Non Linear Programming
ABC inventory classification withmultiple-criteria using weighted non-linear programming
... To have an efficient control of a huge amount of inventory items, traditional approach is toclassify the inventory into different groups. Different inventory control policies can thenapplied to different groups. The ...
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Analysis of Fuzzy Non Preemptive Priority Queue using Non-Linear Programming Approach
... in non preemptive priority queuing model with priority subscribers where the arrival rate and service rate are ...of non -linear programming programs is ...
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Intuitionistic Fuzzy Multi-Objective Non Linear Programming Problem (IFMONLPP) Using Taylor Series Approach
... by non- linear programming techniques are in fact more ...by non-linear programming ...mathematical programming methods and many significant advances have been made in the ...
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Public Cryptography Linear and Non Linear Programming Solver in Cloud Computing
... In this paper, for the first time, we formalize the problem of securely outsourcing LP computations in cloud computing, and provide such practical mechanism design which fulfills input/output privacy,cheating resilience, ...
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Effect of linear and random non-linear programming on environmental pollution caused by broiler production
... including linear programming (LP50, LP69) and random non-linear programming diets (SP69, SP95, SP99 ...random non-linear programming method had significant effect ...
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An Innovative Genetic Algorithms Based Inexact Non Linear Programming Problem Solving Method
... Quadratic programming problems are specific cases of non-linear programming problems ...the non-linear structure, and the inexact information embedded in the structure, most ...
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A Non linear Programming Model for the Machine Grouping and a Genetic Algorithm based Solution Methodology
... A non-linear integer programming model for the design of manufacturing cells is proposed in this paper to minimize the heterogeneity of cells formed for the given part-machine incidence ...
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On the optimization of Dombi non-linear programming
... a non- linear optimization problem in which the constraints are de- fined as fuzzy relational equations (FRE) with the Dombi family of ...is non-convex, conventional nonlinear programming ...
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Application of Non Linear Programming to Locomotive Optimisation: A Case Study of National Railway of Zimbabwe
... Abstract This paper analysed activities undertaken in optimizing locomotive utilisation at National Railways of Zimbabwe (NRZ). Failure to attain breakeven and meet set targets is associated with underutilising resource ...
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Adaptive mesh-free lower bound limit analysis using non-linear programming
... An adaptive mesh-free lower bound limit analysis formulation was proposed for the prediction of limit loads in soil mechanics problems under plane strain condition. In the presented approach, the lower bound theorem of ...
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ON Fuzzy Linear Programming Technique Application
... In the proposed approach fuzzy linear programming model is introduced to the machine scheduling problem based on fuzzy constraints and fuzzy objective function. Here the demand constraints for each product ...
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Solving fully fuzzy linear programming
... T h metic operations were first introduced by e concept of fuzzy numbers and fuzzy arith- Zadeh [36], Dubois et al. [12]. We refer the reader to [22, 10] for more information on fuzzy numbers and fuzzy arithmetic. Fuzzy ...
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On Optimization Criteria of Fuzzy Linear Programming
... the linear problem is proved in the fuzzy domain. Through fuzzy linear theorems of the alternative, we get the optimization criteria for linear problems in the fuzzy case, thus the optimization of ...
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Sensitivity analysis and uncertainty in linear programming
... Most authors of textbooks on LP discuss the need for sensitivity analysis (SA). In analyzing output, researchers use SA to explore how changes in the problem data might change the solution to a linear program, for ...
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Linear Programming Model of Sensor Network
... , “Expander graph based key distribution mechanisms in wireless sensor networks.”, In Proceedings of IEEE International Conference on Communications (ICC), 2006... , “PIKE: peer interm[r] ...
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Actual and Shadow Prices in Linear Programming
... Transition from basis to basis until the optimal basis is reached is effected by changing variables one at a time, symbolically variable numbered k previously with value zero comes into [r] ...
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Integer Linear Programming for Discourse Parsing
... use MST decoding over local probability distribu- tions, this meant that their implementation had in- herent limitations because it is limited to producing tree structures. They also used the turn constraint, but imposed ...
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The Sliding Gradient Algorithm for Linear Programming
... The existence of strongly polynomial algorithm for linear programming (LP) has been widely sought after for decades. Recently, a new approach called Gravity Sliding algorithm [1] has emerged. It is a ...
20
Multiobjective Stochastic Linear Programming: An Overview
... There is a rich array of methods that can be used to deal with both Multiobjective Programming and Stochas- tic Programming problems. This paper has somewhat demonstrated that, the Howards view applies to ...
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Linear fractional programming for fuzzy random based possibilistic programming problem
... mathematical programming model though handling such uncertainties in the decision making model increases the complexities of the problem and make the solution of the problem ...a linear fractional ...
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