Bioimage-informatics is a new collaborative research area for biologist and image-informatics researchers. Tasks of bioimage-informatics are often very difficult because bioimages capture unclear, ambiguous and multiple targets under various noise and low time-space resolution. This difficulty suggests the necessity of robust image processing techniques. One promising strategy for developing such techniques is to utilize various optimization methods. Optimization methods aim to have the best solution among all possible solutions and thus will provide better results than naive and heuristic methods. On the other hands, thoughtless formulation of an image processing task as an optimization problem results in prohibitive computational complexity and it is impossible to have the optimal solution of the problem. We, therefore, need to formulate the problem as practically solvable one by a certain optimization method. This article outline several examples of optimization problems and their application to bioimage-informatics tasks.