multi objectives fuzzy ant colony optimization of palm oil press machine
MULTI OBJECTIVES FUZZY ANT COLONY OPTIMIZATION DESIGN
because in the real case, the supply path has multi path and objectives (especially in palm oil based bioenergy supply). The objective of this paper is to improve the ant colony optimization for
The objective of this paper is to improve the ant colony optimization for solving multi objectives based supply path problem by using fuzzy ant colony optimization. The developed multi objectives fuzzy ant colony optimization design was explained here, that it was used to search the best supply path. Keywords: multi objectives fuzzy ant colony optimization design, supply path searching,
Multi objectives fuzzy ant colony optimization
The objective of this paper is to improve the ant colony optimization for solving multi objectives based supply path problem by using fuzzy ant colony optimization. The developed multi objectives
These multi-objective ACO (MOACO) algorithms exhibit different design choices for dealing with the particularities of the multi-objective context. This program implements the multi-objective ant colony optimization (MOACO) framework. This framework is able to instantiate most MOACO algorithms from the literature, and also combine components
A simple butterfly lifecycle algorithm for measuring
The developed multi objectives fuzzy ant colony optimization was used to search the most optimum path of palm oil based bioenergy supply chain. The method was validated and verified with a real
Ant Colony Optimization to solve multi-objective optimiza-tion problems. The proposed algorithm is parameterized by the number of ant colonies and the number of pheromone trails. We compare different variants of this algorithm on the multi-objective knapsack problem. We compare also the obtained results with other evolutionary algorithms from
The Automatic Design of Multi-Objective Ant Colony
The Automatic Design of Multi-Objective Ant Colony Optimization Algorithms Manuel L opez-Ib´ a´nez and Thomas St utzle¨ Abstract Multi-objective optimization problems are problems with several, typically conicting criteria for evaluating solutions. Without any a
The developed multi objectives fuzzy ant colony optimization was used to search the most optimum path of palm oil based bioenergy supply chain. The method was validated and verified with a real
The optimization of the application of fuzzy ant colony
The objective of this paper is to improve the ant colony optimization for solving multi objectives based supply path problem by using fuzzy ant colony optimization. The developed multi objectives
An objective function of an optimization model is defined as multi-objectives if it models more than one entity is to be optimized; the optimization problem has to be solved in more than one dimension. For instance, an objective function that includes variables of profit and time is multi-objectives.
Artificial Bee Colony (ABC) for multi-objective design
In this paper, we present a generic method/model for multi-objective design optimization of laminated composite components, based on Vector Evaluated Artificial Bee Colony (VEABC) algorithm. VEABC is a parallel vector evaluated type, swarm intelligence multi-objective variant of the Artificial Bee Colony algorithm (ABC). In the current work a
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Ant Colony Optimization for Multi-Objective Machine-Tool
Ant Colony Optimization for Multi-Objective Machine-Tool Selection and Operation Allocation in a Flexible Manufacturing System 1 2M.H.M.A. Jahromi, R. Tavakkoli-Moghaddam, S.A. Jazayeri, R. Jafari and A. Shamsi3 31 1Department of Industrial Engineering, Islamic Azad University Khomein Branch, Khomein, I.R. Iran
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Ditdit Nugeraha Utama
Multi Objectives Fuzzy Ant Colony Optimization for Palm Oil Based Bioenergy Supply Path Searching. Proceeding of International Conference on Computer Science and Information Systems ICACSIS, 2011: pp. 177 182. Jakarta, Indonesia.
Get Price![imoaco[equation]: a new indicator-based multi](/img/equipment420.jpg)
iMOACO[equation]: A New Indicator-Based Multi
Abstract. Ant colony optimization (ACO) is a metaheurisitc which was originally designed to solve combinatorial optimization problems. In recent years, ACO has been extended to tackle continuous single-objective optimization problems, being ACO (_mathbb {R}) one of the most remarkable approaches of this sort. However, there exist just a few ACO-based algorithms designed
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Fuzzy ant colony optimization for optimal control
Fuzzy ant colony optimization for optimal The so called Fuzzy ACO algorithm integrates the multi-agent optimization heuristic of ACO with a fuzzy partitioning of the state space of the system. A simulated control problem is presented to demonstrate the functioning of the proposed algorithm. I. INTRODUCTION Ant Colony Optimization (ACO) is inspired by ants and their behavior of finding
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OPTIMAL DISTRIBUTED GENERATION SIZING AND PLACEMENT
the objective to be minimized. Secondly, the problem is tackled as a multi-objective one, focusing on DG installation costs. These problems are formulated as constrained nonlinear optimization problems using the Sequential Quadratic Programming method. A weighted sum method and a fuzzy decision-making method are presented to generate the
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Composite goal methods for transportation network
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2011 International Conference on Advanced Computer Science
Multi Objectives Fuzzy Ant Colony Optimization of Palm Oil Based Bioenergy Supply Path Searching 177 Ditdit N . Utama, TaufikDjatna, ErlizaHambali, Marimin, and Dadan Kusdiana Computational Model of Social Interaction in Multi -agent Simulation based on Personality Traits 183 Aswin Indraprastha
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2011 International Conference on Advanced Computer Science
Multi Objectives Fuzzy Ant Colony Optimization of Palm Oil Based Bioenergy Supply Path Searching 177 Ditdit N . Utama, TaufikDjatna, ErlizaHambali, Marimin, and Dadan Kusdiana Computational Model of Social Interaction in Multi -agent Simulation based on Personality Traits 183 Aswin Indraprastha
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Hybrid Pareto artificial bee colony algorithm for multi
Hybrid Pareto artificial bee colony algorithm for multi‑objective single machine group scheduling problem with sequence‑dependent setup times and learning effects Lei Yue 1, Zailin Guan1, Ullah Saif1,2*, Fei Zhang1 and Hao Wang1 Background Group technology (GT) is a well-known method used to improve the production effi-
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Ant Colony Optimization SpringerLink
Ant colony optimization (ACO) is a population-based metaheuristic for the solution of difficult combinatorial optimization problems. In ACO, each individual of the population is an artificial agent that builds incrementally and stochastically a solution to the considered problem.
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Ants colony algorithm approach for multi-objective
Abstract. An ant colony based optimisation procedure has been developed to optimise grinding conditions, viz. wheel speed, workpiece speed, depth of dressing and lead of dressing, using a multi-objective function model with a weighted approach for the surface grinding process.
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CHAPTER 3 MULTI AGENT ROBOT CONTROL BASED ON TYPE-2 FUZZY
MULTI AGENT ROBOT CONTROL BASED ON TYPE-2 FUZZY AND ANT COLONY OPTIMIZATION 3.1 INTRODUCTION This chapter is to focus on an Agent based approach to Multi robot control using type -2 fuzzy and Ant colony optimization. Type -2 fuzzy interval controllers was applied to the autonomous robot in order to handle uncertainty in a better way and ant colony optimization
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Multi-objective optimization with artificial weed
4. Adapting IWO for multi-objective optimization. In this section we present the IWO for multi-objective optimization (IWO_MO) algorithm, the associated fuzzy dominance based sorting technique and the constraint handling method that we use for a certain class of benchmarks in conjunction with MOIWO. We also provide an approximate analysis
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Bi-Objective Ant Colony Optimization approach to
This paper presents an algorithm based on Ant Colony Optimization paradigm to solve the joint production and maintenance scheduling problem. This approach is developed to deal with the model previously proposed in for the parallel machine case. This model is formulated according to a bi-objective approach to find trade-off solutions between both objectives of production and maintenance.
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Parameter Optimization of Support Vector Machine
Rongali S., Yalavarthi R. (2016) Parameter Optimization of Support Vector Machine by Improved Ant Colony Optimization. In: Satapathy S., Raju K., Mandal J., Bhateja V. (eds) Proceedings of the Second International Conference on Computer and Communication Technologies. Advances in Intelligent Systems and Computing, vol 379. Springer, New Delhi
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College Of Engineering Research Output — Universiti
Parametrized 2D/3D garment model for dexterous robotic manipulation Yew, C. H., Mohamed Sahari, K. S. & Dickson Neoh, T. H., 15 May 2024, Proceedings 2024 Joint 10th International Conference on Soft Computing and Intelligent Systems and 19th International Symposium on Advanced Intelligent Systems, SCIS-ISIS 2024. Institute of Electrical and Electronics Engineers Inc., p. 287-291 5 p. 8716253.
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Computer Aided Molecular Design for alternative
1. Introduction. Palm oil is one of the major edible oils across the world and is a source of lipids. Nearly 90% of palm oil produced in the world, is further converted into food products such as cooking oil, industrial and confectionery fats, breakfast cereals and supplements/vitamins.
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Synthesis of multiple biomass corridor via decomposition
Read "Synthesis of multiple biomass corridor via decomposition approach: a P-graph application, Journal of Cleaner Production" on DeepDyve, the largest online rental service for scholarly research with thousands of academic publications available at your fingertips.
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Flower pollination algorithm: a comprehensive review
Flower pollination algorithm (FPA) is a computational intelligence metaheuristic that takes its metaphor from flowers proliferation role in plants. This paper provides a comprehensive review of all...
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UTM Scholars
An Ant Colony Optimization For Dynamic Job Scheduling In Grid Environment. International Journal of Computer and Information Science and Engineering, World Academy of Science, Engineer and Technology Journal Article Non Citation-Indexed CO-AUTHOR
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Modeling and control of diesel engines: A systematic
To handle the robustness uncertainty, the discrepancy between the multi-objective optimization and the dynamic single objective optimization that is unveiled during conversion helps a lot. Modelling of this discrepancy with the aid of machine learning approaches could let this uncertainty to be kept under control. Later, this model could
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2009 International Conference of Soft Computing
2009 International Conference of Soft Computing and Pattern Recognition SoCPaR 2009 Table of Contents Welcome from the General Chairs Welcome from the Program Chairs
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Research FSKKP UMP
Faculty of Computing (formerly known as Faculty of Computer Systems & Software Engineering) was established on 16 February 2002 to produce knowledgeable, high skilled and competitive graduates within the sphere of software engineering, system and computer network. At the beginning, the faculty had two fields which are Software Engineering and Networking.
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