Graph layout problems, such as node and edge overlapping, occur widely in many industrial computer-aided design applications. Usually, these problems are handled in an ad-hoc manner by some specially designed algorithms. GENET and its extended model EGENET are local search models that are used to efficiently solve constraint satisfaction problems such as the car-sequencing problems. Both models use min-conflict heuristic-based artificial neural nets to update every finite-domain variable for finding local minima, and then apply heuristic learning rule(s) to escape those local minima not representing solutions. In the past, few researchers have ever considered to apply any local search method like the EGENET approach to solve graph layout problems. In this paper, we consider how to modify the original EGENET model for solving the graph layout problems formulated as continuous constrained optimization problems. An empirical evaluation of different approaches on the graph layout problems demonstrated some advantages of our modified EGENET approach, which requires further investigation. More importantly, this interesting proposal opens up numerous opportunities for exploring the other possible ways to modify the original EGENET model, or using the other local search methods to solve these graph layout problems.
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