A coal preparation plant typically has multiple cleaning circuits based on size of coal particles. Each circuit is operated to produce the same product quality so that the blend of clean coal meets the targeted product quality constraints. Though, this approach of producing the clean coal satisfies the product quality constraints as given by the customer, it may suffer from the loss of overall clean coal yield by 1–2%. Numerous studies conducted in the past illustrate that the optimal yield can be obtained by operating each circuit to produce the same incremental product quality. However, this approach is good enough for single product quality constraints but it fails to produce optimal yield with multiple product quality constraints. A newer optimization technique known as particle swarming is developed for the yield optimization of a coal preparation plant while satisfying multiple product quality constraints. The optimization model incorporates two product quality constraints - product ash and sulfur assay. The results indicate that an increment of 2.73% in the yield could be achieved by both equal incremental ash quality approach and particle swarm optimization. The additional yield can generate extra revenue of $5,460,000 per annum without significantly adding to the implementation/operation cost.