Wireless Sensor Network is a prominent part of Networking and Communications. The usefulness of sensor nodes is meaningful only when they are aware of their positions. This makes localization the most important issue for wireless sensor networks. This technology is used in various domains, for instance, disaster response, wildlife monitoring, military surveillance, etc. Therefore, the accuracy of localization algorithms can never be jeopardized. Methods that are based on distance or angle measurements are called Range Based Methods. They offer precision but at a higher cost and complexity. The Range-Free methods are more suitable than their counterparts because of their no hardware requirements and lower costs. DV-Hop is a highly acclaimed technique for achieving localization. However, it suffers from a great loss of accuracy and other vital issues such as energy constraints, irregular networks, etc. This study discusses the various approaches based on geometry, ML, and optimization techniques that aim to tackle these issues. The paper explores the recent advancements made to DV-Hop to optimize its performance that incorporate techniques like weighted AHD, flooding control, selective anchors, etc. Furthermore, the use of optimization algorithms such as PSO is discussed which aims to further boost the accuracy.