scholarly journals On the optimal design of biased contests

2020 ◽  
Vol 15 (4) ◽  
pp. 1435-1470 ◽  
Author(s):  
Qiang Fu ◽  
Zenan Wu
Keyword(s):  
Optimal Design ◽  
General Setting ◽  
Programming Approach ◽  
Objective Functions ◽  
Equilibrium Solutions ◽  
Design Problems ◽  
Playing Field ◽  
Alternative Approach ◽  
Broad Array ◽  
Contest Design

This paper explores the optimal design of biased contests. A designer imposes an identity‐dependent treatment on contestants that varies the balance of the playing field. A generalized lottery contest typically yields no closed‐form equilibrium solutions, which nullifies the usual implicit programming approach to optimal contest design and limits analysis to restricted settings. We propose an alternative approach that allows us to circumvent this difficulty and characterize the optimum in a general setting under a wide array of objective functions without solving for the equilibrium explicitly. Our technique applies to a broad array of contest design problems, and the analysis it enables generates novel insights into incentive provisions in contests and their optimal design. For instance, we demonstrate that the conventional wisdom of leveling the playing field, which is obtained in limited settings in previous studies, does not generally hold.

Process Optimal Design in Forging by Genetic Algorithm

2002 ◽  
Vol 124 (2) ◽  
pp. 397-408 ◽  
Author(s):  
J. S. Chung ◽  
S. M. Hwang
Keyword(s):  
Genetic Algorithm ◽  
Optimal Design ◽  
Process Design ◽  
Process Model ◽  
Hot Forging ◽  
Objective Functions ◽  
Optimal Design Problem ◽  
Design Problems ◽  
Design Iteration ◽  
Design Variables

A genetic algorithm based approach is presented for process optimal design in forging. In this approach, the optimal design problem is formulated on the basis of the integrated thermo-mechanical finite element process model so as to cover diverse design variables and objective functions, and a genetic algorithm is adopted for conducting design iteration for optimization. The process model, the formulation for process optimal design, and the genetic algorithm are described in detail. The approach is applied to several selected process design problems in cold and hot forging.

Multi-Objective Design Problem of Tire Wear and Visualization of Its Pareto Solutions2

2006 ◽  
Vol 34 (3) ◽  
pp. 170-194 ◽  
Author(s):  
M. Koishi ◽  
Z. Shida
Keyword(s):  
Inverse Problems ◽  
Conceptual Design ◽  
Dimensional Space ◽  
Design Stage ◽  
Objective Functions ◽  
Pareto Solutions ◽  
Design Problems ◽  
Multi Objective ◽  
Design Engineers ◽  
Design Variables

Abstract Since tires carry out many functions and many of them have tradeoffs, it is important to find the combination of design variables that satisfy well-balanced performance in conceptual design stage. To find a good design of tires is to solve the multi-objective design problems, i.e., inverse problems. However, due to the lack of suitable solution techniques, such problems are converted into a single-objective optimization problem before being solved. Therefore, it is difficult to find the Pareto solutions of multi-objective design problems of tires. Recently, multi-objective evolutionary algorithms have become popular in many fields to find the Pareto solutions. In this paper, we propose a design procedure to solve multi-objective design problems as the comprehensive solver of inverse problems. At first, a multi-objective genetic algorithm (MOGA) is employed to find the Pareto solutions of tire performance, which are in multi-dimensional space of objective functions. Response surface method is also used to evaluate objective functions in the optimization process and can reduce CPU time dramatically. In addition, a self-organizing map (SOM) proposed by Kohonen is used to map Pareto solutions from high-dimensional objective space onto two-dimensional space. Using SOM, design engineers see easily the Pareto solutions of tire performance and can find suitable design plans. The SOM can be considered as an inverse function that defines the relation between Pareto solutions and design variables. To demonstrate the procedure, tire tread design is conducted. The objective of design is to improve uneven wear and wear life for both the front tire and the rear tire of a passenger car. Wear performance is evaluated by finite element analysis (FEA). Response surface is obtained by the design of experiments and FEA. Using both MOGA and SOM, we obtain a map of Pareto solutions. We can find suitable design plans that satisfy well-balanced performance on the map called “multi-performance map.” It helps tire design engineers to make their decision in conceptual design stage.

Optimal design of 6-DOF eclipse mechanism based on task-oriented workspace

Robotica ◽  
2011 ◽  
Vol 30 (7) ◽  
pp. 1041-1048 ◽  
Author(s):  
Donghun Lee ◽  
Jongwon Kim ◽  
TaeWon Seo
Keyword(s):  
Optimal Design ◽  
Unit Length ◽  
Numerical Procedure ◽  
Design Procedure ◽  
Mass Reduction ◽  
Objective Functions ◽  
Design Efficiency ◽  
Task Oriented ◽  
Structural Mass ◽  
Optimal Set

SUMMARYWe present a new numerical optimal design for a redundant parallel manipulator, the eclipse, which has a geometrically symmetric workspace shape. We simultaneously consider the structural mass and design efficiency as objective functions to maximize the mass reduction and minimize the loss of design efficiency. The task-oriented workspace (TOW) and its partial workspace (PW) are considered in efficiently obtaining an optimal design by excluding useless orientations of the end-effector and by including just one cross-sectional area of the TOW. The proposed numerical procedure is composed of coarse and fine search steps. In the coarse search step, we find the feasible parameter regions (FPR) in which the set of parameters only satisfy the marginal constraints. In the fine search step, we consider the multiobjective function in the FPR to find the optimal set of parameters. In this step, fine search will be kept until it reaches the optimal set of parameters that minimize the proposed objective functions by continuously updating the PW in every iteration. By applying the proposed approach to an eclipse-rapid prototyping machine, the structural mass of the machine can be reduced by 8.79% while the design efficiency is increased by 6.2%. This can be physically interpreted as a mass reduction of 49 kg (the initial structural mass was 554.7 kg) and a loss of 496 mm3/mm in the workspace volume per unit length. The proposed optimal design procedure could be applied to other serial or parallel mechanism platforms that have geometrically symmetric workspace shapes.

scholarly journals Application of the Fuel-Optimal Energy Management in Design Study of a Parallel Hybrid Electric Vehicle

2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
Author(s):  
Afshin Pedram Pourhashemi ◽  
S. M. Mehdi Ansarey Movahed ◽  
Masoud Shariat Panahi
Keyword(s):  
Optimal Design ◽  
Energy Management ◽  
Management Strategy ◽  
Hybrid Electric Vehicle ◽  
Performance Metrics ◽  
Design Parameters ◽  
Programming Approach ◽  
Energy Management Strategy ◽  
Dynamic Programming Approach ◽  
Dynamic Measures

In spite of occasional criticism they have attracted, hybrid vehicles (HVs) have been warmly welcomed by industry and academia alike. The key advantages of an HV, including fuel economy and environment friendliness, however, depend greatly on its energy management strategy and the way its design parameters are “tuned.” The optimal design and sizing of the HV remain a challenge for the engineering community, due to the variety of criteria and especially dynamic measures related to nature of its working conditions. This paper proposes an optimal design scheme that begins with presenting an energy management strategy based on minimum fuel consumption in finite driving cycle horizon. The strategy utilizes a dynamic programming approach and is consistent with charge sustenance. The sensitivity of the vehicle’s performance metrics to multiple design parameters is then studied using a design of experiments (DOE) methodology. The proposed scheme provides the designer with a reliable tool for investigating various design scenarios and achieving the optimal one.

UNCERTAINTY BASED ROBUST OPTIMIZATION IN AERODYNAMICS

2009 ◽  
Vol 23 (03) ◽  
pp. 477-480 ◽  
Author(s):  
ZHILI TANG
Keyword(s):  
Nash Equilibrium ◽  
Robust Design ◽  
Single Point ◽  
Optimization Method ◽  
Equilibrium Solutions ◽  
Design Problems ◽  
Nash Equilibrium Solutions ◽  
Definition Of ◽  
Taguchi Robust Design ◽  
Statistical Definition

The Taguchi robust design concept is combined with the multi-objective deterministic optimization method to overcome single point design problems in Aerodynamics. Starting from a statistical definition of stability, the method finds, Nash equilibrium solutions for performance and its stability simultaneously.

A Fuzzy Adaptive Simplex Search Optimization Algorithm

1999 ◽  
Author(s):  
Mohamed B. Trabia ◽  
Xiao Bin Lu
Keyword(s):  
Fuzzy Logic ◽  
Optimization Algorithms ◽  
Test Problems ◽  
Objective Functions ◽  
Fuzzy Logic Controllers ◽  
Design Problems ◽  
Simplex Search ◽  
Search Optimization ◽  
Engineering Design Problems ◽  
Fuzzy Adaptive

Abstract Optimization algorithms usually use fixed parameters that are empirically chosen to reach the minimum for various objective functions. This paper shows how to incorporate fuzzy logic in optimization algorithms to make the search adaptive to various objective functions. This idea is applied to produce a new algorithm for minimization of a function of n variables using an adaptive form of the simplex method. The search starts by generating a simplex with n+1 vertices. The algorithm replaces the point with the highest function value by a new point. This process comprises reflecting the point with the highest function value in addition to expanding or contracting the simplex using fuzzy logic controllers whose inputs incorporate the relative weights of the function values at the simplex points. The efficiency of the algorithm is studied using a set of standard minimization test problems. This algorithm generally results in a faster convergence toward the minimum. The algorithm is also applied successfully to two engineering design problems.

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