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The Plug-in Hybrid Electric Vehicle (PHEV) is becoming the most significant component of the future advanced transportation system and an important part of the smart grid. The energy management issue of charging a large number of PHEVs parked in a municipal parking lot with a limited amount of power available from the grid can be formulated as an optimization problem. Since the problem is basically a scalable resource allocation problem, a proportional allocation mechanism in auction theory is used to address the issue as a market-based tool. Also, a decentralized algorithm based on auction theory is developed that furnishes an updating rule to the vehicles as bidders to make the optimal decision about their next bid. This decision considers their previous bids and the price they have received from the market manager as a feedback. In this paper, considering PHEVs as price-taker bidders, we apply the auction theory method to solve the PHEV parking lot optimization problem for 10 vehicles, as a small example, and then for a large number of vehicles. The results are presented for both cases and compared to the Particle Swarm Optimization (PSO) as a well-known population-based optimization method.