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Task scheduling using memetic intelligent water drops algorithm based on tabu search: a case study on azure workflows

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SOFT COMPUTING 2023年第15期27卷 10647-10663页

作者： Hesar, Alireza Sadeghi Mashhad Univ Med Sci Fac Med Dept Med Informat Mashhad Iran

Task scheduling is one of the NP-Complete optimization problems playing a vital role in distributed systems, especially cloud computing and fog computing. The delay due to scheduling affects the pay-as-you-go model negatively and imposes excess costs on users. In this research, a new meta-heuristic based on intelligent water drops algorithm is proposed which uses the tabu search method as a local search. The ideal ability of the intelligent water drops algorithm in general search, along with the remarkable capacity of tabu search in local search guarantees the balance between exploration and exploitation processes in evolutionary cycles. Subsequently, several experiments were performed to evaluate the proposed method on standard benchmark functions, random DAGs, and actual workflows derived from the Microsoft Azure platform, respectively. The results demonstrated that the proposed method also has superiority over the state-of-the-art technologies in terms of algorithmic criteria such as convergence rate and running time, as well as scheduling criteria such as waiting time and makespan.

关键词： Task scheduling Cloud intelligent water drops algorithm Tabu search Makespan Exploration and exploitation

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Hybrid intelligent water drops algorithm for examination timetabling problem

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JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES 2022年第8期34卷 4847-4859页

作者： Aldeeb, Bashar A. Al-Betar, Mohammed Azmi Norwawi, Norita Md Alissa, Khalid A. Alsmadi, Mutasem K. Hazaymeh, Ayman A. Alzaqebah, Malek Imam Abdulrahman Bin Faisal Univ Deanship Informat & Commun Technol Dammam Saudi Arabia Ajman Univ Coll Engn & Informat Technol Artificial Intelligence Res Ctr AIRC Ajman U Arab Emirates Al Balqa Appl Univ Al Huson Univ Coll Dept Informat Technol Irbid Jordan Univ Sains Islam Malaysia Fac Sci & Technol Sembilan Malaysia Imam Abdulrahman Bin Faisal Univ Coll Comp Sci & Informat Technol Dammam Saudi Arabia Imam Abdulrahman Bin Faisal Univ Coll Appl Studies & Community Serv Dept Management Informat Syst Dammam Saudi Arabia Jadara Univ Fac Sci & Informat Technol Dept Math Irbid Jordan Imam Abdulrahman Bin Faisal Univ Coll Sci Dept Math POB 1982 Dammam Saudi Arabia Imam Abdulrahman Bin Faisal Univ Basic & Appl Sci Res Ctr POB 1982 Dammam Saudi Arabia

The current study investigates the intelligent water drops (IWD) metaheuristic algorithm to construct and produce good quality solutions for the university examination timetabling problem (UETP). The IWD isa population-based metaheuristic that simulates the dynamic of the river systems. The main motivations for investigating IWD algorithm for examination timetabling problem is the ability to explore the search space effectively. The main drawback of IWD algorithm is like other population-based algorithm in exploitation process where it is very efficient scanning several search space niches, but it is unable to drilling down in each niche to which it navigates. In this paper we propose a hybrid approach based on IWD and locale search algorithm to improve the exploitation of IWD algorithm. The experimental results demonstrated that the proposed algorithm (i.e., Hybrid IWD) obtained best results in three datasets when comparing with the best-known results performed by the swarm intelligent approaches. Finally, the proposed algorithm achieved one best results in comparison with the other metaheuristic approaches.(c) 2021 The Authors. Published by Elsevier B.V. on behalf of King Saud University. This is an open access article under the CC BY-NC-ND license (http://***/licenses/by-nc-nd/4.0/).

关键词： Examination Timetable intelligent water drops algorithm Metaheuristic Locale search algorithm Optimization

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Automatic Scheduling Using intelligent water drops algorithm 3

Automatic Scheduling Using Intelligent Water Drops Algorithm

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3rd International Conference on Sustainable Information Engineering and Technology (SIET)

作者： Maryati, Indra Sekolah Tinggi Tekn Surabaya Dept Comp Sci Surabaya Indonesia

ISBN: (纸本)9781538674079

There are some differences in scheduling of teaching and learning activities in every school. This is because the need of every school in the schedule is different. Various kinds of algorithms have also been applied in scheduling problems. The most frequently used algorithms for scheduling problems are Genetic algorithms, but this research will use intelligent water drops algorithm. intelligent water drops is an algorithm that is inspired by the movement of water in the river. The movement of water is influenced by the environment, where the water is always moving from higher to lower place and there are many paths with differences in the amount of soil on the riverbed. Representation of this algorithm using graph and schedule will be converted into the form of graphs. By using this algorithm, it is expected that the timetable can be found more quickly and optimally. The first experiments done on each class data reached 100%, with no schedule collision. The second experiments were performed using grade level data, in which there are 9 hours of lessons that collided with the success rate of 79%. The last experiments were performed using all classes data, in which there are 76 hours of lessons that collided with the success rate of 88%.

关键词： Swarm Intelligence intelligent water drops algorithm Scheduling

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Application of intelligent water drops algorithm to Workflow Scheduling in Cloud Environment 8

Application of Intelligent Water Drops Algorithm to Workflow...

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8th International Conference on Computing, Communication and Networking Technologies (ICCCNT)

作者： Kalra, Mala Singh, Sarbjeet Natl Inst Tech Teachers Training & Res Dept Comp Sci & Engn Chandigarh India Panjab Univ Univ Inst Engn & Technol Dept Comp Sci & Engn Chandigarh India

ISBN: (纸本)9781509030385

Cloud Computing has evolved as the one of the most promising approach to execute large scale workflow applications. For successful implementation of any workflow application in cloud computing environment, one of the most significant tasks is to generate an efficient schedule before its execution. The main goal of workflow scheduling is to assign tasks to available resources in a finite time with the satisfaction of users' specified QoS constraints. As workflow scheduling is an NP complete problem, most of the previous work is based on metaheuristic techniques to achieve near optimal solutions within polynomial time. In this paper, we are presenting an application of intelligent water drops (IWD) algorithm, a novel metaheuristic technique, to solve workflow scheduling problem focusing on minimization of makespan. The probability function of MD algorithm is modified to improve quality of solution and enhance convergence speed. Experimental results show that our proposed algorithm achieves better results in comparison to other existing algorithms.

关键词： Scientific Workflows Scheduling intelligent water drops algorithm Cloud Computing Metaheuristic Technique

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An Enhanced intelligent water drops algorithm for Scheduling of an Agile Manufacturing System

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INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY & DECISION MAKING 2016年第2期15卷 239-266页

作者： Teymourian, Ehsan Kayvanfar, Vahid Komaki, Gh M. Khodarahmi, Majtaba Oregon State Univ Sch Mech Ind & Mfg Engn Corvallis OR 97331 USA Amirkabir Univ Technol Dept Ind Engn 424 Hafez Ave Tehran 158754413 Iran Case Western Reserve Univ Dept Elect Engn & Comp Sci 10900 Euclid Ave Cleveland OH 44106 USA Mazandaran Univ Sci & Technol Dept Ind Engn Babol Sar Iran

This paper deals with an agile manufacturing system with two stages where the first stage is the machining stage including a single flexible machine while the second stage is assembly stage including parallel identical assembly machines. Products have an assembly structure where their parts should be processed at the first stage and then proceed to the assembly stage. The goal is to find the parts sequence which minimizes makespan. Since the studied problem is NP-hard, enhanced intelligent water drops (EIWD) algorithm as a new swarm-based nature inspired optimization algorithm is proposed. Also, artificial immune system (AIS) algorithm has been proposed to tackle the addressed problem. Computational results based on randomly generated instances show the effectiveness of the proposed technique.

关键词： Agile manufacturing system intelligent water drops algorithm iterated local search algorithm

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intelligent water drops algorithm for Multimodal Spaces 1

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5th International Conference on Swarm, Evolutionary, and Memetic Computing (SEMCCO)

作者： Harish, Y. Venkateshwarlu, B. Jada, Chakravarthi Rachavarapu, Kranthi Kumar Mohammed, Irfan Feroz Gramoni Rajiv Gandhi Univ Knowledge Technol Basara 504107 India

ISBN: (数字)9783319202945

ISBN: (纸本)9783319202945;9783319202938

This paper presents a new nature inspired intelligent water drops (IWD) based algorithm for finding peaks in continuous multi-modal optimization problems. Initially various conceptual similarities were identified between IWD algorithm and Genetic algorithm(GA). Simultaneously applying IWD-Continuous Optimization(IWD-CO) algorithm and GA on a function in finding the global optima and found IWD-CO having faster convergence qualities. By taking this as basis, GA has been replaced with IWD-CO in a recently developed Modified Roaming Optimization(MRO) algorithm and applied to various benchmark functions and found drastic variation in convergence. Results are proving that replacing GA with IWD-CO can be a novel step in evolutionary based multimodal search algorithms.

关键词： Genetic algorithm intelligent water drops algorithm Roaming optimization Modified roaming optimization Evolutionary computation

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Generalized intelligent water drops algorithm by fuzzy local search and intersection operators on partitioning graph for path planning problem

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JOURNAL OF intelligent & FUZZY SYSTEMS 2015年第2期29卷 975-986页

作者： Monfared, Hesamoddin Salmanpour, Soheila Sharif Univ Technol Dept Comp Engn Tehran Iran Tabari Univ Babol Dept Comp Sci Babol Sar Iran

In this paper, a generalized intelligent water drops algorithm (IWD) for solving robot path planning problem is proposed. The authors want to reduce the time of reaching the optimal solution as much as possible. To do this, some new heuristic operators and a multi section graph model of environment is introduced. The authors divide graph to equal sections and compare behaviour of the solutions (paths) in each section with behaviour of them in other sections. This comparison uses a fuzzy inference system. Base on this comparison, a fuzzy number is assigned to each part of solutions. This fuzzy number determines the worth of a solution in a section. Less worth solutions need more improvement. New heuristic operators are used in the sections that need more improvement. The runtime of algorithms are increased by using a memory for keep proper solutions and a global smooth operator that smooth the solutions. The authors used proposed memory to apply heuristic operations on proper solutions more than other one. This method helps to obtain more improvement in lower runtime. The authors introduce two intersection operators for robot path planning problem that apply to solutions in memory. Experimental results show that the proposed algorithms find the optimal solutions in fewer runtime rather than other works.

关键词： Robot path planning fuzzy logic intelligent water drops algorithm optimization

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Graph Coloring using intelligent water drops algorithm 23

Graph Coloring using Intelligent Water Drops Algorithm

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23rd Iranian Conference on Electrical Engineering

作者： Dadaneh, Behrouz Zamani Markid, Hossein Yeganeh Zakerolhosseini, Ali Shahid Beheshti Univ Dept Comp & Elect Engn Tehran Iran

ISBN: (纸本)9781479919710

Graph coloring is a NP-Hard problem and there is not any polynomial algorithm for solving it yet. Different algorithmic approaches have been applied to find the near optimal solution where two issues always were extremely important;proximity of the solution to the optimal one as well as algorithm speed. Swarm based algorithm is one of the approaches that has been considered. Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO) are some examples. In this paper, we applied another swarm based algorithm to tackle the graph coloring problem (GCP). intelligent water drops (IWD) algorithm, which is used here, has some pre-requirements to be able to solve a problem. According to these pre-requirements, we customized GCP for IWD. The most important issue raised here is that MD compounds both heuristic desirability and past experience in one concept which is called the soil, whereas in the case of algorithms like ACO, these concepts are separate (pheromone corresponds to past experience and heuristic desirability has its own separate amount). We utilized a simple interpreter to overcome this restriction of IWD. The proposed algorithm which is called IWDCOL has been evaluated against the random graphs and numerical results show that the MD algorithm can be one of candidates to tackle the GCP by satisfactory solutions.

关键词： Graph Coloring Problem intelligent water drops algorithm Swarm Intelligence

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Solving University Examination Timetabling Problem Using intelligent water drops algorithm 1

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5th International Conference on Swarm, Evolutionary, and Memetic Computing (SEMCCO)

作者： Aldeeb, Bashar A. Norwawi, Norita Md Al-Betar, Mohammed A. Bin Jali, Mohd Zalisham Univ Sains Islam Malaysia Fac Sci & Technol Nilai 71800 Negeri Sembilan Malaysia Al Balqa Appl Univ Al Huson Univ Coll Dept Informat Technol Irbid Jordan

ISBN: (数字)9783319202945

ISBN: (纸本)9783319202945;9783319202938

This research article aims at proposing intelligent water drops (IWD) algorithm to solve the university examination timetabling problems (UETP). IWD is a recent metaheuristic population-based algorithm belonging to swarm intelligent category which simulate river system. Examination timetabling is a combinatorial optimization problem that is concerned with allocating exams to timeslots efficiently. As an initial study, the IWD algorithm is tailored to solve uncapacitated examination timetabling problem by using carter 1996 dataset and is able to produce acceptable results, though they were not better than the the results that already reported in the literature. Some examination timetabling heuristic methods such as Saturation degree concepts have been embedded in IWD to ensure the feasibility, while the IWD operators have been trigged to iteratively improve the results.

关键词： Uncapacitated examination timetabling problem Scheduling intelligent water drops algorithm

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intelligent water drops algorithm for Vehicle Routing Problem with Time Windows

Intelligent Water Drops Algorithm for Vehicle Routing Proble...

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11th International Conference on Service Systems and Service Management (ICSSSM)

作者： Li, Zhenping Zhao, Fei Liu, Hongwei Beijing Wuzi Univ Sch Informat Beijing Peoples R China

ISBN: (纸本)9781479931347

The vehicle routing problem with time windows (VRPTW) is investigated in this paper. The constraints of vehicle's capacity and the time windows are considered. Based on the principles of the intelligent water drops, a fast and efficient intelligent water drops algorithm for solving the VRPTW is designed. Simulation results show that we can find the global optimal solution of VRPTW with high probability by intelligent water drops algorithm. The average solution found by the intelligent water drops algorithm is better than that found by other algorithms.

关键词： Vehicle routing problem Time windows intelligent water drops algorithm

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