Almir Djedovic

Software solution for optimal planning of sales persons work based on Depth-First Search and Breadth-First Search algorithms

This paper presents and describes the practical usage of Depth-First Search and Breadth-First Search algorithms in the planning and optimization of sales persons work. Experiments for optimal implementation of these two algorithms for planning purposes are made through a specially developed MATLAB simulator. The application consists of two parts: Web application and Mobile application. Web application is developed using the Application Development Framework Technology (ADF), while for the development of the mobile version of application, Oracle ADF Mobile is used. Both applications are interactive with Google Maps, and based on the selected input parameters (such as the origin and destination of sales persons, the way of planning, any possible obstacles, etc.) they visually show the results, indicators and analysis. The commercial version of the software, eSalesmanPlan, which uses the aforementioned algorithms, is used in several companies in Bosnia and Herzegovina. All indicators point to significant savings both in human as well as financial resources and it will be also presented.

Practical Transport Optimization Method and Concept in Pharmaceutical Industry

The application of computer skills and technologies in modern business is essential in modern society, therefore different methods and algorithms are used for the business optimization. This paper primarily focuses on solving the transportation problem of the linear programming for the purpose of the transport optimization, which ultimately leads to the competitive advantage for any institution which performs any type of transport as a part of its business. Therefore, specially implemented Java program for the purposes of pharmaceutical institutions will be presented. The need to optimize the product transport from the producer to the consumer is of a great importance for any company, including pharmaceutical one. The aim for solving the transportation problem is the application of algorithms over real data from the appropriate database of the merchandise management in order to optimize the transport of medicines and other pharmaceutical products from the factory to pharmacies or other institutions.

Optimization of business processes by automatic reallocation of resources using the genetic algorithm

Business process management is the process of modifying or adjusting an organizations business process in order to achieve higher productivity or lower costs. Each company or organization has a value creating process that usually involves people, machines and information. One of the main problems with such processes is that it is very difficult to predict how much of each resource is actually needed. In light of the above, the objective of this paper is to implement a methodology that is capable of optimizing the allocation of resources to tasks in a given business process. In this paper, the genetic algorithm was used for optimization. The idea is that once the units are properly presented, the optimal schedule of users should be determined using the genetic algorithm. The fitness function includes Key Performance Indicators of process: waiting time and cost of the resource. Since al the users are not qualified in performing all the tasks in the process, the algorithm has to consider minimal and the maximal available number of users for each activity. The usability of this approach is tested in the process of credit requirement. Finally, the results are compared to the current work process.

Innovative Approach in Modeling Business Processes with a Focus on Improving the Allocation of Human Resources

Organizations can improve efficiency of process execution through a correct resource allocation, as well as increase income, improve client satisfaction, and so on. This work presents a novel approach for solving problems of resource allocation in business processes which combines process mining, statistical techniques, and metaheuristic algorithms for optimization. In order to get more reliable results of the simulation, in this paper, we use process mining analysis and statistical techniques for building a simulation model. For finding optimal human resource allocation in business processes, we use the improved differential evolution algorithm with population adaptation. Because of the use of a stochastic simulation model, noise appears in the output of the model. The differential evolution algorithm is modified in order to include uncertainty in the fitness function. In the end, validation of the model was done on three different data sets in order to demonstrate the generality of the approach, and the comparison with the standard approach from the literature was done. The results have shown that this novel approach gives solutions which are better than the existing model from literature.

Cluster-based analysis and time-series prediction model for reducing the number of traffic accidents

Traffic is a complex system, in terms of functioning as well as organization. Traffic stop, i.e. failure to perform the required transport function from point A into point B, can be caused by variety of circumstances, and one of them is the occurrence of traffic accident. Therefore, it is of a great importance to pay attention to increasing the traffic safety level throughout the implementation of various measures. Traffic safety is one of the most important links of the traffic system. This paper analyzes in details the impact of the road and its environment, vehicles and drivers on traffic accidents. The model of classification of traffic accidents causes has been implemented on the basis of similarities of drivers, vehicles and road characteristics. k-means clustering algorithm has been used for this purpose. According to data available, time-series prediction model has been implemented in the second part of the work, for prediction of traffic accidents in analyzes regions. Results in both implemented cases are more than satisfactory.

Impact of human resources changes on performance and productivity of Scrum teams

This paper presents results of an analysis of the impact of the human resources changes in Scrum teams. Four Scrum teams were tracked (two developments and two quality assurance) along with their productivity and performance. Analysis showed that human resources changes have a significant impact on the entire team and its behavior. Their effort increased by adding overtime hours. In the same time, their performance and effective work decreased, which is reflected on the quantity of work that can be billed to the client. The analysis shows that it takes, in average, three sprints (each lasting fourteen days) for new team members to fully adjust to the team development process and acquire a business knowledge needed for maximum productivity. Teams whose members have been working together longer period and who have more senior members can adjust to team shifts more quickly. The analysis also showed a correlation between quality assurance and development team - when development team had extra utilization due to overtime, quality assurance team had an increase in overtime hours almost proportionately.

Decission support system for candidates classification in the employment process based on ANFIS method

The aim of this work is to create a decision support system based on Adaptive Neuro-Fuzzy Inference System (ANFIS), which will be used for objective classification of employees in the employment process by analyzing available information about the candidates. Information about the candidates is extracted from the relevant documents on one company during the advertising for job in Information Technology (IT) sector. Filtration and normalization of the data were performed after they had been acquired, the decision support system being realized was implemented in the form of hybrid model, made of fuzzy logic synthesis and neural network, as well as presented by acronym ANFIS. The initial ANFIS system is divided into two subsystems as the result of complexity of the very problem, as well as of more attributes. By training and testing (checking) the obtained Fuzzy Inference System (FIS) structures, the one with the lowest error is chosen. The operation of the network has been demonstrated by the valuable simulation model. The successful validation of the resulting system has been made by validation data.

Application of Big Data and text mining methods and technologies in modern business analyzing social networks data about traffic tracking

Big Data is becoming one of the most important technology trends with a potential for a dramatic change in which organizations use information in order to improve the customers experience and transform their own business models. Big Data as a concept is new in the world of technology and therefore requires research in technological or business sense. Management and analysis of large amount of network offer huge benefits and challenges for all organizations. The amount of information floating through social networks increases every day, and represents a rich source of data, if it is properly processed. The aim of this paper is to show on a concrete example the profit of the system implemented over Big Data from social networks using Text Mining methods and technologies, as well as semantic processing and clustering, storaging and possibility of later examination and treatment.

Successful e-learning concepts and platform in the field of biomedical engineers education

The aim of this paper is to promote and demonstrate the usage and successful practical application of e-learning achievements in the field of biomedical engineering education (BME). Biomedical engineers and bioengineers require significant knowledge of both, engineering and biology. Both, biomedical engineering and BME education in Bosnia and Herzegovina are on an extremely low development level. Therefore, it is important to create a system used by both students and professors, which would increase the level of awareness in this field. During the implementation of this system, the best development practices of web-based systems of wide usage were used. The results of required knowledge in the field of BME, based on real data of the usage of this system, have also been demonstrated.

Optimization of the Business Processes via automatic integration with the Document Management System

In todays global business environment, the importance of customer service, cost-competitiveness, and quality are key factors in determining an organizations success, or undesirable failure. Organizations try to optimize their processes to maximize their profits and make the very process faster. Users usually work with documents in the process. Working with documents makes the process more slowly, since the documents are important to be scanned and attached to the form. This work presents the optimization of such processes. It is achieved by automatic integration of Business Process Management and Electronic Document Management Systems. Improvements and results achieved by proposed integration are presented in this research. The model that is created enables monitoring of defined Key Performance Indicators in the identification process of the bottlenecks in the process. The process can be optimized by increasing the number of resources on the activities that are a bottleneck in the process. Such a solution has been tested in the process of opening a bank account.