Every aspect of our day-to day life is linked with electricity. The quality of life and the development of a given country depend on the quality and reliability of electric power supply systems. The assessment of distribution system reliability gives information about the system performance and helps to know the cost or losses incurred by the utility and its customers as a result of power interruption. Distribution system reliability has acquired importance these days, because the distribution system performance can directly affect the customers. The distribution system reliability mainly deals with the interruption frequency and interruption duration of customers. If these values are large , the reliability of system is poor.The historical reliability assessment of Harar city Substation III, 15KV distribution system for the year 2007 and 2008 EC is carried out using analytical methods. The average power interruption frequency and duration over the period of study for the test system is 470 interruptions and 405 hours of duration respectively. There are many measures to assess the reliability of a power distribution network. The most common measures are SAIFI, SAIDI, EENS, CENS and ASAI. Many measures are used to estimate the reliability of a distribution network. In this research, the focus of the reliability measure is the lost revenue as a result of EENS and the incurred cost as an action to improve reliability through installing optimal number of sectionalizing switches. To improve the system reliability, heuristic optimization methods are applied. These methods are BDSA and BPSO based on multi objective optimization methodology to determine the optimal number and location of new installed sectionalizing switches in electric power distribution networks. To illustrate the performance of the proposed algorithms, an actual 15KV overhead line distribution feeder (line 2) with 62 segments is selected as a test system and the program is written and simulated in MATLAB software. The predictive reliability assessment is calculated by considering no sectionalizing switch, by placing sectionalizing switches on all the segments and by optimal placement of number and allocation of sectionalizing switches for both proposed methods. From the test results the BDSA has better minimized CENS and it also has better computational efficiency. As the result of the optimal placement of switches the cost of EENS is reduced from 6.5861*107 to 3.9289*107 birr at the incurred cost of switches which is 4.4196*105 birr.