RANKING ENTERPRISES IN TERMS OF COMPETENCES INSIDE REGIONAL PRODUCTION NETWORK

Today\u27s economic crisis has led to bankruptcy of many successful, but usually large-sized enterprises. This brought into question the future of large-sized enterprises. However, the only alternative to largesized enterprises (LEs) is networking of small and medium-sized enterprises (SMEs) into Regional Production Networks (RPNet). RPNet is non-hierarchical organizational form in which every SME is autonomous. Hence, every SME of production network is capable and wiling to be part of special cooperation inside network called Virtual Enterprise (VE). For each new product a new virtual enterprise is formed from different SMEs. The question is: which SMEs will be part of new virtual enterprise? If it is possible to evaluate SME\u27s competences, it is also possible to rank SMEs. Ranking of SMEs according to technical, organizational and human competences is multi-criteria decision analysis (MCDA) problem. So, in this paper PROMETHEE method is selected to perform a ranking of SMEs

RANKING ENTERPRISES IN TERMS OF COMPETENCES INSIDE REGIONAL PRODUCTION NETWORK

Today\u27s economic crisis has led to bankruptcy of many successful, but usually large-sized enterprises. This brought into question the future of large-sized enterprises. However, the only alternative to largesized enterprises (LEs) is networking of small and medium-sized enterprises (SMEs) into Regional Production Networks (RPNet). RPNet is non-hierarchical organizational form in which every SME is autonomous. Hence, every SME of production network is capable and wiling to be part of special cooperation inside network called Virtual Enterprise (VE). For each new product a new virtual enterprise is formed from different SMEs. The question is: which SMEs will be part of new virtual enterprise? If it is possible to evaluate SME\u27s competences, it is also possible to rank SMEs. Ranking of SMEs according to technical, organizational and human competences is multi-criteria decision analysis (MCDA) problem. So, in this paper PROMETHEE method is selected to perform a ranking of SMEs

Planning support concept to implementation of sustainable parking development projects in ancient Mediterranean cities

This paper proposes a planning support concept (PSC) to implementation of sustainable parking development projects (SPDP) in ancient Mediterranean cities. It is conceptualized by the logic of decision support systems and a multicriteria analysis approach. The purpose of the concept is to support setting of implementation priorities for subprojects (construction of new and/or improvement of existing parking) within a SPDP. Analysing the existing and a planned state of parking within the city a goal tree is established. Subprojects are defined accordingly. Objectives from the last hierarchy level within the goal tree are used as criteria for assessment of defined subprojects. Representatives of stakeholders provided criteria weights by application of AHP and SAW methods. PROMETHEE II was used for priority ranking and PROMETHEE V ensured a definition of project’s implementation phases. The result of the presented concept is the implementation plan for such projects. The concept is tested on the city of Trogir

Optimization of the selection of competence cells in regional production network

Današnja svjetska gospodarska kriza pokazala je da uspješno poslovanje poduzeća u normalnim ekonomskim uvjetima nije garancija održivosti, tako da je kriza odvela u stečaj mnoga poslovno uspješna poduzeća, a pogotovo velika poduzeća. Ovo je dovelo u pitanje budućnost velikih poduzeća, no u isto vrijeme i otvorilo pitanje postoji li alternativa velikim poduzećima. Alternativa, dakako, postoji u umrežavanju malih i srednjih poduzeća i njihovom optimalnom odabiru u stvaranju novih virtualnih poduzeća. Ovaj se rad bavi baš navedenim problemom odabira kooperanata (kompetencijskih stanica) za određeni novonastali proizvodni proces. Pretpostavlja se da je poduzeća moguće međusobno usporediti i rangirati, što otvara prostor za optimiranje pomoću algoritma Ant Colony Optimization (ACO).The ongoing world economic crisis has shown that being a successful enterprise in normal economic conditions is not a guarantee of sustainability. So the crisis has led to bankruptcy of many successful enterprises, especially large-sized enterprises. This brought into question the future of large-sized enterprises, but at the same time raised the question whether there is an alternative to large-sized enterprises. Of course, there is an alternative in networking of small and medium-sized enterprises and their optimal selection in the creation of new virtual enterprises. This paper deals with the problem of the selection of cooperators for the new production process. It is assumed that enterprises can be mutually compared and ranked, and that makes optimization possible, using Ant Colony Optimization (ACO) algorithm

Project management in mine actions using Multi-Criteria-Analysis-based decision support system

In this paper, a Web-based Decision Support System (Web DSS), that supports humanitarian demining operations and restoration of mine-contaminated areas, is presented. The financial shortage usually triggers a need for priority setting in Project Management in Mine actions. As part of the FP7 Project TIRAMISU, a specialized Web DSS has been developed to achieve a fully transparent priority setting process. It allows stakeholders and donors to actively join the decision making process using a user-friendly and intuitive Web application. The main advantage of this Web DSS is its unique way of managing a mine action project using Multi-Criteria Analysis (MCA), namely the PROMETHEE method, in order to select priorities for demining actions. The developed Web DSS allows decision makers to use several predefined scenarios (different criteria weights) or to develop their own, so it allows project managers to compare different demining possibilities with ease

APPLICATION OF GIS AND MATHEMATICAL MODELING IN MARITIME CRISIS SITUATIONS

This paper aims to propose a decision support system for maritime crisis situation, due to fact that Croatia has decided to implement Directive 2002/59/EC to define places of refuge for ships in need of assistance off their coasts, or to develop techniques for providing assistance to such ships. In order to fulfill this Directive it is necessary to build an effective Decision Support System (DSS) based on GIS and mathematical modeling. The basic module of the proposed system is GIS, for all levels of DSS, that comprise information subsystems about spatial and other data and serves the other modules with data and information. Starting points for analysis are shipping corridors, and 380 potential locations for places of refuge designated in the official navigational pilot book. Multicriteria analysis, with GIS-generated input data, has been used to establish "worthiness" of a place of refuge for each ship category, taking into account kinds of accident. Proposed mathematical models facilitate optimal usage of "available intervention resources"

Prediction of Surface Roughness and Power in Turning Process Using Response Surface Method and ANN

This paper examines the influence of three cutting parameters (cutting speed, cutting depth and feed rate) on surface roughness and power in the longitudinal turning process of aluminium alloy. For the analysis of data gathered by experiments, two methods for prediction of responses were employed, namely Response Surface Methodology (RSM) and Artificial Neural Network (ANN). The research has shown that the ANN gives a better prediction of surface roughness than the RSM. In the modelling of the power, the average error value obtained by the ANN does not differ significantly from its value obtained by the RSM. This research is conducted to reveal the rigidity of the machine tool in order to select an appropriate spindle motor for retrofit purpose. The unexpected surface roughness and the error between the experimental and predicted values show that the obtained models are, in most cases, not adequate to predict surface roughness when the power is greater than a given limit. Therefore, the servo motor with smaller power than the original motor is selected which is cost-effective and it will not cause inappropriate strong vibrations that lead to the unexpected surface roughness and excessive noise inside the Learning Factory environment in which the machine tool is used

Optimization of the selection of competence cells in regional production network

Današnja svjetska gospodarska kriza pokazala je da uspješno poslovanje poduzeća u normalnim ekonomskim uvjetima nije garancija održivosti, tako da je kriza odvela u stečaj mnoga poslovno uspješna poduzeća, a pogotovo velika poduzeća. Ovo je dovelo u pitanje budućnost velikih poduzeća, no u isto vrijeme i otvorilo pitanje postoji li alternativa velikim poduzećima. Alternativa, dakako, postoji u umrežavanju malih i srednjih poduzeća i njihovom optimalnom odabiru u stvaranju novih virtualnih poduzeća. Ovaj se rad bavi baš navedenim problemom odabira kooperanata (kompetencijskih stanica) za određeni novonastali proizvodni proces. Pretpostavlja se da je poduzeća moguće međusobno usporediti i rangirati, što otvara prostor za optimiranje pomoću algoritma Ant Colony Optimization (ACO).The ongoing world economic crisis has shown that being a successful enterprise in normal economic conditions is not a guarantee of sustainability. So the crisis has led to bankruptcy of many successful enterprises, especially large-sized enterprises. This brought into question the future of large-sized enterprises, but at the same time raised the question whether there is an alternative to large-sized enterprises. Of course, there is an alternative in networking of small and medium-sized enterprises and their optimal selection in the creation of new virtual enterprises. This paper deals with the problem of the selection of cooperators for the new production process. It is assumed that enterprises can be mutually compared and ranked, and that makes optimization possible, using Ant Colony Optimization (ACO) algorithm

APPLICATION OF MULTICRITERIA METHODS TO PLANNING OF INVESTMENT PROJECTS IN THE FIELD OF CIVIL ENGINEERING

In this paper we present a new approach for the planning of an investment project in the field of building construction. The focus is in shaping of the concept that serves to facilitate decision making about investments through providing support to investors’ when they are dealing with a problem - selection of a solution for investment project. The concept is based on the combined use of several different criteria, conventional methods for the evaluation of investment projects and multicriteria methods (PROMETHEE and AHP). Selected criteria encompassed economic, social-administrative, construction-functional and spatial aspects of selection problem. The determining criteria weights process is carried out in two steps. In the first step the AHP method is used to obtain the primary weights. The second step allows interactive involvement of investor in the process of solution selection (an investor-subjective approach to the problem). Presented approach is tested on the planning of nvestment project in Croatia

Single-objective and multi-objective optimization using the HUMANT algorithm

When facing a real world, optimization problems mainly become multi-objective i.e. they have several criteria of excellence. A multi-criteria problem submitted for multi-criteria evaluation is a complex problem, as usually there is no optimal solution, and no alternative is the best one according to all criteria. However, if a metaheuristic algorithm is combined with a Multi-Criteria Decision-Making method then, instead of submitting all solutions, only near-optimal solutions are submitted for multi-criteria evaluation, i.e. compared and ranked using a priori decision-maker preferences. It is called an a priori approach to multi-objective optimization. This paper presents this approach using a specially designed HUMANT (HUManoid ANT) algorithm derived from Ant Colony Optimization and the PROMETHEE method. The preliminary results of this optimization algorithm are presented for the Single-Objective Traveling Salesman Problem (TSP), Shortest Path Problem (SPP) and the Multi-Objective Partner Selection Problem (PSP). Additionally, the multi-objective approach of the HUMANT algorithm to single-objective optimization problems is presented using the Shortest Path Problem (SPP)