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Bošnjak, A.; Jajac, N. Road Infrastructure Maintenance Management. Encyclopedia. Available online: https://encyclopedia.pub/entry/24119 (accessed on 29 July 2024).
Bošnjak A, Jajac N. Road Infrastructure Maintenance Management. Encyclopedia. Available at: https://encyclopedia.pub/entry/24119. Accessed July 29, 2024.
Bošnjak, Ana, Niksa Jajac. "Road Infrastructure Maintenance Management" Encyclopedia, https://encyclopedia.pub/entry/24119 (accessed July 29, 2024).
Bošnjak, A., & Jajac, N. (2022, June 16). Road Infrastructure Maintenance Management. In Encyclopedia. https://encyclopedia.pub/entry/24119
Bošnjak, Ana and Niksa Jajac. "Road Infrastructure Maintenance Management." Encyclopedia. Web. 16 June, 2022.
Road Infrastructure Maintenance Management
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This entry is adapted from the peer-reviewed paper 10.3390/infrastructures7060080

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. 

maintenance management management functions road network multicriteria decision making

1. Management and Road Infrastructure Maintenance Management

Maintenance management of the road network, in urban and nonurban areas, is a complex process both from the management point of view and from the technical-economic point of view. Thus, management in general, and in this case, road network maintenance management, is said to be a process or series of continuous and related activities aimed at achieving set goals. A closer look at the general concept of managing the maintenance of the road network outside urban areas is possible through the general division of the management process into three main functions: namely, planning, implementation, as well as monitoring and control. The general division of management processes within the business organization into the three mentioned functions is the same as in other management processes. However, its elaboration in this research subject is in line with the needs of management processes aimed at the maintenance of the nonurban road network.
The nonurban road network presents a network of roads outside urban areas that includes roads between urban areas, cities, and settlements. As such, it is intended to connect economically important areas and centers of local communities.
Roads are national assets that support economic activity, as road transport is the basis for economic activity, outdated road infrastructure requires increased maintenance, traffic continues to grow and increases the need for maintenance, etc. [1]. These facts indicate the importance and need for road maintenance management, as well as constant development of urban and nonurban road network maintenance management models. Planning, as the first function of road infrastructure maintenance management, is a complex process in which several authors generally agree. Thus, Marović et al. [1] emphasize that maintenance planning, as part of urban road infrastructure management, is a complex problem from both the managerial and techno-economic aspects, focusing on decision-making processes related to the planning phase during urban road infrastructure project management. Concerning these problems, Jajac et al. [2] emphasize that the prioritization of projects, in terms of particular annual budgets for construction, maintenance, and rehabilitation activities, are the most difficult and important issues in the public decision-making process. The other reasons for this complexity are different participants with different opinions, the multidisciplinary nature of the problem, a large amount of information, as well as conflicting goals and criteria.

2. Decision Making and Road Infrastructure Maintenance Management

Management is a complex process that cannot happen without a decision-making process. Decision-making is considered the essence of all the above management functions, while decision support is one of the key factors of successful management.
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) [7], Elimination and (Et) Choice Translating Reality (ELECTRE) [8], Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) [9], Multi-Attribute Utility/Value Theory (MAUT/MAVT) [10], Preference Ranking Organization Method for Enrichment Evaluations (PROMETHEE) [11], Analytical Hierarchy Process (AHP) [12], VIKOR [13], 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 [14] 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 [15].
When it comes to the wider field of construction, there are different examples of its application, such as water supply management system [16], risk management [17], selection of the appropriate material supplier [18], selection of the most suitable concrete mix [19], assessment of dam rehabilitation [20], solving problems in the field of energy efficiency [21], evaluation of solutions in the design of building structures [22], determining the priorities of the restoration of architectural heritage [23], determining the index of the condition of the bridge [24], and choosing the best way to manage demand [25].
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 [9]. Numerous authors have applied the TOPSIS method in poorly structured engineering problems, such as selecting the most suitable contractor [26][27], selecting the appropriate wastewater treatment technology [28], assessing the level of risk safety of bridge construction [29], evaluating bids for highway construction [30], the process of hiring employees according to pre-defined criteria [31], etc.
When it comes to the AHP method application in solving the problem of transport infrastructure, Sirin et al. [32] 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 [33] 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 [34] 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 [35] 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. [36] 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. [15] 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 [37], site selection in the construction project planning phase [38], selection of the best investment project [39], planning the rehabilitation of schools by removing barriers [40], and maintenance of city parking facilities [41]. 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 [42] 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. [43] 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.
Furthermore, Rogulj et al. [40] developed a new expert system for assessing the condition of historic road bridges as part of road infrastructure, using fuzzy logic and alpha cuts in combination with the AHP method used to compare and rank alternative solutions.

References

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Subjects: Engineering, Civil
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