scholarly journals GIS Spatial Optimization for Corridor Alignment Using Simulated Annealing

2020 ◽  
Vol 10 (18) ◽  
pp. 6190
Author(s):  
Marco Antonio Cruz-Chávez ◽  
Pedro Moreno-Bernal ◽  
Rafael Rivera-López ◽  
Erika Yesenia Ávila-Melgar ◽  
Beatriz Martínez-Bahena ◽  
...  
Keyword(s):  
Simulated Annealing ◽  
Transmission Lines ◽  
Optimization Problem ◽  
Variable Interval ◽  
Spatial Optimization ◽  
Planning Problem ◽  
Continuous Space ◽  
Corridor Planning ◽  
Neighborhood Method ◽  
New Facilities

Planning corridors for new facilities such as pipeline or transmission lines through geographical spaces is a topographical constraint optimization problem. The corridor planning problem requires finding an optimal route or a set of alternative paths between two locations. This article presents a simulated-annealing-based (SA) approach applying a variable neighborhood strategy in a continuous space to generate competitive and different alternative paths to solve the corridor planning problem. The variable neighborhood method randomly selects two points from a variable interval of the current solution generated by SA creating pseudo-random paths inside a corridor and finding spatially different alternatives. The proposed approach is evaluated with three practical problems using real topographic data from the Veracruz Basin in Mexico. The experimental results show that this approach obtains efficient and competitive solutions with improvements above 18% over those gotten by the compared method.

A Cooperative Simulated Annealing Algorithm for the Optimization of Process Planning

2011 ◽  
Vol 181-182 ◽  
pp. 489-494 ◽  
Author(s):  
Kun Lei Lian ◽  
Chao Yong Zhang ◽  
Liang Gao ◽  
Shao Tan Xu ◽  
Yi Sun
Keyword(s):  
Simulated Annealing ◽  
Process Planning ◽  
Optimization Problem ◽  
Simulated Annealing Algorithm ◽  
Manufacturing Cost ◽  
Planning Problem ◽  
Optimization Strategy ◽  
Computer Aided Process Planning ◽  
Operations Sequencing ◽  
Annealing Algorithm

Process planning is an essential component of computer aided process planning (CAPP), which involves operations selection from design features and operations sequencing of these selected operations. It makes process planning a complex combinatorial optimization problem to conduct of these two steps simultaneously. In this paper, we propose a cooperative simulated annealing (CoSA) approach for the process planning problem to minimize total manufacturing cost. The proposed CoSA algorithm employed a novel optimization strategy different from all the existing approaches in the literature. Simulated annealing was utilized to optimize the four components of a process plan individually and sequentially. The approach is tested on two parts from the literature and compared with other approaches. The computation results validate the effectiveness of the proposed algorithm.

scholarly journals A simulated annealing-based algorithm for selecting balanced samples

2021 ◽  
Author(s):  
Roberto Benedetti ◽  
Maria Michela Dickson ◽  
Giuseppe Espa ◽  
Francesco Pantalone ◽  
Federica Piersimoni
Keyword(s):  
Simulated Annealing ◽  
Optimization Problem ◽  
Sample Selection ◽  
Auxiliary Information ◽  
Real Data ◽  
Simulation Experiments ◽  
Balanced Sampling ◽  
Inclusion Probabilities ◽  
Random Method ◽  
Annealing Algorithms

AbstractBalanced sampling is a random method for sample selection, the use of which is preferable when auxiliary information is available for all units of a population. However, implementing balanced sampling can be a challenging task, and this is due in part to the computational efforts required and the necessity to respect balancing constraints and inclusion probabilities. In the present paper, a new algorithm for selecting balanced samples is proposed. This method is inspired by simulated annealing algorithms, as a balanced sample selection can be interpreted as an optimization problem. A set of simulation experiments and an example using real data shows the efficiency and the accuracy of the proposed algorithm.

Trajectory Optimization Applied to Space Rendezvous

2013 ◽  
Vol 756-759 ◽  
pp. 3466-3470
Author(s):  
Xu Min Song ◽  
Qi Lin
Keyword(s):  
Simulated Annealing ◽  
Optimization Model ◽  
Trajectory Optimization ◽  
Optimization Problem ◽  
Optimization Method ◽  
Nonlinear Constraints ◽  
Design Variables ◽  
Adaptive Simulated Annealing ◽  
Simulation Results

The trajcetory plan problem of spece reandezvous mission was studied in this paper using nolinear optimization method. The optimization model was built based on the Hills equations. And by analysis property of the design variables, a transform was put forward , which eliminated the equation and nonlinear constraints as well as decreaseing the problem dimensions. The optimization problem was solved using Adaptive Simulated Annealing (ASA) method, and the rendezvous trajectory was designed.The method was validated by simulation results.

Design Optimization of an L-Shaped Extrusion Die

2009 ◽  
Author(s):  
Oktay Yilmaz ◽  
Hasan Gunes ◽  
Kadir Kirkkopru
Keyword(s):  
Simulated Annealing ◽  
Optimization Problem ◽  
Numerical Solutions ◽  
Latin Hypercube Sampling ◽  
Kriging Model ◽  
Narrow Channel ◽  
Geometric Parameters ◽  
Die Design ◽  
Dimensional Parameter ◽  
Large Channel

It is an important problem in the polymer extrusion of complex profiles to balance the flow at the die exit. In this paper, we employ simulated annealing-kriging meta-algorithm to optimize the geometric parameters of a die channel to obtain a uniform exit velocity distribution. Design variables for our optimization problem involve the suitable geometric parameters for the die design, which are the thickness of the large channel and the length of the narrow channel. Die balance is based on the deviation of the velocity with respect to the average velocity at the die exit. So the cost function for the optimization problem involves the minimization of this deviation. For the design of numerical experiments, we use Latin Hypercube Sampling (LHS) to construct the kriging model. Then, based on the LHS points, the numerical solutions are performed using Polyflow, a commercial software based on the finite element method and is specifically designed to simulate the flow and heat transfer of non-newtonian, viscoelastic fluids. In our simulations, a HDPE (high density polyethylene) is used as extrusion material. Having obtained numerical simulations for N = 60 LHS points in two-dimensional parameter space (t and L), the optimization of these parameters is carried out by Simulated Annealing (SA) method in conjunction with kriging model. We show that kriging model employed in SA algorithm can be used to optimize the die geometry.

scholarly journals Optimal design of a DC MHD pump by simulated annealing method

2014 ◽  
Vol 11 (2) ◽  
pp. 339-350
Author(s):  
Khadidja Bouali ◽  
Fatima Kadid ◽  
Rachid Abdessemed
Keyword(s):  
Simulated Annealing ◽  
Optimal Design ◽  
Objective Function ◽  
Design Problem ◽  
Design Methodology ◽  
Optimization Problem ◽  
Optimization Procedure ◽  
Simulated Annealing Method ◽  
Direct Interpretation ◽  
Annealing Method

In this paper a design methodology of a magnetohydrodynamic pump is proposed. The methodology is based on direct interpretation of the design problem as an optimization problem. The simulated annealing method is used for an optimal design of a DC MHD pump. The optimization procedure uses an objective function which can be the minimum of the mass. The constraints are both of geometrics and electromagnetic in type. The obtained results are reported.

scholarly journals Trajectory optimization of UAV based on Hp-adaptive Radau pseudospectral method

2021 ◽  
Vol 0 (0) ◽  
pp. 0
Author(s):  
Yi Cui ◽  
Xintong Fang ◽  
Gaoqi Liu ◽  
Bin Li
Keyword(s):  
Trajectory Planning ◽  
Trajectory Optimization ◽  
Optimization Problem ◽  
Tracking Error ◽  
Pseudospectral Method ◽  
Planning Problem ◽  
A Algorithm ◽  
Planning Scheme ◽  
Path Search ◽  
Simulation Results

<p style='text-indent:20px;'>Unmanned Aerial Vehicles (UAVs) have been extensively studied to complete the missions in recent years. The UAV trajectory planning is an important area. Different from the commonly used methods based on path search, which are difficult to consider the UAV state and dynamics constraints, so that the planned trajectory cannot be tracked completely. The UAV trajectory planning problem is considered as an optimization problem for research, considering the dynamics constraints of the UAV and the terrain obstacle constraints during flight. An hp-adaptive Radau pseudospectral method based UAV trajectory planning scheme is proposed by taking the UAV dynamics into account. Numerical experiments are carried out to show the effectiveness and superior of the proposed method. Simulation results show that the proposed method outperform the well-known RRT* and A* algorithm in terms of tracking error.</p>

AN IMPROVED HYBRID OPTIMIZATION ALGORITHM FOR THE QUADRATIC ASSIGNMENT PROBLEM

2005 ◽  
Vol 9 (2) ◽  
pp. 149-168 ◽  
Author(s):  
A. Misevičius
Keyword(s):  
Simulated Annealing ◽  
Tabu Search ◽  
Optimization Algorithm ◽  
Assignment Problem ◽  
Optimization Problem ◽  
Heuristic Algorithms ◽  
Quadratic Assignment Problem ◽  
Hybrid Optimization ◽  
Quadratic Assignment ◽  
Hybrid Optimization Algorithm

In this paper, we present an improved hybrid optimization algorithm, which was applied to the hard combinatorial optimization problem, the quadratic assignment problem (QAP). This is an extended version of the earlier hybrid heuristic approach proposed by the author. The new algorithm is distinguished for the further exploitation of the idea of hybridization of the well‐known efficient heuristic algorithms, namely, simulated annealing (SA) and tabu search (TS). The important feature of our algorithm is the so‐called “cold restart mechanism”, which is used in order to avoid a possible “stagnation” of the search. This strategy resulted in very good solutions obtained during simulations with a number of the QAP instances (test data). These solutions show that the proposed algorithm outperforms both the “pure” SA/TS algorithms and the earlier author's combined SA and TS algorithm. Key words: hybrid optimization, simulated annealing, tabu search, quadratic assignment problem, simulation.

Cooperative Task Assignment and Trajectory Planning of Unmanned Systems Via HFLC and PSO

2019 ◽  
Vol 07 (02) ◽  
pp. 65-81 ◽  
Author(s):  
Ahmed T. Hafez ◽  
Mohamed A. Kamel
Keyword(s):  
Trajectory Planning ◽  
Optimization Problem ◽  
Fuzzy Logic Controller ◽  
Hybrid Approach ◽  
Task Assignment ◽  
Time Discretization ◽  
Planning Problem ◽  
Dynamic Constraints ◽  
Ground Station ◽  
Novel Approach

This paper investigates the problems of cooperative task assignment and trajectory planning for teams of cooperative unmanned aerial vehicles (UAVs). A novel approach of hierarchical fuzzy logic controller (HFLC) and particle swarm optimization (PSO) is proposed. Initially, teams of UAVs are moving in a pre-defined formation covering a specified area. When one or more targets are detected, the teams send a package of information to the ground station (GS) including the target’s degree of threat, degree of importance, and the separating distance between each team and each detected target. Based on the gathered information, the ground station assigns the teams to the targets. HFLC is implemented in the GS to solve the assignment problem ensuring that each team is assigned to a unique target. Next, each team plans its own path by formulating the path planning problem as an optimization problem. The objective in this case is to minimize the time to reach their destination considering the UAVs dynamic constraints and collision avoidance between teams. A hybrid approach of control parametrization and time discretization (CPTD) and PSO is proposed to solve this optimization problem. Finally, numerical simulations demonstrate the effectiveness of the proposed algorithm.

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