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 opt...

This paper introduces one of the most profound Swarm Intelligence-based approaches, namely Ant Colony Optimization (ACO). The different operators in ACO and their effect on the quality of solution are briefly discussed. The ACO algorithms variants like Ant System (AS), Elitist Ant System (EAS), Rankbased Ant System (ASrank), Min-Max based Ant System (MMAS) are detailed. The paper puts forth a s...

The Elitist Convergent Estimation of Distribution Algorithm (ECEDA), is a definition of a class of EDA which guarantees convergence to the optimum. This paper introduces the conceptual ECEDA and a practical approach derived from it, called the Boltzmann Univariate Marginal Distribution Algorithm (BUMDA). The BUMDA uses a Gaussian model to approximate the Boltzmann distribution, requiring only o...

We introduce two models for the quantum weightless neuron node (qRAM) dynamics. After proving the fact that it is not generally possible to mathematically isolate the second qubit after the application of a U-Controlled Operation over a couple of qubits, we propose dynamics models that operate on restrict set of states the elitist states during the iterations. The models are experimentally and ...

In this paper, we present a practical case of the multiobjective knapsack problem which concerns the elaboration of the optimal action plan in the social and medico-social sector. We provide a description and a formal model of the problem as well as some preliminary computational results. We perform an empirical analysis of the behavior of three metaheuristic approaches: a fast and elitist mult...

In data mining, association rule mining is a popular and well researched method for discovering interesting relations between variables in large databases, which are meaningful to the users and can generate strong rules on the basis of these frequent patterns, which are helpful in decision support system. Quantum Particle Swarm Optimization (QPSO) is one of the several methods for mining associ...