Jaafar Abouchabaka - Academia.edu (original) (raw)

Papers by Jaafar Abouchabaka

International Journal of Open Problems in Computer Science and Mathematics, Jun 1, 2017

The Traveling Salesman Problem (TSP) is a combinatorial optimization problem of great importance ... more The Traveling Salesman Problem (TSP) is a combinatorial optimization problem of great importance which continues to interest several researchers in order to develop methods to achieve an optimal solution. Genetic algorithms (GAs) as meta-heuristic methods have been widely applied to this problem. Inspired by biological phenomena, we introduce two immigration operators, random immigration and structured memory immigration, forming two different algorithms. The performance of these algorithms is evaluated using benchmark datasets of symmetric TSP from TSPLIB library. The results of the proposed algorithms are compared with the standard genetic algorithm showing that the proposed algorithms improve the performance of GA in solving TSP problem effectively and specifically with the developed structured memory immigration.

The genetic algorithm includes some parameters that should be adjusted, so as to get reliable res... more The genetic algorithm includes some parameters that should be adjusted, so as to get reliable results. Choosing a representation of the problem addressed, an initial population, a method of selection, a crossover operator, mutation operator, the probabilities of crossover and mutation, and the insertion method creates a variant of genetic algorithms. Our work is part of the answer to this perspective to find a solution for this combinatorial problem. What are the best parameters to select for a genetic algorithm that creates a variety efficient to solve the Travelling Salesman Problem (TSP)? In this paper, we present a comparative analysis of different mutation operators, surrounded by a dilated discussion that justifying the relevance of genetic operators chosen to solving the TSP problem.

Procedia Computer Science

International Journal of Information and Computer Security

Multi-agent system (MAS) appears as a solution to satisfy the requirement of intelligence in dist... more Multi-agent system (MAS) appears as a solution to satisfy the requirement of intelligence in distributed system, this paradigm also accepts distribution and networking as a basic concept. MAS is a system which there is an agent that can act autonomously with intelligent behaviour and can solve complex problem. Mobility is a property of agent which allows him to move from one node to another to achieve their goal. Researchers in different fields have been attracted by systems based on mobile agent, because of the pro-active aspects and the autonomous tasks of the agent. Unfortunately the security of mobile agents is very difficult, especially when it comes to secure an entity that migrates from one platform to another across the network, and which must be executed correctly and safely on the hosting platform. In this paper we will focus on the security aspect of a mobile agent from one platform to another, by introducing a new approach based on cryptographic mechanisms. This approach involves the Amrani et al.'s protocol to get a session key, to guarantee a mutual authentication and the confidentiality of data exchanged, as well as a binary serialisation to ensure the mobility of the agent across the network.

International Journal of Communication Networks and Information Security (IJCNIS), Apr 19, 2019

using multi agents in the wireless sensor networks (WSNs) for aggregating data has gained signifi... more using multi agents in the wireless sensor networks (WSNs) for aggregating data has gained significant attention. Planning the optimal itinerary of the mobile agent is an essential step before the process of data gathering. Many approaches have been proposed to solve the problem of planning MAs itineraries, but all of those approaches are assuming that the MAs visit all SNs and large number of intermediate nodes. This assumption imposed a burden; the size of agent increases with the increase in the visited SNs, therefore consume more energy and spend more time in its migration. None of those proposed approaches takes into account the significant role that the connected dominating nodes play as virtual infrastructure in such wireless sensor networks WSNs. This article introduces a novel energy-efficient itinerary planning algorithmic approach based on the minimum connected dominating sets (CDSs) for multi-agents dedicated in data gathering process. In our proposed approach, instead of planning the itineraries over all sensor nodes SNs, we plan the itineraries among subsets of the MCDS in each cluster. Thus, no need to move the agent in all the SNs, and the intermediate nodes (if any) in each itinerary will be few. Simulation results have demonstrated that our approach is more efficient than other approaches in terms of overall energy consumption and task execution time.

INTERNATIONAL JOURNAL OF MANAGEMENT & INFORMATION TECHNOLOGY, 2013

In this paper, we present the lAD-calculus witch is an elementary functional distributed actor la... more In this paper, we present the lAD-calculus witch is an elementary functional distributed actor language with a new approach of message communication between actors in a distributed environment. This strategy is based on a static analysis which allows determining the parts of a message that must be transmitted. The actors we consider have a functional script and manipulate the terms of the lAD-calculus. The expressions of this language correspond to those of the l-calculus extent by some actor primitives.

Advances in Intelligent Systems and Computing, 2019

In this work, we are interested to propose a new genetic approach to improve the optimal solution... more In this work, we are interested to propose a new genetic approach to improve the optimal solution of a constrained assignment problem of human resources within the multi sites enterprise. By taking into consideration various constraints, this problem can be defined as a NP-hard combinatorial problem as we have showed [2]. In this work, we have developed the mathematical formulation of this problem and proposed a genetic approach to the search for an optimal solution, but we have noticed that the phenomenon of stagnation of this proposed genetic algorithm persists although increases in the number of iterations lead to a significant consumption of computing time and memory space. To remedy this problem, we propose in this paper to integrate new genetic methods, such as Standard Immigration Genetic (SIG) [2], able of improving the convergence towards the optimum. This process is based on the insertion of a percentage of best individuals from previous generations in the genetic population to improve the diversity of the population and to bias the search direction for obtaining the best solution. The results are being evaluated and compared with other results obtained using the last proposed genetic approach.

Indonesian Journal of Electrical Engineering and Computer Science, 2022

This paper proposes a comparison of three machine learning algorithms for a better intelligent ir... more This paper proposes a comparison of three machine learning algorithms for a better intelligent irrigation system based on internet of things (IoT) for differents products. This work's major contribution is to specify the most accurate algorithm among the three machine learning algorithms (k-nearest neighbors (KNN), support vector machine (SVM), artificial neural network (ANN)). This is achieved by collecting irrigation data of a specific products and split it into training data and test data then compare the accuracy of the three algorithms. To evaluate the performance of our algorithm we built a system of IoT devices. The temperature and humidity sensors are installed in the field interact with the Arduino microcontroller. The Arduino is connected to Raspberry Pi3, which holds the machine learning algorithm. It turned out to be ANN algorithm is the most accurate for such system of irrigation. The ANN algorithm is the best choice for an intelligent system to minimize water loss ...

Indonesian Journal of Electrical Engineering and Computer Science, 2021

The human resources (HR) manager needs effective tools to be able to move away from traditional r... more The human resources (HR) manager needs effective tools to be able to move away from traditional recruitment processes to make the good decision to select the good candidates for the good posts. To do this, we deliver an intelligent recruitment decision-making method for HR, incorporating a recruitment model based on the multipack model known as the NP-hard model. The system, which is a decision support tool, often integrates a genetic approach that operates alternately in parallel and sequentially. This approach will provide the best recruiting solution to allow HR managers to make the right decision to ensure the best possible compatibility with the desired objectives. Operationally, this system can also predict the altered choice of parallel genetic algorithm (PGA) or sequential genetic algorithm (SeqGA) depending on the size of the instance and constraints of the recruiting posts to produce the quality solution in a reduced CPU time for recruiting decision-making. The results obt...

2016 2nd International Conference on Cloud Computing Technologies and Applications (CloudTech), 2016

Amazon Ec2 service offers two diverse instance purchasing options. Users can either run instances... more Amazon Ec2 service offers two diverse instance purchasing options. Users can either run instances by using on-demand plan and pay only for the incurred instance-hours, or by renting instances for a long period, while taking advantage of significant reductions (up to 60%). One of the major problems facing these users is cost management. How to dynamically combine between these two options, to serve sporadic workload, without knowledge of future demands? Many strategies in the literature, require either using exact historic workload as a reference or relying on long-term predictions of future workload. Unlike existing works we propose two practical online deterministic algorithms for the multi-slope case, that incur no more than 1+1/1−α and 2/1−α respectively, compared to the cost obtained from an optimal offline algorithm, where α is the maximum saving ratio of a reserved instance offer over on-demand plan.

Abstract----In this paper, we present a mobile implementation of a strategy of communication betw... more Abstract----In this paper, we present a mobile implementation of a strategy of communication between agents in a distributed environment. This strategy is used by the  AD-calculus witch is an elementary functional distributed agent language (1). It's based on a static analysis which allows determining the parts of a message that must be transmitted. The agents we consider have a functional script and manipulate the terms of the  AD-calculus. The expressions of this language correspond to those of the -calculus extent by some agent primitives. The mobile implementation of communication strategy witch we present in this paper is based on mobile agents. In the distributed agent system, each host has its mobile agent witch can migrate to the other hosts with the parts of messages, that must be transmitted outside. Mobile agent migrates to the hosts which have a lot of interactions with his host. In the case of the low interactions, this approach become less efficient, it's pe...

We present a new strategy of messages communication in a Multi Agent Distributed Data Mining. Thi... more We present a new strategy of messages communication in a Multi Agent Distributed Data Mining. This strategy is based on static analysis and mobile agent. The static analysis compiles all messages “send(A,m) to send(A,m,L), where L is the necessary portion of message which will be sent to distant site. In the case where the number of messages “send(A,m,L)” is important, a mobile agent migrates to this site in order to accomplish all tasks locally, thus the send(A,m,L) will not be executed and their cost will be minimized. The agents we consider manipulate data who's structure corresponds to a tree. They also integrates a pattern-matching mechanism in order to recognize the messages. The agent behavior is an expression of the lAGD -calculus [1], extended by the primitives to create an agent, to send a message, to change behavior and those for the pattern matching and the construction of the terms.

Work, 2020

BACKGROUND: To combat COVID-19, curb the pandemic, and manage containment, governments around the... more BACKGROUND: To combat COVID-19, curb the pandemic, and manage containment, governments around the world are turning to data collection and population monitoring for analysis and prediction. The massive data generated through the use of big data and artificial intelligence can play an important role in addressing this unprecedented global health and economic crisis. OBJECTIVES: The objective of this work is to develop an expert system that combines several solutions to combat COVID-19. The main solution is based on a new developed software called General Guide (GG) application. This expert system allows us to explore, monitor, forecast, and optimize the data collected in order to take an efficient decision to ensure the safety of citizens, forecast, and slow down the spread’s rate of COVID-19. It will also facilitate countries’ interventions and optimize resources. Moreover, other solutions can be integrated into this expert system, such as the automatic vehicle and passenger sanitiz...

Proceedings on Engineering Sciences, 2021

Networking, Intelligent Systems and Security, 2021

International Journal of Advanced Computer Science and Applications, 2021

This paper aims to solve the problem of sampling and collecting blood and/ or urine tubes from si... more This paper aims to solve the problem of sampling and collecting blood and/ or urine tubes from sick people at home via a medical staff (nurse/ caregiver) to the laboratory in an optimal way. To ensure good management, several constraints must be taken into account, namely, staff schedules, patient preferences, the maximum delay time for a blood sample, etc. This problem is considered as a vehicle routing problem with time windows, preference and priority according to urgent cases. We first proposed a mathematical formulation of the problem by using a mixed integer linear programming (MILP) as well as various metaheuristics. Also, we applied this method to a real instance of a laboratory in Morocco (Témara) named Laboratory BioGuich, which gave the most optimal results.

E3S Web of Conferences, 2021

Nowadays, the international society began to see clearly the impact of neglecting the environment... more Nowadays, the international society began to see clearly the impact of neglecting the environmental aspect in our lives, especially the issue of global warming. This paper aims in the first degree to minimize the carbon emission by vehicles and in doing so help to reduce the pollution ratio that is increasing day by day. In the home care sector, a patient requires from a health structure offering home care services one or many services to be done at home. For this purpose a health staff is mobilized to provide these services and must be done optimally. Many papers dealing with this kind of problems are suggesting that the way to optimize the problem encountered efficiently is to use the resources put in place to minimize the total travelled distance, but in this perspective, the study prioritizes the reduction and minimizing the fuel consumption. To answer all this questions, an exploration and an investigation of the problems addressed in the literature is performed, after that a m...

International Journal of Open Problems in Computer Science and Mathematics, 2016

The asymmetric traveling salesman problem (ATSP) is a combinatorial problem of great importance w... more The asymmetric traveling salesman problem (ATSP) is a combinatorial problem of great importance where the cost matrix is not symmetric, which complicates its resolution. The genetic algorithms (GAs) are a meta-heuristics methods used to solve transportation problems that have proved their effectiveness to obtain good results. However, improvements can be made by adapting the crossover operator as a primordial operator in GAs. In this work, we propose an adapted XIM crossover operator for the ATSP in order to improve the optimal solution obtained by GAs. Numerical simulations are performed and discussed for different series of standard instances showing the improvement of the optimal solution by the proposed genetic operator.

JOURNAL OF ADVANCES IN NATURAL SCIENCES, 2018

The Internet of things appears as a solution in order to connect people around the world. With th... more The Internet of things appears as a solution in order to connect people around the world. With this concept of interconnection, sharing and dissemination of information between different physical objects. Many objects and services in different fields will be created, such as smart homes, e-health, transport and logistics that will make our everyday needs easier. The main characteristic of a connected object is that it must be identifiable, using technologies such as RFID (Radio-Frequency Identification), must interact with the environment by adding sensory techniques, and finally a connected object must be able to communicate with others. The evolution of Internet of things, increase the number of connected objects. Devices with sensors, generate a huge number of data. With this evolution, the big questions come! how can we control this big data? Cloud Computing a notion that is not newer than the IoT concept, but it's a revolution has steadily been gaining ground. It's a te...

International Journal of Electrical and Computer Engineering (IJECE), 2016

This paper presents an effective approach to optimize the reassignment of Human Resources in the ... more This paper presents an effective approach to optimize the reassignment of Human Resources in the enterprise that is formed by several units of productions to take into consideration the human characteristics. This approach consists of two steps; the first step is to formalize the studied problem that is practically take the form of the generalized assignment problem (GAP) known as NP-hard problem. Additionally, the variables in the formulation of our problem are interlinked by certain constraints. These two proprieties can to justify the important complexity of this problem. The second step is focused to solve this complex problem by using the genetic algorithm. We present the experimentally result for justifying the validity of the proposed approach. So, the solution obtained allowed us to get an optimal assignment of personnel that can lead to improve the average productivity or ratability or at least ensure its equilibration within sites of enterprise.