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Engineering, Civil
Management of nonurban road network maintenance is a complex management process that requires the inclusion of many technical, economic, and other characteristics of the problem, as well as the continuous application of new knowledge and approaches, to maintenance management. To effectively manage the maintenance of the road network in conditions of limited financial resources, maintenance is examined through three interrelated management functions of planning: implementation, monitoring, and maintenance control. This paper includes an analysis of current and relevant papers on this topic. Based on the conducted analysis, the paper gives a theoretical framework and proposes a management model for road network maintenance between urban areas. This model supports the previously mentioned management functions using Multicriteria Decision-Making Methods. The AHP method and the TOPSIS method are engaged in the process of generating a priority road maintenance plan and Earned Value Analysis in maintenance monitoring and control. The AHP method is used to determine the criteria weight vector as a key role in defining the rank of alternatives and in identifying the optimal maintenance rank of nonurban roads using the TOPSIS method. All of the above aim to ensure the safe flow of traffic and the permanent preservation of the construction, traffic, and economic value of roads between urban areas.
- maintenance management
- management functions
- road network
- multicriteria decision making
1. Upravljanje i upravljanje održavanjem cestovne infrastrukture
Upravljanje održavanjem cestovne mreže, u urbanim i izvangradskim sredinama, složen je proces kako s upravljačkog, tako i s tehničko-ekonomskog stajališta. Dakle, upravljanje općenito, au ovom slučaju upravljanje održavanjem cestovne mreže, kaže se kao proces ili niz kontinuiranih i povezanih aktivnosti usmjerenih na postizanje postavljenih ciljeva. Opći koncept upravljanja održavanjem cestovne mreže izvan urbanih područja moguć je pobliže kroz opću podjelu procesa upravljanja na tri glavne funkcije: planiranje, provedbu, kao i praćenje i kontrolu. Opća podjela procesa upravljanja unutar poslovne organizacije na tri spomenute funkcije je ista kao iu ostalim procesima upravljanja. Međutim,
Neurbana cestovna mreža predstavlja mrežu cesta izvan urbanih područja koja uključuje ceste između urbanih područja, gradova i naselja. Kao takav, namijenjen je povezivanju gospodarski važnih područja i središta mjesnih zajednica.
Ceste su nacionalna dobra koja podržavaju gospodarsku aktivnost, budući da je cestovni promet temelj gospodarske djelatnosti, zastarjela cestovna infrastruktura zahtijeva pojačano održavanje, promet nastavlja rasti i povećava potrebu za održavanjem itd. [ 1 ]. Ove činjenice ukazuju na važnost i potrebu upravljanja održavanjem cesta, kao i na stalni razvoj modela upravljanja održavanjem gradske i izvangradske cestovne mreže. Planiranje, kao prva funkcija upravljanja održavanjem cestovne infrastrukture, složen je proces u kojem se više autora uglavnom slaže. Tako su Marović i sur. [ 1] naglašavaju da je planiranje održavanja, kao dio upravljanja gradskom cestovnom infrastrukturom, složen problem i s upravljačkog i s tehno-ekonomskog aspekta, s fokusom na procese donošenja odluka vezanih uz fazu planiranja tijekom upravljanja projektima gradske cestovne infrastrukture. Što se tiče ovih problema, Jajac i sur. [ 2 ] naglašavaju da su prioriteti projekata, u smislu pojedinih godišnjih proračuna za aktivnosti izgradnje, održavanja i sanacije, najteža i najvažnija pitanja u procesu javnog odlučivanja. Drugi razlozi ove složenosti su različiti sudionici s različitim mišljenjima, multidisciplinarna priroda problema, velika količina informacija, kao i suprotstavljeni ciljevi i kriteriji.
2. Donošenje odluka i upravljanje održavanjem cestovne infrastrukture
Upravljanje je složen proces koji se ne može dogoditi bez procesa donošenja odluka. Donošenje odluka smatra se suštinom svih navedenih upravljačkih funkcija, dok je podrška odlučivanju jedan od ključnih čimbenika uspješnog upravljanja.
The decision-making process usually comes after setting goals and objectives that should be achieved, selecting criteria, and preparing to choose the best alternative. Decision-making happens in the management process several times, and in different time intervals, depending on the process that takes place and the resulting need to make appropriate decisions [3]. Therefore, there is a close connection between management and decision-making, as pointed out by numerous authors from the relevant literature within this field. According to Simon [4], decision-making is synonymous with management. Novak [5] defines decision-making as an integral element of managerial activity, while Gorupić [6] considers that managing a business organization means deciding.
Every decision-maker faces more or fewer problems when making decisions. One of the most common problems is the gap between the needs and possibilities. Namely, the needs of every decision-maker are greater than the possibilities or resources available to them.
The complexity of road infrastructure maintenance management stems, mainly, from a large number of different and conflicting criteria, a large number of stakeholders involved in the decision-making process, a limited maintenance budget, and the multidisciplinary nature of the problems, which is why the decision-making process, as an integral part of management, belongs to complex and poorly structured problems [2]. Therefore, successful nonurban road network maintenance management, as a subject of this research, can be achieved through decision support systems and the application of various methods of multicriteria analysis.
3. Multicriteria Methods and Road Infrastructure Maintenance Management
When managing the maintenance of a nonurban road network, it is usually poorly structured and unstructured problems that are solved by finding the best option, in relation to defined qualitative and quantitative criteria and their weight, using multicriteria analysis methods. The methods of multi-criteria analysis include the following: Simple Additive Weighting (SAW) [8], Elimination and (Et) Choice Translating Reality (ELECTRE) [9], Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) [10], Multi-Attribute Utility/Value Theory (MAUT/MAVT) [11], Preference Ranking Organization Method for Enrichment Evaluations (PROMETHEE) [12], Analytical Hierarchy Process (AHP) [13], VIKOR [14], etc.
Each method has its advantages and disadvantages depending on the problem. What is common for all of them is that each consists of developing several alternative solutions, defining criteria, evaluating alternative solutions to all criteria, determining the weight of criteria, ranking solutions, conducting sensitivity analysis, and making the final decision [15] Each MCDM method is based on the definition of a decision matrix and a criteria weight vector W, which represents the importance that the decision maker gives to each selected criterion. Therefore, after the definition of the decision matrix and criteria weight vector, the most appropriate MCDM method can be used.
In this research, among the mentioned methods, the AHP method was used in determining the importance of criteria, while the TOPSIS method was used in the final ranking of nonurban roads, according to maintenance priorities.
The AHP method, as a multicriteria decision-making method, was developed in 1977 and is used to determine the ranking list of identified alternative solutions that are evaluated according to defined criteria. The method determines the importance factor according to pairwise comparisons of stakeholders involved in the decision-making process. Higher weights define a criterion of greater importance, while lower weights define a less important criterion. The final ranking is obtained by combining the weights of the criteria and the grade of alternative solutions [16].
When it comes to the wider field of construction, there are different examples of its application, such as water supply management system [17], risk management [18], selection of the appropriate material supplier [19], selection of the most suitable concrete mix [20], assessment of dam rehabilitation [21], solving problems in the field of energy efficiency [22], evaluation of solutions in the design of building structures [23], determining the priorities of the restoration of architectural heritage [24], determining the index of the condition of the bridge [25], and choosing the best way to manage demand [26].
The TOPSIS method, developed in 198,1 is based on selecting the optimal alternative according to the shortest distance from the positive ideal solution and the furthest distance from the negative ideal solution, in the geometric sense [10]. Numerous authors have applied the TOPSIS method in poorly structured engineering problems, such as selecting the most suitable contractor [27,28], selecting the appropriate wastewater treatment technology [29], assessing the level of risk safety of bridge construction [30], evaluating bids for highway construction [31], the process of hiring employees according to pre-defined criteria [32], etc.
When it comes to the AHP method application in solving the problem of transport infrastructure, Sirin et al. [33] identify all factors that affect the performance of roads as a fundamental element of road infrastructure during road design, construction, and the maintenance phase.
Khademi and Sheikholeslami [34] combine the AHP method with the Delfi technique, as a hybrid Delfi-AHP model, in prioritizing the maintenance, improvement, and upgrading of lower-class roads. In this research, the Delphi technique was applied in defining the criteria by 76 traffic experts, while the AHP method determines their relative weights, based on which the observed roads are finally ranked according to the priorities of maintenance and reconstruction.
The AHP method can be combined with other methods of multicriteria analysis. Therefore, Sayadinia and Beheshtinia [35] provide a new hybrid approach to multicriteria decision-making by combining AHP, ELECTRE II, ELECTRE III, and ELECTRE IV methods and Copeland techniques in prioritizing road maintenance. Using the AHP method, the weights of individual criteria were also determined, but ELECTRE II, ELECTRE III, and ELECTRE IV methods of multicriteria decision-making were used to rank alternatives. The results obtained with the help of these methods were finally combined with the Copeland technique, thus giving the final list of priorities for the maintenance of the observed roads.
Bhandari and Nalmpantis [36] use the AHP method to rank a total of 13 criteria, divided into three sustainability groups, according to their relative importance. TOPSIS, MOORA, and PROMETHEE methods are used to rank rural roads according to maintenance priorities. Each method gives a similar priority list of observed rural roads.
Jajac et al. [37] propose the concept of decision support on the problem of urban road infrastructure management, based on a combination of AHP, SAW, and PROMETHEE methods and 0–1 programming. The assessment of the importance of the criteria, which includes the opinion of all stakeholders, was performed using the AHP and SAW methods, while the ranking of priorities for the construction of garages, in the urban part of the city of Split, was performed using the PROMETHEE method.
Kilić Pamuković et al. [16] use a combination of the AHP method and PROMETHEE method to rank and determine priorities in the maintenance of asphalt pavement, on the main roads of the city of Split, as part of the road infrastructure. In order to improve the process of planning, the maintenance of asphalt pavements through the applied multicriteria methods—the social, technical, and economic aspects of this problem—have been taken into account.
A similar approach to multicriteria decision-making, based on a combination of AHP and PROMETHEE methods, has been used in other technical and more precise construction issues, such as planning projects for the rehabilitation of historic bridges [38], site selection in the construction project planning phase [39], selection of the best investment project [40], planning the rehabilitation of schools by removing barriers [41], and maintenance of city parking facilities [42]. Regardless of the subject of the research, all authors agree on how complex decision-making processes, such as ranking, cannot take place without the establishment of a decision support system and the application of appropriate multi criteria decision-making methods. Furthermore, Nodrat and Kang [43] developed a tool to prioritize road maintenance and rehabilitation activities. They have taken into account the road condition index, road width, traffic intensity, and maintenance costs. To increase road safety, Francello et al. [44] rank urban road intersections, based on eight safety criteria, by comparing the results obtained using the TOPSIS and VIKOR methods, as well as the Concordance Analysis.
In contrast to decision-making concepts based exclusively on a combination of multi-criteria methods, Jajac et al. [2] presented a multi criteria decision-making approach. It aimed at improving decision-making at the level of urban road infrastructure planning, based on a combination of multi-criteria SAW and AHP methods, with neural networks. Marović et al. [1], to also solve the problem of decision-making in the field of urban infrastructure, developed a model of artificial neural networks to predict road degradation as an auxiliary tool in planning the maintenance of road infrastructure.
Nadalje, Rogulj i sur. [ 41 ] razvio je novi ekspertni sustav za procjenu stanja povijesnih cestovnih mostova kao dijela cestovne infrastrukture, koristeći neizrazu logiku i alfa rezove u kombinaciji s AHP metodom koja se koristi za usporedbu i rangiranje alternativnih rješenja.
This entry is adapted from the peer-reviewed paper 10.3390/infrastructures7060080
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