  For decades, complex networks, such as social networks, biological networks,
chemical networks, technological networks, have been used to study the
evolution and dynamics of different kinds of complex systems. These complex
systems can be better described using weighted links as binary connections do
not portray the complete information of the system. All these weighted networks
evolve in a different environment by following different underlying mechanics.
Researchers have worked on unraveling the evolving phenomenon of weighted
networks to understand their structure and dynamics. In this chapter, we
discuss the evolution of weighted networks and evolving models to generate
different types of synthetic weighted networks, including undirected, directed,
signed, multilayered, community, and core-periphery structured weighted
networks. We further discuss various properties held by generated synthetic
networks and their similarity with real-world weighted networks.
