The Experts below are selected from a list of 4683 Experts worldwide ranked by ideXlab platform
Rhymend V Uthariaraj - One of the best experts on this subject based on the ideXlab platform.
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an approach to find Redundant objective function s and Redundant Constraint s in multi objective nonlinear stochastic fractional programming problems
European Journal of Operational Research, 2010Co-Authors: Vincent Charles, A Udhayakumar, Rhymend V UthariarajAbstract:Structural redundancies in mathematical programming models are nothing uncommon and nonlinear programming problems are no exception. Over the past few decades numerous papers have been written on redundancy. Redundancy in Constraints and variables are usually studied in a class of mathematical programming problems. However, main emphasis has so far been given only to linear programming problems. In this paper, an algorithm that identifies Redundant objective function(s) and Redundant Constraint(s) simultaneously in multi-objective nonlinear stochastic fractional programming problems is provided. A solution procedure is also illustrated with numerical examples. The proposed algorithm reduces the number of nonlinear fractional objective functions and Constraints in cases where redundancy exists.
Gongxuan Zhang - One of the best experts on this subject based on the ideXlab platform.
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synthesis of petri net supervisors for fms via Redundant Constraint elimination
Automatica, 2015Co-Authors: Bo Huang, Mengchu Zhou, Gongxuan ZhangAbstract:The Minimal number of Control Places Problem (MCPP), which is formulated to obtain optimal and structurally minimal supervisors, needs extensive computation. The current methods to reduce the computational burden have mainly focused on revision of the original formulation of MCPP. Instead, this paper presents methods to accelerate its solution by eliminating its Redundant reachability Constraints. The optimization problem scale required for supervisor synthesis is thus drastically reduced. First, a sufficient and necessary condition for a reachability Constraint to be Redundant is established in the form of an integer linear program (ILP), based on a newly proposed concept called feasible region of supervisors. Then, two kinds of redundancy elimination methods are proposed: an ILP one and a non-ILP one. Most of the Redundant reachability Constraints can be eliminated by our methods in a short time. The computational time to solve MCPP is greatly reduced after the elimination, especially for large-scale systems. The obtained supervisors are still optimal and structurally minimal. Finally, numerical tests are conducted to show the efficiency and effectiveness of the proposed methods.
Xu Zhai - One of the best experts on this subject based on the ideXlab platform.
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Analysis and Determination of Associated Linkage, Redundant Constraint, and Degree of Freedom of Closed Mechanisms With Redundant Constraints and/or Passive Degree of Freedom
Journal of Mechanical Design, 2012Co-Authors: Lu Yang, Bingyi Mao, Xu ZhaiAbstract:The relations among the associated linkages (ALs), the Redundant Constraints, the passive degree of freedom (DoF), and the degree of freedom are studied systematically for the type synthesis of the closed mechanisms in this paper. First, the kinematic pairs with multidegree of freedoms are formed by combination of the basic joints with single degree of freedom in series, and the formulae are derived for the calculation of the degree of freedoms of the associated linkages, the number of the basic joints, and the valid numbers of the basic links in the associated linkages. Second, many different associated linkages and the number of basic links are derived, and the relations among the associated linkages, the Redundant Constraints, the passive degree of freedom, and the degree of freedoms of the closed mechanisms are analyzed. Third, some topology graphs are derived and the relative closed mechanisms with the Redundant Constraints and the passive degree of freedom are synthesized. Finally, the Redundant Constraints and the degree of freedoms of the closed mechanisms are determined.
Lu Y - One of the best experts on this subject based on the ideXlab platform.
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relation of associated linkage and Redundant Constraint of closed mechanisms
Journal of Yanshan University, 2013Co-Authors: Lu YAbstract:It has been a significant issue to synthesize novel mechanisms with Redundant Constraints and passive DoF.The relations of the associated linkages,the Redundant Constraints are studied systematically for the type synthesis of the closed mechanisms in this paper.Firstly,the kinematic pairs with multi-degree of freedoms are formed by combination of the basic joints with single degree of freedom in series,and the formulae are derived for the calculation of the degree of freedoms of the associated linkages,the number of the basic joints and the valid numbers of the basic links in the associated linkages.Secondly,many different associated linkages and the number of basic links are derived,and the relations among the associated linkages,the Redundant Constraints of the closed mechanisms are analyzed.The results of this research provide theoretical basic for type synthesis of mechanisms.
Vincent Charles - One of the best experts on this subject based on the ideXlab platform.
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an approach to find Redundant objective function s and Redundant Constraint s in multi objective nonlinear stochastic fractional programming problems
European Journal of Operational Research, 2010Co-Authors: Vincent Charles, A Udhayakumar, Rhymend V UthariarajAbstract:Structural redundancies in mathematical programming models are nothing uncommon and nonlinear programming problems are no exception. Over the past few decades numerous papers have been written on redundancy. Redundancy in Constraints and variables are usually studied in a class of mathematical programming problems. However, main emphasis has so far been given only to linear programming problems. In this paper, an algorithm that identifies Redundant objective function(s) and Redundant Constraint(s) simultaneously in multi-objective nonlinear stochastic fractional programming problems is provided. A solution procedure is also illustrated with numerical examples. The proposed algorithm reduces the number of nonlinear fractional objective functions and Constraints in cases where redundancy exists.