Sharif Digital Repository

This paper presents a new method to solve the problem of finding the best configuration of fuel assemblies in a pressurized water reactor (PWR) core. Finding the optimum solution requires a huge amount of calculations in classical methods. It has been shown that the application of continuous Hopfield neural network accompanied by simulated annealing method to this problem not only reduces the amount of calculations, but also guarantees finding the best solution. In this study flattening of neutron flux inside the reactor core of Bushehr NPP is considered as the objective function. The result is the optimum configuration which is in agreement with the pattern proposed by the designer. © 2001... 

Scheduling sports leagues has drawn significant attention to itself in recent years, as it involves considerable revenue as well as challenging combinatorial optimization problems. A particular class of these problems is the Traveling Tournament Problem (TTP) which focuses on minimizing the total traveling distance for teams. In this paper, an efficient simulated annealing approach is presented for TTP which applies two simultaneous and disparate models for the problem in order to search the solutions space more effectively. Also, a computationally efficient modified greedy scheme is proposed for constructing a favorable initial solution for the simulated annealing algorithm. Our... 

The graph colouring problem, as an important NP-complete problem, is considered in this paper and a hybrid meta-heuristic approach is developed to solve it. The initial solution of the algorithm, generated by a heuristic method, is used by a simulated annealing (SA) approach to generate new solutions until no progress in a number of solutions reported. At this stage, the algorithm will use a tabu search routine and this local search operator will be followed for some iterations. After finding a better solution, the algorithm is again followed through SA. Efficiency of the algorithm is showed through various experiments on well-known benchmark problems of DIMACS. Comparison with the available... 

A novel Locomotion and gait planning method for a surface walking/climbing robot based on sequential 4-bar mechanism motions is presented. The robot moves on a surface through decoupled transverse gaits and turning gaits with desired length and angle. For implementation of turning gaits three methods of Simulated Annealing Accurate Planning (SAAP), Gradient Based Planning (GBP) and Hybrid Accurate Planning (HAP) are studied. Where the last method was found the most effective approach  

The Hopfield network is studied from the standpoint of taking it as a computational model in optimizing the fuel management of pressurized water reactors (PWRs). In this paper, the flattening of the neutron flux is considered as the objective function. By this consideration, the power peaking inside the reactor core is also minimized. Regarding the local minimum problem of Hopfield network, the simulated annealing method is applied to improve the Hopfield solution. The method is applied to Bushehr Nuclear Power Plant (PWR design) and the result is compared with the core configuration purposed by the designer  

Inspired by an upward stochastic walking idea, a new ensemble pruning method called simulated quenching walking (SQWALKING) is developed in this paper. The rationale behind this method is to give values to stochastic movements as well as to accept unvalued solutions during the investigation of search spaces. SQWALKING incorporates simulated quenching and forward selection methods to choose the models through the ensemble using probabilistic steps. Two versions of SQWALKING are introduced based on two different evaluation measures; SQWALKINGA that is based on an accuracy measure and SQWALKINGH that is based on a human-like foresight measure. The main objective is to construct a proper... 

0–1 knapsack problem (KP01) is one of the classic variants of knapsack problems in which the aim is to select the items with the total profit to be in the knapsack. In contrast, the constraint of the maximum capacity of the knapsack is satisfied. KP01 has many applications in real-world problems such as resource distribution, portfolio optimization, etc. The purpose of this work is to gather the latest SA-based solvers for KP01 together and compare their performance with the state-of-the-art meta-heuristics in the literature to find the most efficient one(s). This paper not only studies the introduced and non-introduced single-solution SA-based algorithms for KP01 but also proposes a new... 

In this research, we present results of simulated annealing (SA), a heuristic optimization algorithm, for focusing light through a turbid medium. Performance of the algorithm on phase and amplitude modulations has been evaluated. A number of tips to tune the optimization parameters are provided. The effect of measurement noise on the performance of the SA algorithm is explored. Additionally, SA performance is compared with continuous sequential and briefly with other optimization algorithms. © 2018 Optical Society of America  

Weibull distribution plays an important role in failure distribution modeling in reliability studies. It is a hard work to estimate the parameters of Weibull distribution. This distribution has three parameters, but for simplicity, a parameter is omitted and as a result, the estimation of the others will be easily done. When the three-parameter distribution is of interest, the estimation procedure will be quite boring. Maximum likelihood estimation is a good method, which is usually used to elaborate on the parameter estimation. The likelihood function formed for the parameter estimation of a three-parameter Weibull distribution is very hard to maximize. Many researchers have studied this... 

0–1 knapsack problem (KP01) is one of the classic variants of knapsack problems in which the aim is to select the items with the total profit to be in the knapsack. In contrast, the constraint of the maximum capacity of the knapsack is satisfied. KP01 has many applications in real-world problems such as resource distribution, portfolio optimization, etc. The purpose of this work is to gather the latest SA-based solvers for KP01 together and compare their performance with the state-of-the-art meta-heuristics in the literature to find the most efficient one(s). This paper not only studies the introduced and non-introduced single-solution SA-based algorithms for KP01 but also proposes a new... 

While the usual assumptions in multiperiodic inventory control problems are that the orders are placed either at the beginning of each period (periodic review) or depending on the inventory level they can happen at any time (continuous review), in this paper we assume the periods between two replenishments of several products are identical and independent random variables. For the problem at hand, the order quantities (decision variables) are of integertype and there are two kinds of space and service level constraints for each product. A model of the problem is first developed in which a combination of backorder and emergency orders is considered for the shortages, and the costs are... 

The graph colouring problem, as an important NP-complete problem, is considered in this paper and a hybrid meta-heuristic approach is developed to solve it. The initial solution of the algorithm, generated by a heuristic method, is used by a simulated annealing (SA) approach to generate new solutions until no progress in a number of solutions reported. At this stage, the algorithm will use a tabu search routine and this local search operator will be followed for some iterations. After finding a better solution, the algorithm is again followed through SA. Efficiency of the algorithm is showed through various experiments on well-known benchmark problems of DIMACS. Comparison with the available... 

This paper mainly aims to obtain a minimum norm solution to the NP-hard absolute value equations (AVE) $$Ax-|x|=b$$Ax-|x|=b. In our proposed method, first we show that the AVE is equivalent to a bilinear programming problem and then we present a system tantamount to this problem. To find the minimum norm solution to the AVE, we solve a quadratic programming problem with quadratic and linear constraints. Eventually, we solve the obtained programming problem by Simulated Annealing algorithm. Numerical results support the efficiency of the proposed method and the high accuracy of calculation  

Permeability as a fundamental reservoir property plays a key role in reserve estimation, numerical reservoir simulation, reservoir engineering calculations, drilling planning, and mapping reservoir quality. In heterogeneous reservoir, due to complexity, natural heterogeneity, non-uniformity, and non-linearity in parameters, prediction of permeability is not straightforward. To ease this problem, a novel mathematical robust model has been proposed to predict the permeability in heterogeneous carbonate reservoirs. To this end, a fairly new soft computing method, namely least square support vector machine (LSSVM) modeling optimized with coupled simulated annealing (CSA) optimization technique... 

The main goal of this paper is to compute the solution to the NP-hard absolute value equations (AVEs) Ax - |x| = b when the singular values of A exceed 1. First we show the AVE is equivalent to a bilinear programming problem and then we present a system tantamount to this problem. We use the simulated annealing (SA) algorithm to solve this system. Finally, several examples are given to illustrate the implementation and efficiency of the proposed method. Copyright © 2017 Inderscience Enterprises Ltd  

In this research, a single-period two-echelon inventory control problem with market targeting strategies is considered. In this problem, there are several final products and raw materials with varying usage rates. The objective is to determine the order sizes of final products and raw materials before the selling period such that customers' satisfaction is reached and expected profit is maximized within an available budget. The problem is first mathematically formulated and then a modified particle swarm optimization algorithm is employed to solve the nonlinear programming problem. To validate the results obtained, a simulated annealing algorithm is provided as a benchmark. The parameters of... 

Although demand responsive feeder bus operation is possible with human-driven vehicles, it has not been very popular and is mostly available as a special service because of its high operating costs due to intensive labor costs as well as requirement for advanced real-time information technology and complicated operation. However, once automated vehicles become available, small-sized flexible door-to-door feeder bus operation will become more realistic, so preparing for such automated flexible feeder services is necessary to take advantage of the rapid improvement of automated vehicle technology. Therefore, in this research, an algorithm for optimal flexible feeder bus routing, which... 

Improving testability during the early stages of High-Level Synthesis (HLS) has several benefits, including reduced test hardware overhead, reduced test costs, reduced design iteration, and significant improved fault coverage. In this paper, we present a novel register allocation method, which is based on weighted graph coloring algorithm, targeting testability improvement for digital circuits. The topics covered in this paper include an overview of HLS and testability parameters, our testability model and experimental results