Almir Karabegovic

Fuzzy Logic and Genetic Algorithm Application for Multi Criteria Land Valorization in Spatial Planning

This chapter investigates the possibility of multicriterial land valorization in land use planning by the application of genetic algorithm and fuzzy logic. One of the key tools for the design of the decision support system based on this methodology is a geographic information system which serves to quantify multicriterial data and presents resulting spatial data. The methodology and the algorithm are applied to a specific problem of the spatial planning in Tuzla Canton, Bosnia and Herzegovina. In spatial multi criteria analyses, geographic information systems are used to identify alternatives, present them and give information to decision makers for evaluation, comparison and ordering of the alternatives. The limitations of multi criteria analyses in the standard GIS are necessity in defining of all the steps in advance and inability to simple change the criteria or thresholds later. Fuzzy set methodologies and GA optimization could be excellent for designing efficient tools to support the spatial decision making process. This works analizes the incorporation of these methodologies into a DBMS repository for the application domain of GIS [6]. It is shown how the useful concepts of fuzzy set theory and GA may be adopted for the representation and analysis of geographic data, whose uncertainty is an inherent characteristic.

Web portals for visualizing and searching spatial data

Spatial data have proven to be extremely useful in many areas. Accordingly, there are more and more Web GIS solutions. These solutions allow the visualization of spatial data to all Internet users. A large number of available online resource introduced the problem of efficient retrieval of relevant information. The aim of this paper is to describe the way in which Web portals can be used to search and presentation of spatial data. The paper first analyzes the area of the Web portal. It provides an overview of the Web GIS technology, with particular emphasis in its advantages and disadvantages and how the client/server architecture can be applied to Web GIS solutions. Then, it describes how the service oriented architecture can be used to resolve interoperability problems, and gives an overview of OGC standards: WMS, WFS, and WCS. In the end, it explains the need for introducing a geoportal, as a special type of a Web portal. In the practical part of this paper is implemented interactive map of Bosnia and Herzegovina. An overview of the technologies was given: PostGIS, Boundless SDK, GeoServer and OpenLayers, which are an integral part of the OpenGeo Suite. The paper also describes how to integrate local data sources with public web services: MapQuest, Bing Maps and OpenStreetMap.

Geoportal as Interface for Data Warehouse and Business Intelligence Information System

There is increasing interest of organization for advanced presentation and data analysis for public users. This paper shows how to integrate data from enterprise data warehouse with spatial data warehouse, publish them together to online interactive map, and enable public users to perform analysis in simple web interface. As case study is used Business Intelligence System for Investors, where data comes from different sources, different levels, structured and unstructured. This approach has three phases: creating spatial data warehouse, implementing ETL (extract, transform and load) procedure for data from different sources (spatial and non-spatial) and, finally, designing interface for performing data analysis. The fact, that this is a public site, where users are not known in advanced and not trained, calls for importance of usability design and self-evident interface. Investors are not willing to invest any time in learning the basics of a system. Geographic information providers need geoportals to enable access to spatial data and services via the Internet; and it is a first step in creating Spatial Data Infrastructure (SDI).

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.

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.

Spatial Component in Business Intelligence System for Advanced Threat and Risk Analysis

This paper shows an innovative approach for implementation business intelligence systems in advanced threat and risk analysis using spatial component. It demonstrates how to improve intelligence of complete information system by involving spatial extension. Most of business data in data warehouses are often spatial per se, and without using this component, analysis missing very important dimension of the data nature. From other side, frequent problem in enterprise data warehouse is creating relations between tables which come from different sources and without any common attributes; that could be very easily solved by spatial relations. This paradigm of spatialization assumes changing overall system architecture, from data storage, via retrieving to its presentation mechanism. Particular benefit of this approach for threat and risk analysis is effective utilization of location data, advanced spatial analysis techniques and more variety in data visualization. Examples of organizations which need such system are intelligence agencies, emergence services or epidemiology centers.