Surveillance videos are a ubiquitous and powerful tool in modern security and surveillance systems. Storing and analyzing these surveillance videos pose a challenge to both cost and time. Surveillance videos have a lot of spatio-temporal redundancies. Owing to this, video synopsis aims to reduce the redundancy to produce a summary, through the preservation of all activities of objects in a short span. Video synopsis has multiple steps, of which the optimization module is the main focus. Reducing activity loss, minimizing collision occurrences, and ensuring temporal consistency are some of the objectives that the energy minimization component within the video synopsis framework serves. This paper measures and studies the performances of various standalone (generic) algorithms and hybrid algorithms. Comprehensive experiments are conducted, and the outcomes are analyzed to assess their effectiveness, considering the reduction of activity loss, and collision occurrences, and ensuring temporal consistency. This paper highlights the practical application of optimization algorithms and emphasizes the significance of choosing the right optimization algorithm to minimize energy when creating the synopsis of an object-based surveillance video.