Complex Housing: Modelling and Optimization Using an Improved Multi-Objective Simulated Annealing Algorithm

2016 ◽  
Author(s):  
Pei Cao ◽  
Zhaoyan Fan ◽  
Robert Gao ◽  
Jiong Tang
Keyword(s):  
Simulated Annealing ◽  
Optimization Problem ◽  
Simulated Annealing Algorithm ◽  
Line Length ◽  
Multi Objective ◽  
Hard Constraints ◽  
Improved Performance ◽  
The Mathematical Model ◽  
Complex Housing

This research concerns the complex housing optimization problem encountered in engineering design, where the volume in space occupied by components need to be minimized along with other objectives and constraints. Since in real applications the constraints are usually complex, the formulation of computationally tractable optimization becomes challenging. In this research, we first develop the mathematical model of such optimization problem, then propose two versions of an improved multi-objective simulated annealing (MOSA) approach towards the design optimization, i.e., optimizing the placement of cylinders under prescribed constraints to minimize the volume occupied, and the estimated plumbing line length. Our case study indicates that the new MOSA algorithm has improved performance towards complex housing with hard constraints and the design can indeed be automated. The outcome of this research may benefit both existing manufacturing practice and future additive manufacturing.

Multi-Objective Optimal Design of Sandwich Composite Laminates Using Simulated Annealing and FEM

2008 ◽  
Author(s):  
A. Sarhadi ◽  
M. Tahani ◽  
F. Kolahan ◽  
M. Sarhadi
Keyword(s):  
Simulated Annealing ◽  
Optimal Design ◽  
Composite Laminates ◽  
Composite Structures ◽  
Simulated Annealing Algorithm ◽  
Core Layer ◽  
Sandwich Composite ◽  
Surface Layers ◽  
Multi Objective ◽  
Aspect Ratios

Multi-objective optimal design of sandwich composite laminates consisting of high stiffness and expensive surface layers and low-stiffness and inexpensive core layer is addressed in this paper. The object is to determine ply angles and number of surface layers and core thickness in such way that natural frequency is maximized with minimal material cost and weight. A simulated annealing algorithm with finite element method is used for simultaneous cost and weight minimization and frequency maximization. The proposed procedure is applied to Graphite-Epoxy/Glass-Epoxy and Graphite-epoxy/Aluminum sandwich laminates and results are obtained for various boundary conditions and aspect ratios. Results show that this technique is useful in designing of effective, competitive and light composite structures.

scholarly journals Multi Objective Simulated Annealing Approach for Facility Layout Design

2018 ◽  
Vol 3 (4) ◽  
pp. 365-380 ◽  
Author(s):  
Safiye Turgay
Keyword(s):  
Simulated Annealing ◽  
Objective Function ◽  
Material Handling ◽  
Simulated Annealing Algorithm ◽  
Facility Layout ◽  
Layout Design ◽  
Local Optima ◽  
Facility Layout Design ◽  
Multi Objective ◽  
Annealing Algorithm

Facility layout design problem considers the departments’ physcial layout design with area requirements in some restrictions such as material handling costs, remoteness and distance requests. Briefly, facility layout problem related to optimization of the layout costs and working conditions. This paper proposes a new multi objective simulated annealing algorithm for solving of the unequal area in layout design. Using of the different objective weights are generated with entropy approach and used in the alternative layout design. Multi objective function takes into the objective function and constraints. The suggested heuristic algorithm used the multi-objective parameters for initialization. Then prefered the entropy approach determines the weight of the objective functions. After the suggested improved simulated annealing approach applied to whole developed model. A multi-objective simulated annealing algorithm is implemented to increase the diversity and reduce the chance of getting layout conditions in local optima.

scholarly journals A Knowledge-Based Simulated Annealing Algorithm to Multiple Satellites Mission Planning Problems

2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Da-Wei Jin ◽  
Li-Ning Xing
Keyword(s):  
Simulated Annealing ◽  
Optimization Problem ◽  
Simulated Annealing Algorithm ◽  
Mission Planning ◽  
Knowledge Based ◽  
Combination Optimization ◽  
Annealing Algorithm ◽  
The Given ◽  
Planning Problems ◽  
Annealing Method

The multiple satellites mission planning is a complex combination optimization problem. A knowledge-based simulated annealing algorithm is proposed to the multiple satellites mission planning problems. The experimental results suggest that the proposed algorithm is effective to the given problem. The knowledge-based simulated annealing method will provide a useful reference for the improvement of existing optimization approaches.

Solving a multi-objective multi-depot stochastic location-routing problem by a hybrid simulated annealing algorithm

2009 ◽  
Vol 223 (8) ◽  
pp. 1045-1054 ◽  
Author(s):  
H A Hassan-Pour ◽  
M Mosadegh-Khah ◽  
R Tavakkoli-Moghaddam
Keyword(s):  
Simulated Annealing ◽  
Large Scale ◽  
Simulated Annealing Algorithm ◽  
Genetic Operators ◽  
Location Routing Problem ◽  
Routing Problem ◽  
Multi Objective ◽  
Location Routing ◽  
Proposed Model ◽  
Stochastic Location

This paper presents a novel mathematical model for a stochastic location-routing problem (SLRP) that minimizes the facilities establishing cost and transportation cost, and maximizes the probability of delivery to customers. In this proposed model, new aspects of a location-routing problem (LRP), such as stochastic availability of facilities and routes, are developed that are similar to real-word problems. The proposed model is solved in two stages: (i) solving the facility location problem (FLP) by a mathematical algorithm and (ii) solving the multi-objective multi-depot vehicle routing problem (MO-MDVRP) by a simulated annealing (SA) algorithm hybridized by genetic operators, namely mutation and crossover. The proposed SA can find good solutions in a reasonable time. It solves the proposed model in large-scale problems with acceptable results. Finally, a trade-off curve is used to depict and discuss a large-sized problem. The associated results are compared with the results obtained by the lower bound and Lingo 8.0 software.

Multi-Objective Optimization Design of Screw Conveyor Using Genetic Algorithm

2013 ◽  
Vol 732-733 ◽  
pp. 402-406
Author(s):  
Duan Yi Wang
Keyword(s):  
Genetic Algorithm ◽  
Mathematical Model ◽  
Optimization Design ◽  
Optimization Problem ◽  
Machine Design ◽  
Screw Conveyor ◽  
Optimized Design ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
The Mathematical Model

The weight minimum and drive efficiency maxima1 of screw conveyor were considered as double optimizing objects in this paper. The mathematical model of the screw conveyor has been established based on the theory of the machine design, and the genetic algorithm was adopted to solving the multi-objective optimization problem. The results show that the mass of spiral shaft reduces 13.6 percent, and the drive efficiency increases 6.4 percent because of the optimal design based on genetic algorithm. The genetic algorithm application on the screw conveyor optimized design can provided the basis for designing the screw conveyor.

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