In this paper, an efficient extension of network SIMPLEX ALGORITHM is presented. In static scheduling problem, where there is no change in situation, the challenge is that the large problems can be solved in a short time. In this paper, the Static Scheduling problem of Automated Guided Vehicles in container terminal is solved by Network SIMPLEX ALGORITHM (NSA) and NSA+, which extended the standard NSA. The ALGORITHMs are based on graph model and their performances are at least 100 times faster than traditional SIMPLEX ALGORITHM for Linear Programs. Many random data are generated and fed to the model for 50 vehicles. We compared results of NSA and NSA+ for the static automated vehicle scheduling problem. The results show that NSA+ is significantly more efficient than NSA. It is found that, in practice, NSA and NSA+ take polynomial time to solve problems in this application.

In static scheduling problem, where there is no change in situation, the challenge is that the large problems can be solved in a short time. In this paper, the Static Scheduling problem of Automated Guided Vehicles in container terminal is solved by the Network SIMPLEX ALGORITHM (NSA). The ALGORITHM is based on graph model and their performances are at least 100 times faster than traditional SIMPLEX ALGORITHM for Linear Programs. Many random data are generated and fed to the model for 50 vehicles. The results show that NSA is fast and efficient. It is found that, in practice, NSA takes polynomial time to solve problems in this application.

In the real world, in most cases, such as industry, management, and even in daily life, we encounter optimization and decision-making problems that require the opinions of experts and masters on the problem to be able to make the best decision. In these cases, it is necessary to use an optimization problem with hesitant fuzzy parameters.There are few studies on hesitant fuzzy linear programming (HFLP) problems. Therefore,in this paper, we  consider such problems.Especially, we study HFLP problems with hesitant cost coefficients. For this purpose,we propose the SIMPLEX  method to solve the introduced optimization problems and draw a flowchart of the proposed  method.Finally, by solving two illustrative examples with hesitant fuzzy information, we examine the applicability of the proposed method.

Presents article is deal with optimization of the fixture for end milling process, the most important objective being the minimization of work piece deformation by changing the layout of fixture elements and the clamping forces. The main objective of this work has been the optimization of the fixtures Work piece deformation subjected to clamping forces for End milling operation. The present analysis is used in hollow rectangular isotropic material work piece for FEA analysis and its optimization A linear programing (L. P) SIMPLEX model optimization activity has been performed both on fixture-work piece systems modeled with FEM and on fixture-work piece systems modeled with 3-D solid elements. The optimization constraints is selected as W/P deformation in x, y, z direction for various clamping forces, in order to provide a new design of fixture. The MATLAB code has been developed for L. P. model optimization purpose. Present MATLAB code is validated by using available literature. This paper deals with application of the L. P. model for w/p deformation optimization for a accommodating work piece. A SIMPLEX iterative ALGORITHM that minimizes the work piece elastic deformation for the entire clamping force is proposed. It is shown via an example of milling fixture design that this ALGORITHM yields a design that is superior to the result obtained from either fixture layout or w/p deformation optimization alone.

It is well known that in operations research, degeneracy can cause a cycle in a network SIMPLEX ALGORITHM which can be prevented by maintaining strong feasible bases in each pivot. Also, in a network consists of n arcs and m nodes, not considering any new conditions on the entering variable, the upper bound of consecutive degenerate pivots is equal…

In this paper a hybrid ALGORITHM based on exploration power of the Genetic ALGORITHMs and exploitation capability of Nelder Mead SIMPLEX is presented for global optimization of multivariable functions. Some modifications are imposed on genetic ALGORITHM to improve its capability and efficiency while being hybridized with SIMPLEX method. Benchmark test examples of structural optimization with a large number of variables and constraints are chosen to show the robustness of the ALGORITHM.

The standard model capacitated facility location (CPLP / CWLP) to locate the facility on a network of customer demand until total cost of the allocation minimize. The purposes of this paper cover all the demands of specified number of facilities to reduce the cost. In this paper closer to the real world, parameters of model is fuzzy and objective function is multi objective at the same time the total establishment cost and travel time is minimized in accordance with the constraints. The innovation is combining hybrid fuzzy SIMPLEX with genetic ALGORITHM approach to accelerate near optimization process to change multi-objective to a single objective with LP metric. Simulated annealing ALGORITHM also compared to reflect significant differences in performance and response time. Its application in locating facilities include warehouses, factories and services sector.

in this paper, a linear programming problem is considered involving interval grey numbers as an extension of the classical linear programming problem to an inexact environment as well as fuzzy and stochastic environment. Hence, here a new approach for solving interval grey number linear programming problems is introduced without converting them to classical linear programming problems. The proposed method is established based on the primal SIMPLEX ALGORITHM where the cost coefficient row includes grey numbers. As an essential tool in the solving process, a theoretical discussion on grey arithmetic and in particular an ordering role for grey numbers is necessary to evaluate the optimality conditions of a candidate feasible solution. It is also emphasized that the discussed model and the solution process is useful for real situations and practical cases, when a kind of the grey number linear programming is appeared, such as Water Resource Management and Planning, Economics, etc. Finally, the proposed approach is illustrated by a numerical example.

Using linear programming method in control allocation for attitude control subsystem of spacecraft with redundant thrusters is studied in this paper. The SIMPLEX ALGORITHM is utilized as a solver and the Direction Preserving and Bodson’ s Reduced size Direction preserving approaches are used as optimal approaches to deal with non admissible solutions. Also, proper functioning of these approaches against thrusters fault phenomenon is evaluated. The results show that the Direction Preserving approache has less computational time and less fuel consuming. However, the Bodson’ s Reduced size Direction preserving approache has more computational time and more fuel consuming but less tri-axis tracking error. It should be noted that the PD controller has been used as a spacecraft control rule, and simulations have been made for the number and configuration of the specific thrusters.