Papers by Seyedsaeid Mirkamali
IEEE Access
The Traveling Salesman Problem (TSP) which is a theoretical computer science and operations resea... more The Traveling Salesman Problem (TSP) which is a theoretical computer science and operations research problem, has several applications even in its purest formulation, such as the manufacture of microchips, planning, and logistics. There are many methods proposed in the literature to solve TSP with gains and losses. We propose a discrete metaheuristic method called D-PFA to solve this problem more efficiently. Initially, the Pathfinder Algorithm (PFA) was presented to handle issues involving continuous optimization, where it worked effectively. In recent years, there have been various published variants of PFA, and it has been frequently employed to address engineering challenges. In this study, the original PFA algorithm is broken into four sub-algorithms and every sub-algorithm is discretized and coupled to form a new algorithm. The proposed algorithm has a high degree of flexibility, a quick response time, strong exploration and exploitation. To validate the significant advantages of the proposed D-PFA, 34 different instances with different sizes are used in simulation results. The proposed method was also compared with 12 State-of-the-Art algorithms. Results indicate that the suggested approach is more competitive and resilient in solving TSP than other algorithms in different aspects. A conclusion and an outlook on future studies and applications are given at the end of the paper.
IEEE Access
Nowadays, mobile devices can run a wide range of programs, and they all require more and more pro... more Nowadays, mobile devices can run a wide range of programs, and they all require more and more processing power. Due to their limited resources, mobile devices often make use of cloud computing ′ s offloading features to do more complex tasks. The offloading problem in Mobile Cloud Computing (MCC) is the task scheduling problem, which entails deciding where to dump work to maximize its value. The task scheduling problem in MCC is an NP-hard problem because of the difficulty in moving resources and the size of the search space required to find the ideal scheduler, making the use of extensive search techniques impractical. For this reason, metaheuristic search strategies are provided, to yield a best-case or near-bestcase scenario in terms of job completion time and energy savings. This work provides a non-dominated multi-objective strategy based on the Harris Hawks Optimization (HHO) technique called Hybrid Multiobjective Harris Hawks Optimization (HMHHO) to handle the described issue in MCC. The objectives of this research were allocating jobs from mobile source nodes to processors in the public cloud, cloud patches, and processors in mobile resources. In comparison to the other four algorithms-the Genetic Algorithm (GA), the Ant Colony Optimization (ACO), the Particle Swarm Optimization (PSO), and the Cuckoo Search Algorithm (CSA) the proposed method completes jobs faster and uses less energy on average. INDEX TERMS Task scheduling, multi-objective, mobile cloud computing, optimization, metaheuristic algorithm, Harris Hawks optimization. I. INTRODUCTION Cloud computing is intended to offer computer services such as servers, storage, databases, networks, software, and so on. Instead of having their own computer infrastructure or data centers, businesses may utilize cloud computing to access anything from apps to sufficient storage space [1], [2]. The availability of cloud computing services in a mobile environment to deliver optimum services to mobile phone The associate editor coordinating the review of this manuscript and approving it for publication was Yinliang Xu. users is referred to as Mobile Cloud Computing (MCC). Since all MCC data and complex computing modules can be computed on the cloud, there is no need for mobile devices to have robust specifications like a fast CPU, a lot of storage space, and so on. However, there are several resource concerns (such as battery life, storage space, and bandwidth) and communication issues unique to mobile devices (e.g., privacy, mobility, and security). The service quality is drastically impacted by these issues [3], [4]. A scheduler ′ s principal purpose is to decrease run-time and distribute appropriate resources to activities [5], [6].
An improved particle swarm optimization algorithm for task scheduling in cloud computing
Journal of Ambient Intelligence and Humanized Computing
GSAGA: A hybrid algorithm for task scheduling in cloud infrastructure
The Journal of Supercomputing
Complexity
Open Shop Scheduling Problem (OSSP) is one of the most important scheduling problems in the field... more Open Shop Scheduling Problem (OSSP) is one of the most important scheduling problems in the field of engineering and industry. This kind of problem includes m machines and n jobs, each job contains a certain number of operations, and each operation has a predetermined processing time on its corresponding machine. The order of processing of these operations affects the completion times of all jobs. Therefore, the purpose of OSSP is to achieve a proper order of processing of jobs using specified machines, so that the completion time of all jobs is minimized. In this paper, the strengths and limitations of three methods are evaluated by comparing the results of solving the OSSP in large-scale and small-scale benchmarks. In this case, the minimized completion time and total tardiness are considered the objective functions of the adapted methods. To solve small-scale problems, we adapt a mathematical model called Multiobjective Mixed Linear Programming (MOMILP). To solve large-scale prob...
Hybrid Gravitational Search Algorithm to Solve the Task Scheduling Problem of Two-Machine Flow Shop
The main goal of any task scheduling problem is to map several tasks to proper processors so that... more The main goal of any task scheduling problem is to map several tasks to proper processors so that it could optimize one or more objectives at an acceptable time under some constraints. In this paper, the problem of scheduling n independent work with different due times on Two -Machines in the sequential flow shop environment is investigated. To solve this problem, we propose a hybrid metaheuristic algorithm that combines the Simulated Annealing (SA) with Gravitational Search Algorithm (GSA) called SA_GSA. The proposed hybrid algorithm starts the above problem by defining two stages. First, we generate an initial solution of the problem using the SA algorithm, then we run the GSA algorithm on the generated solution. To evaluate the answers, the criterion of the minimum weight of delays and delays of tasks has been used as an objective function, which is considered in line with the goals of timely production systems. The proposed algorithm is presented in 4 scenarios, which are obtain...
Signal, Image and Video Processing, 2014
We reviewed the literature on transcutaneous electrical nerve stimulation (TENS) used as a therap... more We reviewed the literature on transcutaneous electrical nerve stimulation (TENS) used as a therapy for overactive bladder (OAB) symptoms, with a particular focus on: stimulation site, stimuli parameters, neural structures thought to be targeted, and the clinical and urodynamic outcomes achieved. The majority of studies used sacral or tibial nerve stimulation. The literature suggests that, whilst TENS therapy may have neuromodulation effects, patient are unlikely to benefit to a significant extent from a single application of TENS and indeed clear benefits from acute studies have not been reported. In long-term studies there were differences in the descriptions of stimulation intensity, strategy of the therapy, and positioning of the electrodes, as well as in the various symptoms and pathology of the patients. Additionally, most studies were uncontrolled and hence did not evaluate the placebo effect. Little is known about the underlying mechanism by which these therapies work and therefore exactly which structures need to be stimulated, and with what parameters. There is promising evidence for the efficacy of a transcutaneous stimulation approach, but adequate standardisation of stimulation criteria and outcome measures will be necessary to define the best way to administer this therapy and document its efficacy.
The Era of Interactive Media, 2012
Recent advances in 3D modeling and depth estimation of objects have created many opportunities fo... more Recent advances in 3D modeling and depth estimation of objects have created many opportunities for multimedia computing. Using depth information of a scene enables us to propose a brand new segmentation method called Depth-Wise segmentation. Unlike the conventional image segmentation problems which deal with surface-wise decomposition, the depth-wise segmentation is a problem of slicing an image containing 3D objects in a depth-wise sequence. The proposed method uses entropy of a depth image to characterize the edges of objects in a scene. Later, obtained edges are used to find Line-Segments. By linking the line-segments based on the ir object and layer numbers, Objects-Layers are achieved. To test the proposed segmentation algorithm, we use syntactic images of some 3D scenes and their depth maps. The experiment results show that our method gives good performance.
Image segmentation has long been a basic problem in computer vision. Depth-wise Layering is a kin... more Image segmentation has long been a basic problem in computer vision. Depth-wise Layering is a kind of segmentation that slices an image in a depth-wise sequence unlike the conventional image segmentation problems dealing with surface-wise decomposition. The proposed Depth-wise Layering technique uses a single depth image of a static scene to slice it into multiple layers. The technique employs a thresholding approach to segment rows of the dense depth map into smaller partitions called Line-Segments in this paper. Then, it uses the line-segment labelling method to identify number of objects and layers of the scene independently. The final stage is to link objects of the scene to their respective object-layers. We evaluate the efficiency of the proposed technique by applying that on many images along with their dense depth maps. The experiments have shown promising results of layering.
Neural Computing and Applications
Using the Cuckoo Optimization Algorithm to Solve the Point Coverage Problem with Moving Targets in Wireless Sensor Networks
Wireless Sensor Networks (WSNs) have been used in many sectors in recent years. Easy deployment a... more Wireless Sensor Networks (WSNs) have been used in many sectors in recent years. Easy deployment and low prices are the main reasons for using WSN. On the other hand, power source limitations and unstructured overlay networks are the major concerns in these kinds of networks. Region coverage is one of the problems that should be solved smartly in order to maximize the productivity of the network. Appropriate sensor selection and efficient energy usage are essential in region coverage. Pointwise coverage is a well-known version of the coverage problem. Since this is an NP-complete problem, many approaches have already been designed to solve it. The main shortcoming in previous works is the short network lifetime due to high energy consumption. In this paper, an enhanced method has been proposed based on the Cuckoo Optimization Algorithm (COA). By means of an adjusted version of the cuckoo search and a heuristic fitness function, it has been possible to expand the lifespan of the netwo...
Wirel. Commun. Mob. Comput., 2021
School of Software, Dalian Neusoft University of Information, Dalian, China Department of Compute... more School of Software, Dalian Neusoft University of Information, Dalian, China Department of Computer Engineering, Moghadas Ardabili Institute of Higher Education, Ardabil, Iran Department of Computer and Information Technology Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran Department of Engineering, Islamic Azad University, South Tehran Branch, Tehran, Iran Department of Computer Science and Information Technology, Mahdishahr Branch, Islamic Azad University, Mahdishahr, Iran School of Computer and Software, Dalian Neusoft University of Information, Dalian, China Department of Computer Engineering and IT, Payame Noor University (PNU), Tehran, Iran
ArXiv, 2020
Image segmentation has long been a basic problem in computer vision. Depth-wise Layering is a kin... more Image segmentation has long been a basic problem in computer vision. Depth-wise Layering is a kind of segmentation that slices an image in a depth-wise sequence unlike the conventional image segmentation problems dealing with surface-wise decomposition. The proposed Depth-wise Layering technique uses a single depth image of a static scene to slice it into multiple layers. The technique employs a thresholding approach to segment rows of the dense depth map into smaller partitions called Line- Segments in this paper. Then, it uses the line- segment labelling method to identify number of objects and layers of the scene independently. The final stage is to link objects of the scene to their respective object-layers. We evaluate the efficiency of the proposed technique by applying that on many images along with their dense depth maps.The experiments have shown promising results of layering
A feature selection approach for spam detection in social networks using gravitational force-based heuristic algorithm
Nowadays, technologies cover all human life areas and expand communication platforms with suitabl... more Nowadays, technologies cover all human life areas and expand communication platforms with suitable and low-cost space. Advertising and profiteering organizations use this large space of audience and low-cost platform to send their desired information and goals in the form of spam. In addition to creating problems for users, it causes time and bandwidth consumption. They will also be a threat to the productivity, reliability, and security of the network. Various approaches have been proposed to combat spam. The most dynamic and best methods of spam filtering are machine learning and deep learning, which perform high-speed filtering and classification of spam. In this paper, we present a new way to discover spam on various social networks by scaling up a Support Vector Machine (SVM) based on a combination of the Genetic Algorithm (GA) and Gravitational Emulation Local Search Algorithm (GELS) to select the most effective features of spam. The experiments' results show that the accu...
Object removal by depth-wise image inpainting
Signal, Image and Video Processing, 2014
The problem posed in this paper was to fill-up the hole in the digital image left behind after th... more The problem posed in this paper was to fill-up the hole in the digital image left behind after the removal of an object from it. The real challenge is to deal with images of cluttered scenes of objects with complex and infrequent textures. In the past, this problem has been addressed by two classes of algorithms: (i) exemplar-based algorithms to fill the hole using the patches available in a given example and (ii) depth-based algorithms to differentiate the foreground and background before inpainting. This paper presents a novel method that combines advantages of these two approaches. We use depth map of an image to find the order of all the objects in the target image and a database of multi-views of objects to fill the holes. To reduce the size of the database, we propose a method called Keyview Extraction. An object retrieval followed by geometric and photometric registration algorithms is employed to make every object an exact match for inpainting. A number of experiments on both real and synthetic images demonstrate the advantage of depth-wise image inpainting compared with other inpainting methods. In these experiments, we compare three different types of image inpainting methods with our method quantitatively by computing their SSIM values using a ground-truth.
Neural Computing and Applications
The cloud computing systems are sorts of shared collateral structure which has been in demand fro... more The cloud computing systems are sorts of shared collateral structure which has been in demand from its inception. In these systems, clients are able to access existing services based on their needs and without knowing where the service is located and how it is delivered, and only pay for the service used. Like other systems, there are challenges in the cloud computing system. Because of a wide array of clients and the variety of services available in this system, it can be said that the issue of scheduling and, of course, energy consumption is essential challenge of this system. Therefore, it should be properly provided to users, which minimizes both the cost of the provider and consumer and the energy consumption, and this requires the use of an optimal scheduling algorithm. In this paper, we present a two-step hybrid method for scheduling tasks aware of energy and time called Genetic Algorithm and Energy-Conscious Scheduling Heuristic based on the Genetic Algorithm. The first step...
A New Efficient Approach for Solving the Capacitated Vehicle Routing Problem Using the Gravitational Emulation Local Search Algorithm
Applied Mathematical Modelling, 2017
Capacitated Vehicle Routing Problem (CVRP) is one of the most famous specialized forms of the VRP... more Capacitated Vehicle Routing Problem (CVRP) is one of the most famous specialized forms of the VRP, which has attracted considerable attention from scientists and researchers. Therefore, many accurate, heuristic, and meta-heuristic methods have been introduced to solve this problem in recent decades. In this paper, a new meta-heuristic optimization algorithm is introduced to solve the CVRP, which is based on the law of gravity and group interactions. The proposed algorithm uses two of the four basic parameters of velocity and gravitational force in physics based on the concepts of random search and searching agents, which are a collection of masses that interact with each other based on Newtonian gravity and the laws of motion. The introduced method was quantitatively compared with the Stateof-the-Art algorithms in terms of execution time and number of optimal solutions achieved in four well-known benchmark problems. Our experiments illustrated that the proposed method could be a very efficient method in solving CVRP and the results are comparable with the results using state-of-the-art computational methods. Moreover, in some cases our method could produce solutions with less number of required vehicles compared to the Best Known Solution (BKS) in a very efficient manner, which is another advantage of the proposed algorithm.
A New Efficient Approach for Solving the Capacitated Vehicle Routing Problem Using the Gravitational Emulation Local Search Algorithm
Applied Mathematical Modelling
Capacitated Vehicle Routing Problem (CVRP) is one of the most famous specialized forms of the VRP... more Capacitated Vehicle Routing Problem (CVRP) is one of the most famous specialized forms of the VRP, which has attracted considerable attention from scientists and researchers. Therefore, many accurate, heuristic, and meta-heuristic methods have been introduced to solve this problem in recent decades. In this paper, a new meta-heuristic optimization algorithm is introduced to solve the CVRP, which is based on the law of gravity and group interactions. The proposed algorithm uses two of the four basic parameters of velocity and gravitational force in physics based on the concepts of random search and searching agents, which are a collection of masses that interact with each other based on Newtonian gravity and the laws of motion. The introduced method was quantitatively compared with the Stateof-the-Art algorithms in terms of execution time and number of optimal solutions achieved in four well-known benchmark problems. Our experiments illustrated that the proposed method could be a ver...
Recent advances in 3D modeling and depth estimation of objects have created many opportunities fo... more Recent advances in 3D modeling and depth estimation of objects have created many opportunities for multimedia computing. Using depth information of a scene enables us to propose a brand new segmentation method called Depth-Wise segmentation. Unlike the conventional image segmentation problems which deal with surface-wise decomposition, the depth-wise segmentation is a problem of slicing an image containing 3D objects in a depth-wise sequence. The proposed method uses entropy of a depth image to characterize the edges of objects in a scene. Later, obtained edges are used to find Line-Segments. By linking the line-segments based on the ir object and layer numbers, Objects-Layers are achieved. To test the proposed segmentation algorithm, we use syntactic images of some 3D scenes and their depth maps. The experiment results show that our method gives good performance.
Depth-Wise Multi-layered 3D Modeling
International Symposium on Distributed …, Jan 1, 2011
3D modeling is an emerging trend both in the areas of machine vision and computer graphics. With ... more 3D modeling is an emerging trend both in the areas of machine vision and computer graphics. With the current 3D modeling systems the user can virtually travel around a scene and see the foreground objects. A 3D model would be more realistic if the user could also go into the depth of a scene from a specific view and see the obscured objects as well as foreground objects. The aim of this paper is to present a new scheme of 3D modeling which capable of segmenting a specific view of a scene into depth-wise multiple layers followed ...
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Papers by Seyedsaeid Mirkamali