A Simulated Annealing Approach for Minimum Cost Isolated Failure Immune Networks

2002 ◽  
pp. 169-183 ◽  
Author(s):  
Alfredo Candia ◽  
Hugo Bravo
Keyword(s):  
Simulated Annealing ◽  
Minimum Cost

A Hybrid Simulated Annealing and Simplex Method for Fixed-Cost Capacitated Multicommodity Network Design

2012 ◽  
pp. 17-31 ◽  
Author(s):  
Masoud Yaghini ◽  
Mohammad Karimi ◽  
Mohadeseh Rahbar ◽  
Rahim Akhavan
Keyword(s):  
Simulated Annealing ◽  
Network Design ◽  
Simplex Method ◽  
Minimum Cost ◽  
Parameter Tuning ◽  
Fixed Cost ◽  
Hybrid Simulated Annealing ◽  
Np Hard Problem ◽  
Multicommodity Network Design ◽  
Opening And Closing

The fixed-cost Capacitated Multicommodity Network Design (CMND) problem is a well known NP-hard problem. This paper presents a matheuristic algorithm combining Simulated Annealing (SA) metaheuristic and Simplex method for CMND problem. In the proposed algorithm, a binary array is considered as solution representation and the SA algorithm manages open and closed arcs. Several strategies for opening and closing arcs are proposed and evaluated. In this matheuristic approach, for a given design vector, CMND becomes a Capacitated Multicommodity minimum Cost Flow (CMCF) problem. The exact evaluation of the CMCF problem is performed using the Simplex method. The parameter tuning for the proposed algorithm is done by means of design of experiments approach. The performance of the proposed algorithm is evaluated by solving different benchmark instances. The results of the proposed algorithm show that it is able to obtain better solutions in comparison with previous methods in the literature.

A Hybrid Simulated Annealing and Simplex Method for Fixed-Cost Capacitated Multicommodity Network Design

2011 ◽  
Vol 2 (4) ◽  
pp. 13-28 ◽  
Author(s):  
Masoud Yaghini ◽  
Mohammad Karimi ◽  
Mohadeseh Rahbar ◽  
Rahim Akhavan
Keyword(s):  
Simulated Annealing ◽  
Network Design ◽  
Simplex Method ◽  
Minimum Cost ◽  
Parameter Tuning ◽  
Fixed Cost ◽  
Hybrid Simulated Annealing ◽  
Np Hard Problem ◽  
Multicommodity Network Design ◽  
Opening And Closing

The fixed-cost Capacitated Multicommodity Network Design (CMND) problem is a well known NP-hard problem. This paper presents a matheuristic algorithm combining Simulated Annealing (SA) metaheuristic and Simplex method for CMND problem. In the proposed algorithm, a binary array is considered as solution representation and the SA algorithm manages open and closed arcs. Several strategies for opening and closing arcs are proposed and evaluated. In this matheuristic approach, for a given design vector, CMND becomes a Capacitated Multicommodity minimum Cost Flow (CMCF) problem. The exact evaluation of the CMCF problem is performed using the Simplex method. The parameter tuning for the proposed algorithm is done by means of design of experiments approach. The performance of the proposed algorithm is evaluated by solving different benchmark instances. The results of the proposed algorithm show that it is able to obtain better solutions in comparison with previous methods in the literature.

Optimal Tolerance Allocation Over Multiple Manufacturing Alternatives

1992 ◽  
Author(s):  
Jonathan Cagan ◽  
Thomas R. Kurfess
Keyword(s):  
Simulated Annealing ◽  
Optimization Problem ◽  
Simulated Annealing Algorithm ◽  
Minimum Cost ◽  
Tolerance Allocation ◽  
Hyperbolic Function ◽  
Manufacturing Processes ◽  
Worst Case ◽  
Annealing Algorithm ◽  
Manufacturing Alternatives

Abstract We introduce a methodology for concurrent design that considers the allocation of tolerances and manufacturing processes for minimum cost. Cost is approximated as a hyperbolic function over tolerance, and worst-case stack-up tolerance is assumed. Two simulated annealing techniques are introduced to solve the optimization problem. The first assumes independent, unordered, manufacturing processes and uses a Monte-Carlo simulation; the second assumes well known individual process cost functions which can be manipulated to create a single continuous function of cost versus tolerance with discontinuous derivatives solved with a continuous simulated annealing algorithm. An example utilizing a system of friction wheels over the manufacturing processes of turning, grinding, and saw cutting bar stock demonstrates excellent results.

scholarly journals Pareto simulated annealing for the design of experiments: illustrated by a gene expression study

2012 ◽  
Vol 37 (3) ◽  
pp. 199-221 ◽  
Author(s):  
Penny Sanchez ◽  
Gary Glonek ◽  
Andrew Metcalfe
Keyword(s):  
Gene Expression ◽  
Simulated Annealing ◽  
Minimum Cost ◽  
Optimal Designs ◽  
Expression Study ◽  
Expression Studies ◽  
Optimal Values ◽  
Gene Expression Studies ◽  
And Performance ◽  
Pareto Simulated Annealing

Abstract Experimental design is concerned with the problem of allocating resources within an experiment to ensure that objectives of the experiment are achieved at the minimum cost. This paper focuses on the generation of optimal or near-optimal designs for large and complex experiments where it is infeasible to carry out an ex- haustive search of the design space. Optimal designs for gene expression studies, aimed at investigating the behaviour of genes, are considered, where the optimality criterion employed is Pareto optimality. We develop an adaptation of the metaheuris- tic method of Pareto simulated annealing to generate an approximation to the set of Pareto optimal designs for large and complex experiments. We develop algorithms that utilise response surface methodology to search systematically for the optimal values of parameters associated with Pareto simulated annealing and performance is evaluated using quality measures.

scholarly journals Optimization of substation grounding grid design for horizontal and vertical multilayer and uniform soil condition using Simulated Annealing method

PLoS ONE ◽  
2021 ◽  
Vol 16 (9) ◽  
pp. e0256298
Author(s):  
Navinesshani Permal ◽  
Miszaina Osman ◽  
Azrul Mohd Ariffin ◽  
Navaamsini Boopalan ◽  
Mohd Zainal Abidin Ab Kadir
Keyword(s):  
Simulated Annealing ◽  
Soil Structure ◽  
Soil Layer ◽  
Minimum Cost ◽  
Soil Condition ◽  
Problem Formulation ◽  
Soil Conditions ◽  
Grounding System ◽  
Grounding Grid ◽  
Grounding Grids

Grounding systems are critical in safeguarding people and equipment from power system failures. A grounding system’s principal goal is to offer the lowest impedance path for undesired fault current. Optimization of the grounding grid designs is important in satisfying the minimum cost of the grounding system and safeguarding those people who work in the surrounding area of the grounded installations. Currently, there is no systematic guidance or standard for grounding grid designs that include two-layer soil and its effects on grounding grid systems, particularly vertically layered soil. Furthermore, while numerous studies have been conducted on optimization, relatively limited study has been done on the problem of optimizing the grounding grid in two-layer soil, particularly in vertical soil structures. This paper presents the results of optimization for substation grounding systems using the Simulated Annealing (SA) algorithm in different soil conditions which conforms to the safety requirements of the grounding system. Practical features of grounding grids in various soil conditions discussed in this paper (uniform soil, two-layer horizontal soil, and two-layer vertical soil) are considered during problem formulation and solution algorithm. The proposed algorithm’s results show that the number of grid conductors in the X and Y directions (Nx and Ny), as well as vertical rods (Nr), can be optimized from initial numbers of 35% for uniform soil, 57% for horizontal two-layer soil for ρ1> ρ2, and 33% for horizontal two-layer soil for ρ1< ρ2, and 29% for vertical two-layer soil structure. In other words, the proposed technique would be able to utilize square and rectangle-shaped grounding grids with a number of grid conductors and vertical rods to be implemented in uniform, two-layer horizontal and vertical soil structure, depending on the resistivity of the soil layer.

scholarly journals Simulated annealing technique to design minimum cost exchanger

2011 ◽  
Vol 17 (4) ◽  
pp. 409-427 ◽  
Author(s):  
Nadeem Khalfe ◽  
Kumar Lahiri ◽  
Kumar Wadhwa
Keyword(s):  
Simulated Annealing ◽  
Heat Exchangers ◽  
Cost Minimization ◽  
Optimization Technique ◽  
Optimization Procedure ◽  
Minimum Cost ◽  
Geometric Parameters ◽  
Tube Length ◽  
Total Annual Cost ◽  
Economic Point

Owing to the wide utilization of heat exchangers in industrial processes, their cost minimization is an important target for both designers and users. Traditional design approaches are based on iterative procedures which gradually change the design and geometric parameters to satisfy a given heat duty and constraints. Although well proven, this kind of approach is time consuming and may not lead to cost effective design as no cost criteria are explicitly accounted for. The present study explores the use of nontraditional optimization technique: called simulated annealing (SA), for design optimization of shell and tube heat exchangers from economic point of view. The optimization procedure involves the selection of the major geometric parameters such as tube diameters, tube length, baffle spacing, number of tube passes, tube layout, type of head, baffle cut etc and minimization of total annual cost is considered as design target. The presented simulated annealing technique is simple in concept, few in parameters and easy for implementations. Furthermore, the SA algorithm explores the good quality solutions quickly, giving the designer more degrees of freedom in the final choice with respect to traditional methods. The methodology takes into account the geometric and operational constraints typically recommended by design codes. Three different case studies are presented to demonstrate the effectiveness and accuracy of proposed algorithm. The SA approach is able to reduce the total cost of heat exchanger as compare to cost obtained by previously reported GA approach.

A Stochastic Search Approach for Tool Requirement Planning

2015 ◽  
Vol 2 (1) ◽  
Author(s):  
D. Ganeshwar Rao ◽  
C. Patvardhan ◽  
Ranjit Singh
Keyword(s):  
Simulated Annealing ◽  
Tool Life ◽  
Minimum Cost ◽  
Stochastic Search ◽  
Automated Manufacturing ◽  
Tool Management ◽  
Primary Function ◽  
Search Approach ◽  
Production Period ◽  
Life Inventory

In an automated manufacturing unit, tool requirement planning is the primary function of tool management. The issues such as tool procurement, tool life inventory, use of alternative tools etc. can be addressed at a level below aggregate planning and above operational implementation. At this level, it is very essential to choose the optimum set of tools out of the alternative tools available for performing operations on various parts in a production period for minimum cost. In the present work, a model has been developed to consider the above mentioned factors and provide the optimum set of tools, out of the alternative tools available, for performing operations on a batch of parts. The performance of the three stochastic search techniques has been studied. It has been observed that the modified simulated annealing techniques are powerful techniques o provide the results in a very less number of evaluations.

scholarly journals A novel approach for solving travelling thief problem using enhanced simulated annealing

2021 ◽  
Vol 7 ◽  
pp. e377
Author(s):  
Hamid Ali ◽  
Muhammad Zaid Rafique ◽  
Muhammad Shahzad Sarfraz ◽  
Muhammad Sheraz Arshad Malik ◽  
Mohammed A. Alqahtani ◽  
...  
Keyword(s):  
Simulated Annealing ◽  
Optimization Problem ◽  
Optimization Problems ◽  
State Of The Art ◽  
Minimum Cost ◽  
Medium Size ◽  
Time Interval ◽  
Maximum Profit ◽  
Novel Approach ◽  
Hard Problems

Real-world optimization problems are getting more and more complex due to the involvement of inter dependencies. These complex problems need more advanced optimizing techniques. The Traveling Thief Problem (TTP) is an optimization problem that combines two well-known NP-Hard problems including the 0/1 knapsack problem and traveling salesman problem. TTP contains a person known as a thief who plans a tour to collect multiple items to fill his knapsack to gain maximum profit while incurring minimum cost in a standard time interval of 600 s. This paper proposed an efficient technique to solve the TTP problem by rearranging the steps of the knapsack. Initially, the picking strategy starts randomly and then a traversal plan is generated through the Lin-Kernighan heuristic. This traversal is then improved by eliminating the insignificant cities which contribute towards profit adversely by applying the modified simulated annealing technique. The proposed technique on different instances shows promising results as compared to other state-of-the-art algorithms. This technique has outperformed on a small and medium-size instance and competitive results have been obtained in the context of relatively larger instances.

Maximum production — minimum cost via value analysis

1963 ◽  
Vol 42 (3) ◽  
pp. 147
Author(s):  
N. Taylor
Keyword(s):  
Minimum Cost ◽  
Value Analysis ◽  
Maximum Production

A generalized fuzzy cost efficiency model

2020 ◽  
Vol 54 (6) ◽  
pp. 1775-1791
Author(s):  
Nazila Aghayi ◽  
Samira Salehpour
Keyword(s):  
Cost Efficiency ◽  
Minimum Cost ◽  
Extensive Literature ◽  
Data Envelopment ◽  
Fuzzy Environment ◽  
Decision Making Unit ◽  
Production Possibility Set ◽  
Fuzzy Cost ◽  
The Cost ◽  
Generalized Cost

The concept of cost efficiency has become tremendously popular in data envelopment analysis (DEA) as it serves to assess a decision-making unit (DMU) in terms of producing minimum-cost outputs. A large variety of precise and imprecise models have been put forward to measure cost efficiency for the DMUs which have a role in constructing the production possibility set; yet, there’s not an extensive literature on the cost efficiency (CE) measurement for sample DMUs (SDMUs). In an effort to remedy the shortcomings of current models, herein is introduced a generalized cost efficiency model that is capable of operating in a fuzzy environment-involving different types of fuzzy numbers-while preserving the Farrell’s decomposition of cost efficiency. Moreover, to the best of our knowledge, the present paper is the first to measure cost efficiency by using vectors. Ultimately, a useful example is provided to confirm the applicability of the proposed methods.

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