristic algorithm

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COMPUTERS & INDUSTRIAL ENGINEERING 2020年 143卷 106387-106387页

作者： Moosavi, Amirhossein Ebrahimnejad, Sadoullah Univ Ottawa Telfer Sch Management 55 Laurier Ave East Ottawa ON K1N 6N5 Canada Islamic Azad Univ Dept Ind Engn Karaj Branch POB 31485-313 Karaj Iran

This paper studies the operating room planning problem at the tactical and operational decision levels considering upstream and downstream units. For this purpose, a multi-objective mathematical programming model is proposed for the construction of master surgical scheduling and the allocation of elective and emergency surgeries. This model encompasses the profits of all stakeholders in the operating theater. A new policy, named complete opening policy, is introduced for the management of operating rooms that has some particular benefits compared to the conventional policy. Then, a scenario-based robust formulation is proposed to consider the uncertainties of surgery duration, length of stay and emergency demands. Because the simpler variants of this problem are known to be NP-complete, a new two-stage heuristic algorithm is developed for solving its large-scale instances. During the first stage, this algorithm generates an initial solution using a greedy constructive algorithm. To improve the initial solution, the algorithm applies eight actions and searches the neighborhoods. In the second stage, the algorithm evaluates whether or not closing an operating room could improve the incumbent solution. A heuristic algorithm, named partial-mixed integer programming, is also adapted as a benchmark algorithm. This algorithm incorporates the CPLEX solver and a very large-scale neighborhood search. Eventually, a hospital in Iran is introduced and evaluated. The computational results demonstrate that the application of the proposed methodology could potentially decrease the waiting cost, the overtime and idleness of operating rooms, and the total deviation from the average beds used in upstream and downstream. The computational results also show that an increase of two beds in the intensive care unit might potentially reduce the waiting cost by 3.6% and the total average of overtime and idleness of operating rooms each day by 20.3%.

关键词： Operating room Tactical decision-making Operational decision-making Uncertainty heuristic algorithm

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A fast and efficient heuristic algorithm for the delay- and delay variation-bounded multicast tree problem

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COMPUTER COMMUNICATIONS 2002年第8期25卷 825-833页

作者： Sheu, PR Chen, ST Natl Yunlin Univ Sci & Technol Dept Elect Engn Touliu 640 Yunlin South Korea

More and more multicast communications are becoming real-time. In real-time communications, messages must be transmitted to their destination nodes within a certain amount of time;otherwise the messages will be rendered futile. To support real-time multicast communications, computer networks have to guarantee an upper bound on the end-to-end delay from the source node to each of the destination nodes. This is known as the multicast end-to-end delay problem [10]. On the other hand, if the same message fails to arrive at each destination node at the same time, there will probably arise inconsistency or unfairness problem among users. This is related to the multicast delay variation problem [10]. Our research subject in the present paper is concerned with the minimization of multicast delay variation under the multicast end-to-end delay constraint. The problem is first defined and discussed in Ref. [10]. They have proved it to be an NP-complete problem and proposed a heuristic algorithm for it called DVMA (Delay Variation Multicast algorithm). In this paper, we find that in spite of DVMA's smart performance in terms of multicast delay variations, its time complexity is as high as O(klmn(4)). It is strongly believed that such a high time complexity does not fit in modern high-speed computer network environment. Therefore, we will present an alternative heuristic algorithm with a much lower time complexity O(mn(2)) and with a satisfactory performance. Computer simulations also testify that our algorithm is both fast and efficient. (C) 2002 Published by Elsevier Science B.V.

关键词： multicast communications delay variation end-to-end delay heuristic algorithm time complexity

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A Newton-based heuristic algorithm for multi-objective flexible job-shop scheduling problem

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JOURNAL OF INTELLIGENT MANUFACTURING 2016年第2期27卷 409-416页

作者： Fernandez Perez, Miguel A. Raupp, Fernanda M. P. Pontificia Univ Catolica Rio de Janeiro Dept Ind Engn Rio De Janeiro Brazil

We propose a new hierarchical heuristic algorithm for multi-objective flexible job-shop scheduling problems. The proposed method is an adaptation of the Newton's method for continuous multi-objective unconstrained optimization problems, belonging to the class of multi-criteria descent methods. Numerical experiments with the proposed method are presented. The potential of the proposed method is demonstrated by comparing the obtained results with the known results of existing methods that solve the same test instances.

关键词： heuristic algorithm Flexible job-shop scheduling Multi-objective optimization Multi-criteria Newton method

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A heuristic algorithm based on leaf photosynthate transport

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SIMULATION-TRANSACTIONS OF THE SOCIETY FOR MODELING AND SIMULATION INTERNATIONAL 2018年第7期94卷 593-607页

作者： Yu Bin Shan Wenxuan Guo Zhen Wang Yunpeng Beihang Univ Sch Transportat Sci & Engn Beijing 100191 Peoples R China

Transportation network design is non-deterministic polynomial-time hard due to its attributes of multi-objects, multi-constraints, and the non-convexity objective function. In this paper, a bi-level programming model is proposed for the transportation network design. The upper layer pursues the minimum total travel time of users and the total length of the road network simultaneously, while the lower layer is an equilibrium assignment model. A new algorithm for the network optimization based on the principle of leaf photosynthate transport in nature is proposed. The proposed algorithm simulates the natural selection of biological evolution and genetic transmission. It can retain the genetic idea of the evolutionary algorithm, together with the heuristic information update mechanism of swarm intelligence. Finally, empirical research is carried out with the Sioux Falls network to validate the performance of the proposed algorithm. The results show that although the total network length obtained by the proposed algorithm increases slightly compared with the ant colony algorithm and the genetic algorithm, the total travel time and objective function value reduce obviously. This indicates that the proposed algorithm has good performance on topology and efficiency.

关键词： heuristic algorithm leaf photosynthate transport evolutionary rule transportation network optimization

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A heuristic algorithm for determining replacement policies in consecutive k-out-of-n systems

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COMPUTERS & OPERATIONS RESEARCH 2004年第8期31卷 1335-1348页

作者： Flynn, J Chung, CS Cleveland State Univ Dept Operat Management & Businss Stat Cleveland OH 44115 USA

This article presents a heuristic algorithm for determining replacement policies in a discrete-time, infinite-horizon, dynamic programming model of a binary coherent system with n statistically independent components, and then specializes the algorithm to consecutive k-out-of-n systems. Costs arise when the system fails and when failed components are replaced. The objective is to minimize the long run expected average undiscounted cost per period. A companion article (Naval Res. Logistics 49 (2002) 288) develops a branch and bound algorithm for computing optimal policies. Extensive computational experiments on consecutive k-out-of-n systems find it effective when n less than or equal to 40 or k is near n;however, the computations can be intractable when n > 40 and 2 less than or equal to k < n - 15, suggesting the need for a good heuristic. Computational experiments on consecutive k-out-of-n systems involving over 300,000 test problems find the heuristic of this article highly effective. For each n and k tested, its percentage error was under 2.53%, and its mean computation time on a 1700 MHz Pentium IV was under 0.24 s (the largest n in our experiments was 200). (C) 2003 Elsevier Ltd. All rights reserved.

关键词： heuristic algorithm reliability replacement policies multicomponent consecutive k-out-of-n

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A novel heuristic algorithm for disruption mitigation in a global food supply chain

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COMPUTERS & INDUSTRIAL ENGINEERING 2024年 194卷

作者： Sasi, Mani Bakhshi Sarker, Ruhul A. Essam, Daryl L. Univ New South Wales Canberra Sch Syst & Comp Canberra Australia

The Global Food Supply Chain (GFSC) often encounters challenges in maintaining the continuous flow of essential food products such as rice and wheat. In this paper, we consider possible disruptions in supply and transportation in GFSC. Disruptions may cause severe food shortages in some parts of the world. Moreover, a disruption is not necessarily a single independent event, as multiple disruptions may occur sequentially or simultaneously. After any interruption, it is essential to reoptimize the remaining flow activities in a short period under the changed conditions. Although both the initial flow plan and post-disruption plan can be generated by formulating them as Mixed Integer Linear Programming (MILP) models, such a mitigation plan is challenging because of time constraints and when multiple disruptions are considered. To address this issue, we proposed a novel heuristic algorithm that revises the ideal plan in the event of a disruption. The developed heuristic can deal with different types of disruptions, as well as a series of disruptions. The performance of the heuristic was judged by solving 300 problem instances and comparing the results with those obtained from the exact method. To demonstrate the applicability of the proposed algorithm in practice, we have solved three real-world disruption Scenarios. The analysis of results uncovered crucial managerial insights, recommending strategies for disruption mitigation, and proved to be an effective method for post-disruption planning.

关键词： Global Food Supply Chain Rice and wheat supply chain Disruption mitigation heuristic algorithm Recovery plan

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AN EFFICIENT heuristic algorithm FOR TWO-DIMENSIONAL RECTANGULAR PACKING PROBLEM WITH CENTRAL RECTANGLE

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JOURNAL OF INDUSTRIAL AND MANAGEMENT OPTIMIZATION 2020年第1期16卷 495-510页

作者： Chen, Mao Tang, Xiangyang Zeng, Zhizhong Liu, Sanya Cent China Normal Univ Natl Engn Res Ctr E Learning Wuhan 430079 Hubei Peoples R China

This paper presents a heuristic algorithm for solving a specific NP-hard 2D rectangular packing problem in which a rectangle called central rectangle is required to be placed in the center of the final layout, and the aspect ratio of the container is also required to be in a given range. The key component of the proposed algorithm is a greedy constructive procedure, according to which, the rectangles are packed into the container one by one and each rectangle is packed into the container by an angle-occupying placement with maximum fit degree. The proposed algorithm is evaluated on two groups of 35 well-known benchmark instances. Computational results disclose that the proposed algorithm outperforms the previous algorithm for the packing problem. For the first group of test instances, solutions with average filling rate 99.31% can be obtained;for the real-world layout problem in the second group, the filling rate of the solution is 94.75%.

关键词： Optimization heuristic algorithm 2D rectangular packing problem central rectangle angle-occupying placement

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