A Simple, Standard Linear Programming Scenario

1969 ◽  
Vol 91 (3) ◽  
pp. 799-806 ◽  
Author(s):  
F. A. Leckie ◽  
R. K. Penny

Using the theorems of plasticity lower bound estimates of shakedown loadings have been calculated for a number of shell-like structures commonly found in the pressure vessel industry. These have been determined by making use of elastic solutions, already available, in conjunction with standard linear programming techniques. Combinations of loadings and temperatures have been considered with a view to illustrating how calculations of these types can help in making design decisions.


2017 ◽  
Vol 2017 ◽  
pp. 1-9
Author(s):  
Shu-Cheng Lin ◽  
Han-Wen Tuan ◽  
Peterson Julian

We examined the solution process for linear programming problems under a fuzzy and random environment to transform fuzzy stochastic goal programming problems into standard linear programming problems. A previous paper that revised the solution process with the lower-side attainment index motivated our work. In this paper, we worked on a revision for both-side attainment index to amend its definition and theorems. Two previous examples were used to examine and demonstrate our improvement over previous results. Our findings not only improve the previous paper with both-side attainment index, but also provide a theoretical extension from lower-side attainment index to the both-side attainment index.


Author(s):  
Y. X. Chu ◽  
J. B. Gou ◽  
Z. X. Li

Abstract The problem of aligning the CAD model of a workpiece such that all points measured on the finished surfaces of the workpiece match closely to corresponding surfaces on the model while all unmachined surfaces lie outside the model to guarantee the presence of material to be machined at a later time is referred to as the hybrid localization/envelopment problem. The hybrid problem has important applications in setting up for machining of partially finished workpieces. This paper gives a formulation of the hybrid localization/envelopment problem and present a geometric algorithm for computing its solutions. First, we show that when the finished surfaces of a workpiece are inadequate to fully constrain the rigid motions of the workpiece, then the set of free motions remaining must form a subgroup G0 of the Euclidean group SE(3). This allows us to decompose the hybrid problem into a (symmetric) localization problem on the homogeneous space SE(3)/G0 and an envelopment problem on G0. While the symmetric localization problem is solved using the Fast Symmetric Localization (FSL) algorithm developed in one of our early papers, the envelopment problem is solved by computing the solutions of a sequence of linear programming (LP) problems. We derive explicitly the LP problems and apply standard linear programming techniques to solve the LP problems. We present simulation results to demonstrate efficiency of our method for the hybrid problem.


2011 ◽  
Vol 14 (3) ◽  
pp. 63 ◽  
Author(s):  
John E. Burnett ◽  
Bruce M. Wampler

<span>A general analytical framework within which to solve the competitive bidding problem is developed by considering a unit price contract. By viewing the problem in the standard capital budgeting framework and exploiting the linearity of the firms objective function and constraints, the problem can be formulated as a standard linear programming (LP) application whose solution is the optimal bid. We also investigate a so-called unbalanced bidding strategy as an effective way for bidding firms to hedge the risk, or uncertainty, inherent in may unit price contracts.</span>


2014 ◽  
Vol 2014 ◽  
pp. 1-13
Author(s):  
Xiang Li ◽  
Mohammad Reza Bonyadi ◽  
Zbigniew Michalewicz ◽  
Luigi Barone

This paper presents a hybrid evolutionary algorithm to deal with the wheat blending problem. The unique constraints of this problem make many existing algorithms fail: either they do not generate acceptable results or they are not able to complete optimization within the required time. The proposed algorithm starts with a filtering process that follows predefined rules to reduce the search space. Then the linear-relaxed version of the problem is solved using a standard linear programming algorithm. The result is used in conjunction with a solution generated by a heuristic method to generate an initial solution. After that, a hybrid of an evolutionary algorithm, a heuristic method, and a linear programming solver is used to improve the quality of the solution. A local search based posttuning method is also incorporated into the algorithm. The proposed algorithm has been tested on artificial test cases and also real data from past years. Results show that the algorithm is able to find quality results in all cases and outperforms the existing method in terms of both quality and speed.


2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Yu Xu ◽  
Lin Xiao ◽  
Dingcheng Yang ◽  
Laurie Cuthbert ◽  
Yapeng Wang

Wireless communications with unmanned aerial vehicles (UAVs) is a promising technology offering potential high mobility and low cost. This paper studies a UAV-enabled communication system, in which a fixed-wing UAV is deployed to collect information from a group of distributed ground terminals (GTs). Considering the requirements for quality of service (QoS) (i.e., the throughput of each GT is above a given threshold) and GT scheduling, we maximize the energy efficiency (EE) of the UAV in bits/Joule by optimizing the UAV’s flight trajectory. In this paper, a mixed integer nonconvex optimization problem is formulated. As that is difficult to solve, we divide the formulated problem into two subproblems and apply standard linear programming (LP) and successive convex optimization techniques. We further propose an efficient iterative algorithm that jointly optimizes GT scheduling and the UAV’s trajectory. Moreover, we set two special cases as benchmarks to measure the performance of the proposed design. The numerical results show that our proposed design achieves much better performance than the other two benchmark designs.


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