In the Activity Based Modeling (ABM) approach, an activity pattern is specifically assigned to each individual in ahousehold. In this way, one of the fundamental steps in the ABM approach is to project the socio-economic characteristics of allhousehold members while considering some marginal constraints available for the whole of population which is known as populationsynthesizing. In the current paper, the household characteristics distribution is defined as the probability of having a household with aparticular size, number of students and workers. The main goal of current research is to statistically fit the household characteristicsdistribution of the population to a previously obtained distribution for sample households in a way which satisfies the marginalconstraints in traffic zones. It is also followed to solve two main issues in most previous research on population synthesis, one ofthem is related to the so called “zero cell” and the other is known as the “Integrality” problem. Similarity between characteristicsdistributions of the sample and all households can be achieved by using Maximum Likelihood Estimation (MLE) with the marginalconstraints. Satisfying all marginal constraints in a single optimization for a real case study involving a huge number of householdsincreases the mathematical complexity of the problem, and likely leads to an infeasible state. In the current paper, a new idea forsolving this problem in real cases is proposed. The proposed algorithm using GAMS software is implemented in Mashhad city(population of more than 2.5 million) in Iran.