Initially, VisuAlgo was not designed for small touch screens like smartphones, as intricate algorithm visualizations required substantial pixel space and click-and-drag interactions. While primarily designed for National University of Singapore (NUS) students enrolled in various data structure and algorithm courses (e.g., CS1010/equivalent, CS2040/equivalent (including IT5003), CS3230, CS3233, and CS4234), VisuAlgo also serves as a valuable resource for inquisitive minds worldwide, promoting online learning. Suhendry Effendy - VisuAlgo remains the exclusive platform for visualizing and animating several of these complex algorithms even after a decade. Steven Halim's book, 'Competitive Programming' - co-authored with Dr. Steven Halim, VisuAlgo aimed to facilitate a deeper understanding of data structures and algorithms for his students by providing a self-paced, interactive learning platform.įeaturing numerous advanced algorithms discussed in Dr. This missing feature will likely be added in the next iteration of this visualization page.ĭiscussion: Is there other ways to compute the value of the flow value(f)? In this visualization, we focus on showing the final max flow value and the final ST-min cut components at the end of each max flow algorithm execution, instead of the precise assignment of flow f to each edge, i.e., f(e) must be computed manually from the initial capacity c(e) (first frame of the animation) minus the final residual capacity of that edge e (last frame of the animation). So that the value of the flow ( value(f) = ∑ v: (s, v) ∈ E f(s,v)) is maximum. Equilibrium constraints (for every vertex except s and t, flow-in = flow-out).Capacity constraints (flow on each edge ( f(e)) is between 0 and its (unit) capacity ( c(e)), i.e., 0 ≤ f(e) ≤ c(e) - not negative and not more than the capacity), and. ![]() The output for a Max Flow algorithm is the max flow value and an assignment of flow f to each edge that satisfies two important constraints:
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