High-Throughput (HT) platforms have been increasingly used in the life science area for diverse bio-chemical experiments. This paper addresses the scheduling of HT platform based experiments under multiple constraints, such as operation constraints, resource constraints and starvation constraints. We use timed transition Petri nets (PN) to model the experimental process with constraints. We first propose the transition variant property of the PN model. We then propose the HCH (Hong-Chow-Haaland) algorithm, which is customized from A* algorithm, to find a feasible solution. HCH algorithm is more efficient than L1 algorithm and most other A* extended algorithms in identification of new markings when applied to the transition variant PN. We then applied HCH algorithm to two typical HT processes. The results show that HCH algorithm can be used to find optimal solutions with the time complexity of identifying new markings less than 2% of the L1 algorithm. which fulfills the starvation constraint because 6 J starts right after 5 J is completed. Since only one job can be operated at a time due to the resource constraint, the minimum operation time for the whole experiment should be the sum of all the jobs' operation time. The result shows that the total time of this schedule is equal to the minimum operation time (15 time units), which means that the scheduling result is an optimal solution with the objective of minimizing the operation time.J stands for the bth job in the ath process. For example, 2.6 J means the 6th job (culture cells) in process 2. The jobs operating sequence is: