The scheduling of multi-user remote laboratories is modeled as a multimodal function for the proposed optimization algorithm. hybrid algorithm, hybridization Nelder-Mead Simplex and Non-dominated Sorting Genetic Algorithm (NSGA), named (SNSGA), to optimize timetable problem coordinate shared access. algorithm utilizes in terms exploration NSGA sorting local optimum points with consideration pot...

Algorithms generating piecewise linear approximations of the nondominated set for general, convex and nonconvex, multicriteria programs are developed. Polyhedral distance functions are used to construct the approximation and evaluate its quality. The functions automatically adapt to the problem structure and scaling which makes the approximation process unbiased and self-driven. Decision makers...

Designing an optimal communication network is a complex, multiconstraint and multi-criterion optimisation problem. Previous work in this field has optimized a single objective or a combination of multiple values into a single scalar value. In this work, we use the multiobjective genetic optimisation technique along with the convergence to obtain a Pareto front – a set of solutions, which are no...

This paper presents an optimal kinematic design of a 3PRC (prismatic-revolute-cylindrical) spatial translational parallel manipulator with inclined actuator arrangement by formulating a multi-objective optimization problem. Three performance criteria’s namely Global Conditioning Index (GCI), Global stiffness Index (GSI) and Workspace volume are considered as the objective functions. A multi-obj...

The multiobjective vehicle routing problem considering customer satisfaction MVRPCS involves the distribution of orders from several depots to a set of customers over a time window. This paper presents a self-adaptive grid multi-objective quantum evolutionary algorithm MOQEA for the MVRPCS, which takes into account customer satisfaction as well as travel costs. The degree of customer satisfacti...

A multiobjective programming algorithm may find multiple nondominated solutions. If these solutions are scattered more uniformly over the Pareto frontier in the objective space, they are more different choices and hence their quality is better. In this paper, we propose a quality measure called U-measure to measure the uniformity of a given set of nondominated solutions over the Pareto frontier...

In several machine vision problems, a relevant issue is the estimation of homographies between two different perspectives that hold an extensive set of abnormal data. A method to find such estimation is the random sampling consensus (RANSAC); in this, the goal is to maximize the number of matching points given a permissible error (Pe), according to a candidate model. However, those objectives a...

In binary classification problems, receiver operating characteristic (ROC) graphs are commonly used for visualizing, organizing and selecting classifiers based on their performances. An important issue in the ROC literature is to obtain the ROC convex hull (ROCCH) that covers potentially optima for a given set of classifiers [1]. Maximizing the ROCCH means to maximize the true positive rate (tp...

The renowned nursing shortage has attracted much attention from national level law makers, state legislatures, commercial organizations, and researchers due to its direct impact on the quality of patient care. High workloads and undesirable schedules are two major issues that cause nurses’ job dissatisfaction. The focus of this paper is to find nondominated solutions to an integrated nurse staf...

In this paper we introduce a sublinear conditional operator with respect to family of possibly nondominated probability measures in presence multiple ordered default times. way generalize the results Biagini and Zhang (2019), where reduced-form framework under model uncertainty for single time is developed. Moreover, use valuation credit portfolio derivatives uncertainty.