MOSMA: Multi-Objective Slime Mould Algorithm Based on Elitist Non-Dominated Sorting

This paper proposes a multi-objective Slime Mould Algorithm (MOSMA), variant of the recently-developed (SMA) for handling optimization problems in industries. Recently, problems, several meta-heuristic and evolutionary techniques have been suggested community. These methods tend to suffer from low-quality solutions when evaluating (MOO) than addressing objective functions identifying Pareto optimal solutions’ accurate estimation increasing distribution throughout all objectives. The SMA method follows logic gained oscillation behaviors slime mould laboratory experiments. algorithm shows powerful performance compared other well-established methods, it is designed by incorporating food path using positive-negative feedback system. proposed MOSMA employs same underlying mechanisms convergence combined with an elitist non-dominated sorting approach estimate solutions. As posteriori method, formulation maintained MOSMA, crowding distance operator utilized ensure coverage across To verify validate 41 different case studies, including unconstrained, constrained, real-world engineering design are considered. Multiobjective Symbiotic-Organism Search (MOSOS), Multi-objective Evolutionary Based on Decomposition (MOEA/D), Water-Cycle (MOWCA) terms metrics, such as Generational Distance (GD), Inverted (IGD), Maximum Spread (MS), Spacing, Run-time. simulation results demonstrated superiority realizing high-quality linear, nonlinear, continuous, discrete front. indicate effectiveness solving complicated problems. research will be backed up extra online service guidance paper’s source code at https://premkumarmanoharan.wixsite.com/mysite xmlns:xlink="http://www.w3.org/1999/xlink">https://aliasgharheidari.com/SMA.html . Also, shared public