METHODOLOGY FOR OPTIMISING OF THE ROUTE NETWORK IN THE CITY.

Sofia is the largest city in Bulgaria and continues to grow. From 2011 to 2021, its population increased by 9.8%. Fifteen years ago it had a monocentric structure, or to put it another way, most jobs, commercial space, cultural and social institutions were in the city centеr. As the population increased, the situation changed and the city acquired a polycentric structure with separate centers in all areas of the city. The transformation into a polycentric area also leads to the need for adaption of the route network to the needs of the growing population. The main task of urban passenger transport is delivery of rapid transport between two or more regional centers. In order to function at its best, any transport network needs to meet the conditions for a short journey and the overall transport service needs to be of the highest quality. In the 18th and 19th centuries, models for monocentric cities were developed to explain their economic organization. Cities subsequently evolved from monocentric to polycentric with multiple regional centers. The forces of agglomeration and dispersion determined the emergence of the polycentric city. Climate change, demography and the challenges of globalization also influence the development of cities. The main objective of the study is to develop a methodology to optimize Sofia's future transportation network needed for the growing number of people living in the city. Currently, Sofia's network is designed as a loose structure. In the optimization methodology, certain steps are followed in a specific order to obtain the desired result. The programs used for this type of optimization consist of four consecutive steps and the constraints are the required number. Although in the reorganization of the routing network, their minimization should also be aimed at. Problem formulation is important for the development of the optimization model. The result with the least constraints will always be chosen. In order to adopt a particular course of action, data must be selected and processed to obtain optimal results, which must also be analyzed. The standard four-stage models work with an origin-destination matrix (O-D matrix). It will show us the number of trips people want to make. The peak hour data is mainly used to test the model. The data used in the optimization program must be in a format suitable for the program. In models of this type, blocks of travel flows are used to determine only those routes that meet certain criteria. And from an economic point of view it is important to achieve a balance between the ticket price and the shortest vehicle travel time, and this is a linear combination. The result of optimizing the route network in any major city should be the best service for the growing number of public transport journeys. [ABSTRACT FROM AUTHOR]