Extending evolutionary multi-objective optimization of business process designs

Διπλωματική εργασία--Πανεπιστήμιο Μακεδονίας, Θεσσαλονίκη, 2019.Optimizing a problem to produce a set of improved solutions is not a new concept. Many scientific areas have been benefited by the application of optimizations techniques and so have business processes. The competitive business environments have led organizations into examining and re-designing their core business processes, aiming for improving their performance and market responsiveness. The optimization and the continuous improvement of business processes within a company, can give the advantage to the company to be more competitive by reducing its costs, improving the delivery quality and efficiency, and enabling adaptation to changing environments. This thesis focuses on business process multi-objective optimization with evolutionary algorithms. There have already been optimization approaches with evolutionary algorithms for business process optimization problems that demonstrated rather satisfactory results. This thesis aims to improve and extent those approaches by providing a revised and refined version of an existing business process optimization framework by Vergidis (2008), that incorporates a pre-processing technique for enhancing the efficiency of the employed Evolutionary Multi-objective Optimization Algorithms (EMOAs), a new process composition algorithm that make the new framework capable of fulfilling more real-life constraints and handling more complex problems and many other features such as ease of use, more efficient I/O, better interactivity and easy maintenance. The proposed pre-processing technique was tested as a standalone procedure and demonstrated satisfactory results, managing to reduce drastically the problem dataset of all scenarios examined. The results of the whole optimization framework for the real-life scenarios examined, were very promising and indicated that the framework work as expected. It can automate the process composition and identify alternative business process designs with optimized attribute values

Βελτιστοποίηση επιχειρησιακών διαδικασιών βασισμένη σε προγραμματισμό περιορισμών

Διπλωματική εργασία--Πανεπιστήμιο Μακεδονίας, Θεσσαλονίκη, 2019.During the last two decades a change occurred in the dialectics of Business Administration science about the principles that should rule the organizational structure of a company. A structural model based on business processes that run through the business entity horizontally and/or vertically, is gradually replacing the traditional strategy that stratifies the functional entity in distinct and isolated hierarchical levels. A business process can be defined as a set of coordinated activities aiming at the successful realization of a business goal and the production of surplus value. Therefore, the design and the implementation of a process can significantly affect the efficiency of an organization's operation and the quality that the consumer receives from the produced outcome. The significance of planning and managing the business processes for the survival of a company in the modern globalized economic environment, demonstrates the need for the development of computational systems that can assist the effort for the improvement or re-engineering of processes in regard to quantitative and qualitative criteria. Considering that the constraint logic programming can offer the computational means for the confrontation of complex combinatorial problems, the aim of this thesis is to design and develop a system that can compose optimized complex business processes from simple tasks based on predefined evaluation criteria. The proposed system is consisted by four collaborating software modules. The database that stores the simple tasks in the appropriate quantitative representation for the optimization procedure. The graphical user interface (GUI) that accepts the required input by the decision maker and creates the constraint logic program using the programming language Prolog. The ECLiPSe platform executes the logic program to determine the feasible processes for specific input and output resource data sets, and construct the processes with the optimum evaluation. Finally, the visualization subsystem translates the quantitative representation of the optimized business processes into a graphical form