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Minimization of power losses in distribution network (DN) is one of the vast areas of research, where researchers are performing different techniques and methods to reduce the losses. In recent times, network reconfiguration (Nr) has gained more significance in DN to reduce the losses due to its ease of implementation. Most of the work carried on Nr has usually assumed only single hour load model, which didn't vary with time. But in practical DN, load varies during the day. The tie line switching configuration obtained with single hour load model (which doesn't vary with time) is implemented in practical DN, it induces high power losses, reduces the reliability, loadability and voltage profile of the network. Most of the researchers have used single hour load model with Nr and not considered variation in load with Nr. In this study, variation in load is considered with twenty-four hour load. An investigation has been performed to find the losses obtained with variation in load for twenty-four hours. However, changing the topological of the network without disturbing the radiality is a complex non differentiable optimization problem. Nr implemented with twenty-four hour load has more complex computation as compared with single hour load. A quantum-inspired evolutionary algorithm, i.e., adaptive quantum-inspired evolutionary algorithm (AQiEA), is used to solve this complex optimization problem. In this study, two test cases are created in which the first case, uses four different scenarios to find the effect of power losses incurred in the system after opening the switches on single hour load and twenty-four hour load model. An effort has been made for optimal tie line switching configuration for twenty-four hour load instead of single hour load. In addition, an attempt has been made to maximize the economic benefits in DN with Nr on twenty-four hour load. Switching operation cost is considered to study the effect of frequent Nr on the life span of switches. Second case is used to test the efficacy of the proposed algorithm as compared with other techniques. The performance of AQiEA is tested on two IEEE standard test bus systems. Wilcoxon signed-rank test is also used to demonstrate the effectiveness of AQiEA. [ABSTRACT FROM AUTHOR]