Almir Djedovic

Bio: Almir Djedovic is an academic researcher from University of Sarajevo. The author has contributed to research in topics: Business process & Process mining. The author has an hindex of 5, co-authored 15 publications receiving 64 citations.

Design of optimization system for warehouse order picking in real environment

Abstract: Warehouse Management Systems (WMS) play a major role in optimizing warehouse logistic processes, archiving merchant trends of supply and demand, and also easen treating of goods which are close to expiring deadline, out of stock, broken or deposited by customers. Since warehouse management systems may be integrated with business intelligence, they may comprise algorithms for optimization of warehouse order picking and storing of goods, sales prediction etc. In this article case study of warehouse management system is presented, and afterwards problem of optimal warehouse order picking is exhibited. This problem is transformed into Travelling Salesman Problem (TSP), and solved using heuristic optimization methods.

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

Abstract: Business process management is the process of modifying or adjusting an organization's 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.

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

Abstract: 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.

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

Abstract: 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.

Model business process improvement by statistical analysis of the users' conduct in the process

Abstract: Process Mining is a research area that meets the gap between business processes and various IT systems. Most of the works in this area focus on the control flow perspective, while very few of them address the organizational aspect. The organization perspective of process mining supports the discovery of social network within organization by analyzing events logs recorded during real process execution. For process owners, it is very important to know how users perform their activities in process. In this paper, we introduce a process discovery method that combines an organizational perspective with probabilistic approach. Combining these two approaches we are able to fit distribution of users work and distribution of instance generation in process. We use different statistic methods like Cullen and Frey graph, Kolmogorov-Smirnov statistic test, Carmen-von-Mises statistic test and Anderson-Darling statistic test. After finding appropriate distribution we estimate its parameters. Research conducted and presented in this paper reveals that the information about users behaviour in process is significantly useful in further analysis: in simulations, to identify bottlenecks, to improve productivity of resource management and to identify task complexity in process.

e‐Learning and the Science of Instruction

Abstract: Practice is a necessary but not sufficient condition to reach high levels of competence. Deliberate practice, which includes five basic elements, is needed to build expertise. Those elements include: 1. Effortful exertion to improve performance 2. Intrinsic motivation to engage in the task 3. Carefully tailored practice tasks that focus on areas of weakness 4. Feedback that provides knowledge of results, and 5. Continued repetition over a number of years (p. 256)

Business Process Management: A Survey

Abstract: Business Process Management (BPM) includes methods, techniques, and tools to support the design, enactment, management, and analysis of operational business processes. It can be considered as an extension of classical Workflow Management (WFM) systems and approaches. Although the practical relevance of BPM is undisputed, a clear definition of BPM and related acronyms such as BAM, BPA, and STP are missing. Moreover, a clear scientific foundation is missing. In this paper, we try to demystify the acronyms in this domain, describe the state-of-the-art technology, and argue that BPM could benefit from formal methods/languages (cf. Petri nets, process algebras, etc.).

Replaying history on process models for conformance checking and performance analysis

Abstract: Process mining techniques use event data to discover process models, to check the conformance of prede?ned process models, and to extend such models with information about bottlenecks, decisions, and resource usage. These techniques are driven by observed events rather than hand-made models. Event logs are used to learn and enrich process models. By replaying history on the model, it is possible to establish a precise relationship between events and model elements. This relationship can be used to check conformance and to analyze performance. For example, it is possible to diagnose deviations from the modeled behavior. The severity of each deviation can be quanti?ed. Moreover, the relationship established during replay and the timestamps in the event log can be combined to show bottlenecks. These examples illustrate the importance of maintaining a proper alignment between event log and process model. Therefore, we elaborate on the realization of such alignments and their application to conformance checking and performance analysis.

Smart Warehouse Management System Concept with Implementation

Abstract: Distribution companies use complex software systems called WMS (Warehouse Management System). The WMS is an important part of the company’s business and it can make processes simple to keep track of. Smart WMS optimizes processes to save resources and to create a more efficient working place. This paper describes the concept of a smart WMS that is implemented in one of the largest distribution companies in Bosnia and Herzegovina. The system uses artificial intelligence and optimization algorithms to improve working process. The paper describes the complete warehouse workflow that includes stock planning, initial product placement, transfer from stock to pick zone, order picking process, transport and tracking. The anomaly detection is used in some processes to improve the whole system. The main contribution of this paper is the presentation of an efficient and in the real world used smart WMS concept.