ALLAOUA Hemmak

Bouamar Aya and , hemmiche ismahan

Vehicle rental platform for transporting goods

BENNOUIOUA Amal , FADLI Hana

Implémentation d’une supérette électronique avec optimisation de la chaine d’approvisionnement

Demane Dounia , Khezzari Hadil

Algorithme génétique pour le problème d'équilibrage de chaîne de montage

MIHOUBI HADIL , SAOUDI RACHA

CALORIE BURN PREDICTION

Boukabouya Noudjoud , Chebih Souhila

Système de prévention des incendies basée sur la classification des établissements pour la protection civile algérienne

BENHADDAD Hind , BELABBAS Manar

Algorithme génétique parallèle pour l’ordonnancement flow shop

BENNAOUI BOUCHRA , MANNED MAROUA

Machine Learning approach for single machine scheduling problems

kadri yassamine

Modélisation de l’évolution urbaine par automate cellulaire Cas d’application : ville de M’sila

LADJEDEL ASMA , GHACHA YASSMINE

GENETIC PROGRAMMING FOR INTELLIGENT BEHAVIOR OF A VIRTUAL ROBOT IN A RANDOM ENVIRONMENT

Souhil Larbi BOULANOUAR

New Hybrid Method for Segmentation of MRI Medical Images

GOUBI Khedidja , GUETTOUCHE Chames Elassil, LAMDJED Douaa

CONCEPTION ET IMPLEMENTATION D’UN SITE WEB POUR LA GESTION DES RESERVATIONS D’HOTELS

ALILI Zohir , NECHE Samir

Méthode OCA pour le PVC appliqué au réseau routier algérien

Benazi Makhlouf

Analyse des réseaux complexes : Application à la détection de communautés dans les réseaux sociaux

BENDAKMOUSSE Faiza

Algorithme génétique pour la régression du front Pareto en optimisation multicritères

Aicha Badza , Khadidja Logsier, Nour Elhouda Messaoudi

Implémentation d’un portail web pour une revue scientifique spécialisée en informatique

بوفسيو عفاف , بغدادي لينا, بن بودينة سارة

تصميم موقع الكتروني لتسيير طلبيات الزبون - مؤسسة وهج للإعلام والثقافة والفنون -

Benzaoui Aya , Demaine Dounia, Khezzari Hadil

Site web pour assurance auto en ligne

ZOHRA DELLOUM , KADDOUR DJAKAM, SOULAF MEDJENAH

APPLICATION ANDROID POUR LE SUIVI DU DIABÈTE

Hamiche Ismahan , Ziouche Faiza, Letaissa Nor Elhouda

Développement d'un site web de gestion des RDV pour consultation médicale

Seghiour Nour El Houda , Benzia Abir Ikram, Maouche Diaa Eddine

SITE WEB POUR L’ARCHIVE DE PFEs Cas : faculté de mathématiques et informatique

Benazi Makhlouf

Analyse des réseaux complexes : Application à la détection de communautés dans les réseaux sociaux

Bouyebba Mohammed Et-Tahire

Ordonnancement des Commandes Client, Simulation par PSO

CHAANBI BOUTHAINA

Forecasting Tool for Optimizing the Supply Chain

DAHMANE Khawla , SILINI Loubna

Stochastic Routing Algorithm for Ad-Hoc Networks

DAHMANE Lamia , HADROUG Selma

Algorithmes génétiques pour un problème d’ordonnancement d’atelier Job Shop

guechi salah

algorithme quantique pour le probleme sat

arar hanane

Méthode du seuil d'acceptation appliqué au problème de coloration de graphes

kouici rokaya

hubridation relais d'algorithmes génétiques pour le probleme SAD simple

safer khadidja

Descente multi voisinage pour le problème du sac-à-dos

bouchareb sara

Sieve Optimization Method a Survey and Applications

hassani khawla

Impact du scaling et du sharing sur l'efficacité des AGs

radjai khadidja

Classification ascendante hierarchique pour la detection d'intrusions

meratete soumia

Etude comparatives des protocoles de routage dans les réseaux ad-hoc

djennaoui abdellatif

Android system for solving islamic inheritance problems

Benlaiter Djamel Eddine , Aissi Nadia, Ferahtia Abla

Développement d'un système de transport intelligent par géolocalisation

dilmi fatima zohra , Heraiz Fatma, Khennouf Dalal

site web dynamique pour la gestion des TFEs

Baguira Asma , Melki Zakia

Site web dynamique pour la gestion des notes

Abdellaoui Oussama , Laifa Abdelhadi, Bencharif Youcef

Conception Et Realisation D'une Application Android Pour Le Suivi Du Diabète

benaissa adel

Etdue et simulation du routage inter VLANs

hasnaoui djamel eddine

Simulation d'un wlan multimédia utilisant le spread spectrum

madjidi rochdi

Conception d'un LAN multimédia sur CPL

MERATATE Soumia

Les protocoles de routage dans les reseaux mobiles ad-hoc

chemini mimi

Android application for calendar

derri asma

Dynamic web site for weather

derri asma

Dynamic web site for weather

SEMATI HICHAM

Algorithme optimal pour la gestion du cache d'un serveur web

Guelmine Abdelkamel

Conception et réalisation d'un site web dynamique pour la gestion de la scolarité

berroubi aicha

Parallélisation de B&B pour le PVC

gherabi samiha

Algorithme génétique appliqué au PVC avec dates échues

ouled djaballah youcef

simulation and implementation of routing algorithm

alili mourad

Mise au point d'un système de cryptage

rouissat messaouda

Mise au point d'un robot d'indexage web

benyounes nadjet , zaiter leila

Intégration et paramétrage d'un OpenERP au Moulins Hodna M'sila

bouslah wafa , Zawak Baya

Système de recherche documentaire pour la bibliothèque universitaire

Benamra Warda , guelmine amel, guelmine salim

Conception et implémentation d'un système de gestion de stock ERIAD M'sila

ghozi amel , kerkeb mayada

Mise au point d'un système informatique pour le payement électronique, SONELGAZ M'sila

Benadel Oussama , Bey Abdelali

Conception et implémentation d'un site web dynamique pour les examens et mémoires, département d'informatique M'sila

Djeddi Samir

Site web dynamique pour la facturation ACTEL

1) Azouz Hayat , 1)Marouf Imane

Conception et réalisation d'un SIH: CH Zahraoui M'sila

In this paper, we propose a new linear algorithm to tackle a specific class of unrelated machine scheduling problem, considered as an important real-life situation, which we called Batch Scheduling on Unrelated Machine (BSUM), where we have to schedule a batch of identical and non-preemptive jobs on unrelated parallel machines. The objective is to minimize the makespan (Cmax) of the whole schedule. For this, a mathematical formulation is made and a lower bound is computed based on the potential properties of the problem in order to reduce the search space size and thus accelerate the algorithm. Another property is also deducted to design our algorithm that solves this problem. The latter is considered as a particular case of RmCmax family problems known as strongly NP-hard, therefore, a polynomial reduction should realize a significant efficiency to treat them. As we will show, Batch BSUM is omnipresent in several kind of applications as manufacturing, transportation, logistic and routing. It is of major importance in several company activities. The problem complexity and the optimality of the algorithm are reported, proven and discussed.

Citation

ALLAOUA Hemmak , , (2023-07-01), Exact Algorithm for Batch Scheduling on Unrelated Machine, The International Arab Journal of Information Technology (IAJIT), Vol:20, Issue:4, pages:618-623, Zarqa University, Jordan

Despite the efforts of the World Health Organization, blood transfusions and delivery are still the crucial challenges in blood supply chain management, especially when there is a high demand and not enough blood inventory. Consequently, reducing uncertainty in blood demand, waste, and shortages has become a primary goal. In this paper, we propose a smart platform-oriented approach that will create a robust blood demand and supply chain able to achieve the goals of reducing uncertainty in blood demand by forecasting blood collection/demand, and reducing blood wastage and shortage by balancing blood collection and distribution based on an effective blood inventory management. We use machine learning and time series forecasting models to develop an AI/ML decision support system. It is an effective tool with three main modules that directly and indirectly impact all phases of the blood supply chain: (i) the blood demand forecasting module is designed to forecast blood demand; (ii) blood donor classification helps predict daily unbooked donors thereby enhancing the ability to control the volume of blood collected based on the results of blood demand forecasting; and (iii) scheduling blood donation appointments according to the expected number and type of blood donations, thus improving the quantity of blood by reducing the number of canceled appointments, and indirectly improving the quality and quantity of blood supply by decreasing the number of unqualified donors, thereby reducing the amount of invalid blood after and before preparation. As a result of the system’s improvements, blood shortages and waste can be reduced. The proposed solution provides robust and accurate predictions and identifies important clinical predictors for blood demand forecasting. Compared with the past year’s historical data, our integrated proposed system increased collected blood volume by 11%, decreased inventory wastage by 20%, and had a low incidence of shortages.

Citation

WALID BEN ELMIR , ALLAOUA Hemmak , Benaoumeur Senouci, , (2023), Smart Platform for Data Blood Bank Management: Forecasting Demand in Blood Supply Chain Using Machine Learning, Information, Vol:14, Issue:1, pages:31, MDPI

The blood management system confronts a challenge with blood transfusions and their distribution regardless of the efforts of the World Health Organization and other global health organizations: inadequate supply, excessive demand, and a shortage of accessible blood. Due to its ability to raise labor efficiency and service quality via systematic management, artificial intelligence is currently necessary to enhance blood supply operations. The objective of this work is to provide an AI/ML platform that facilitates the use of data to assist health professionals in making the most effective management choices that are consistent with methods for minimizing waste and costs. By more accurately anticipating blood demand. As production models, we are using both time series and machine learning methods as prediction models. The optimal performance model for the provided case study was determined by comparing the performance outcomes of each method. In this work, autoregressive Moving Average models, autoregressive Integrated Moving Average models, and seasonal ARIMA models are applied. In addition, we used four native algorithms for machine learning: Artificial Neural Networks, Linear Regression, and Support Vector Regression. The results demonstrate that both types of forecasting models can significantly enhance the management of the blood supply.

Citation

WALID BEN ELMIR , ALLAOUA Hemmak , Benaoumeur Senouci, ,(2023), Smart platform for Blood Management in Healthcare using AI/ML Approach,International Conference on Artificial Intelligence in Information and Communication (ICAIIC),Bali, Indonesia

Information and computer technology are gaining popularity in blood banks because of their potential to enhance labor productivity and service quality. This article focuses on the significance of web-based technologies in blood bank information management in order to improve the efficacy of this vital, particularly challenging activity in developing nations. Despite the efforts of the World Health Organization and others, blood transfusions and their delivery pose a problem in developing countries: insufficient supply, high demand, and inadequate availability. The research revealed that blood banking institutions in developing countries lacked coordination, as each blood bank maintained its own records that were not shared with other banks. The objective of this paper is to propose a solution that: (1) facilitates coordination between blood banks, health institutions, and donors by interacting with a central database. (2) Providing a solution to one of the most important issues of blood bank information systems, namely, how to effectively use the growing amount of data and information to aid in decisionmaking. (3) Proposes a decision support system for blood supply management that enables the incorporation of human knowledge into an automated system to improve the efficacy of blood bank management; the objective is to assist health administrators in making the best management decisions that are in line with the best strategies.

Citation

WALID BEN ELMIR , ALLAOUA Hemmak , Benaoumeur Senouci, ,(2022), Data Blood Management for Algerian Healthcare System : Smart Platform Oriented Approach,5th International Conference on Embedded Systems in Telecommunications and Instrumentation,Annaba, Algeria

: This paper presents a mathematically enhanced genetic algorithm (MEGA) using the mathematical properties of the single-machine scheduling of multiple jobs with a common due date. The objective of the problem is to minimize the sum of earliness and tardiness penalty costs in order to encourage the completion time of each job as close as possible to the common due date. The importance of the problem is derived from its NP-hardness and its ideal modeling of just-in-time concept. This philosophy becomes very significant in modern manufacturing and service systems, where policy makers emphasize that a job should be completed as close as possible to its due date. That is to avoid inventory costs and loss of customer’s goodwill. Five mathematical properties are identified and integrated into a genetic algorithm search process to avoid premature convergence, reduce computational effort, and produce high-quality solutions. The computational results demonstrate the significant impact of the introduced properties on the efficiency and effectiveness of MEGA and its competitiveness to state-of-the-art approaches.

Citation

ALLAOUA Hemmak , , (2017), New Properties for Solving the Single-Machine Scheduling Problem with Early/Tardy Jobs, JOURNAL OF INTELLIGENT SYSTEMS, Vol:25, Issue:3, pages:10, DE GRUYTER

This paper presents a combination of Genetic Algorithm (GA) with Dynamic Programming (DP) to solve the well-known Travelling Salesman Problem (TSP). In this work, DP is integrated as a GA operator with a certain probability. In specific, at a given GA generation, the individuals are subdivided into a number of equal segments of genes, and the shortest path on each segment is obtained by applying a DP algorithm. Since the computational complexity of the DP is O (k22k), it becomes of O(1) when k is small. Experimental analyses are conducted to investigate the impact and trade-offs among DP probability, segment size and time processing on the solution quality and computational effort. In addition, we will implement a basic GA approach to compare results and show the contribution of combination of combination approach. Experimental results on benchmark instances showed that the combined GA-DP algorithm reduces significantly the computational effort, produces a clearly improved solution quality and avoids early premature convergence of GA.

Citation

ALLAOUA Hemmak , , (2015-01-01), Combination of Genetic Algorithm with Dynamic Programming for Solving TSP, Int. J. Advance Soft Compu. Appl, Vol:9, Issue:2, pages:12, Int. J. Advance Soft Compu. Appl

Modern manufacturing philosophy of just-in-time emphasizes that a job should be completed as close as possible to its due date to avoid inventory cost and loss of customers goodwill. In this paper, the single machine scheduling problem with a common due date, where the objective is to minimize the total earliness and tardiness penalties in the schedule of jobs, is considered. A new genetic algorithm inspired by the philosophy of dynamic programming, where the chromosome and the population lengths are varied from one iteration to another, is proposed.

Citation

ALLAOUA Hemmak , ibrahim hoceine osman, , (2010), Variable Parameters Lengths Genetic Algorithm for Minimizing Earliness-Tardiness Penalties of Single Machine Scheduling With a Common Due Date, Electronic Notes in Discrete Mathematics, Vol:36, Issue:1, pages:471-478, elsevier