The convergent product concept is realized through the systematic integration of functions and sub-functions to form a final product. This integration is modeled as a web-based network, where nodes represent base functions and sub-functions, and arcs denote connections between them. The objective is to identify an optimal functional tree within this network that maximizes product value in a web-based environment. The modeling approach begins with an algorithmic framework to establish relationships between base functions and sub-functions. A mathematical formulation is then applied to assign quantitative measures, where arcs are characterized by benefit values and nodes by implementation costs, with customer value being explicitly incorporated through the benefit structure. To solve this optimization problem, the conventional Steiner tree methodology is extended into a multi-objective framework and solved using an ant colony optimization algorithm, demonstrated through a numerical example. Further enhancing this approach, a particle swarm optimization technique is implemented within a fuzzy Steiner tree framework for the convergent product network. This advanced formulation incorporates fuzzy mathematical principles to represent uncertain arc benefits and node costs. The fuzzy Steiner tree methodology is subsequently adapted into a bi-objective optimization model to determine the optimal network configuration, with its practical application illustrated through a detailed case study.