نتایج جستجو برای: dominated sorting genetic algorithm nsga

تعداد نتایج: 1385558  

Distribution centers (DCs) play important role in maintaining the uninterrupted flow of goods and materials between the manufacturers and their customers.This paper proposes a mathematical model as the bi-objective capacitated multi-vehicle allocation of customers to distribution centers. An evolutionary algorithm named non-dominated sorting ant colony optimization (NSACO) is used as the optimi...

Journal: :Electronics 2023

This paper presents two optimization methods of an interior permanent magnetic motor (IPM). The first method is based on the non-dominated sorting genetic algorithm II (NSGA-II), while second one NSGA-III algorithm. focus reduction cogging torque (CT), which acts upon rotor when IPM not powered, and current that flows through three windings 0. influence CT over operation a negative one, inducin...

2011
Petr KADLEC Zbyněk RAIDA

In the paper, a novel stochastic Multi-Objective Self-Organizing Migrating Algorithm (MOSOMA) is introduced. For the search of optima, MOSOMA employs a migration technique used in a single-objective Self Organizing Migrating Algorithm (SOMA). In order to obtain a uniform distribution of Pareto optimal solutions, a novel technique considering Euclidian distances among solutions is introduced. MO...

This paper considers a multi-period, multi-product inventory-routing problem in a two-level supply chain consisting of a distributor and a set of customers. This problem is modeled with the aim of minimizing bi-objectives, namely the total system cost (including startup, distribution and maintenance costs) and risk-based transportation. Products are delivered to customers by some heterogeneous ...

Journal: :Electronic Notes in Discrete Mathematics 2012
Vitor Nazário Coelho Marcone J. F. Souza Igor Machado Coelho Frederico G. Guimarães Thibaut Lust R. C. Cruz

This work presents three multi-objective heuristic algorithms based on Two-phase Pareto Local Search with VNS (2PPLS-VNS), Multi-objective Variable Neighborhood Search (MOVNS) and Non-dominated Sorting Genetic Algorithm II (NSGA-II). The algorithms were applied to the open-pit-mining operational planning problem with dynamic truck allocation (OPMOP). Approximations to Pareto sets generated by t...

Journal: :IEEE Access 2023

Trajectory planning is always a hot issue for harvesting manipulator in practice considering that the limitations of mechanical structure and other nonlinear factors lead to long harvest time, big jerk high energy consumption. The cubic spline algorithm, fifth-order polynomial interpolation fusing algorithm are used shorten reduce enhance robustness manipulator, respectively. Then trajectory pr...

Taking into account competitive markets, manufacturers attend more customer’s personalization. Accordingly, build-to-order systems have been given more attention in recent years. In these systems, the customer is a very important asset for us and has been paid less attention in the previous studies. This paper introduces a new build-to-order problem in the supply chain. This study focuses on bo...

2017
Luis Martí Eduardo Segredo Nayat Sánchez Pi Emma Hart

Selection methods are a key component of all multi-objective and, consequently, many-objective optimisation evolutionary algorithms. They must perform two main tasks simultaneously. First of all, they must select individuals that are as close as possible to the Pareto optimal front (convergence). Second, but not less important, they must help the evolutionary approach to provide a diverse popul...

A. Yaghoubi, M. Asghari

In today’s competitive world, the need to supply chain management (SCM) is more than ever. Since the purpose of logistic problems is minimizing the costs of organization to create favorable time and place for the products, SCM seek to create competitive advantage for their organizations and increase their productivity. This paper proposes a new multi-objective model for integrated forward / rev...

2008
M. Jagadeeswari M. C. Bhuvaneswari

This paper proposes a novel Multi-Objective Evolutionary Algorithm for hardware software partitioning of embedded systems. Customized genetic algorithms (GA) have been effectively used for solving complex optimization problems (NP Hard) but are mainly applied to optimize a particular solution with respect to a single objective. Many real world problems in embedded systems have multiple objectiv...

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