Using Genetic Algorithm and Simplex Method to Stabilize an Oil Treatment Plant Inlet Flow

Author(s):  
Adriano C. Silva ◽  
Takaaki Ohishi ◽  
Alexandre S. Mendes ◽  
Fernando A. França ◽  
Eliana A. R. Delgado

This paper presents a hybrid approach, composed of a genetic algorithm and a linear programming method, to achieve an efficient pipeline network operation. The pipeline network optimization consists of the determination of pump scheduling over a short-term horizon, usually one or more days ahead. The resulting mathematical problem has a dynamic and combinatorial characteristic, in which a sub-optimal solution was obtained through these two mathematical tools in a short computational time. The approach was applied in a Pipeline Network to a study case based on the Patagonia Argentina, which is comprised of 16 tanks and linked pumps, with 66 kilometers of pipelines, that transport the production of more than 100 wells to a pre-processing plant. The goal was to obtain a constant input flow rate at the plant respecting physical and chemical processes requirements.

2014 ◽  
Vol 2014 ◽  
pp. 1-15 ◽  
Author(s):  
I. Hameem Shanavas ◽  
R. K. Gnanamurthy

In Optimization of VLSI Physical Design, area minimization and interconnect length minimization is an important objective in physical design automation of very large scale integration chips. The objective of minimizing the area and interconnect length would scale down the size of integrated chips. To meet the above objective, it is necessary to find an optimal solution for physical design components like partitioning, floorplanning, placement, and routing. This work helps to perform the optimization of the benchmark circuits with the above said components of physical design using hierarchical approach of evolutionary algorithms. The goal of minimizing the delay in partitioning, minimizing the silicon area in floorplanning, minimizing the layout area in placement, minimizing the wirelength in routing has indefinite influence on other criteria like power, clock, speed, cost, and so forth. Hybrid evolutionary algorithm is applied on each of its phases to achieve the objective. Because evolutionary algorithm that includes one or many local search steps within its evolutionary cycles to obtain the minimization of area and interconnect length. This approach combines a hierarchical design like genetic algorithm and simulated annealing to attain the objective. This hybrid approach can quickly produce optimal solutions for the popular benchmarks.


2015 ◽  
Vol 5 (4) ◽  
pp. 239-245 ◽  
Author(s):  
Ahmad Fouad El-Samak ◽  
Wesam Ashour

Abstract Combinatorial optimization problems, such as travel salesman problem, are usually NP-hard and the solution space of this problem is very large. Therefore the set of feasible solutions cannot be evaluated one by one. The simple genetic algorithm is one of the most used evolutionary computation algorithms, that give a good solution for TSP, however, it takes much computational time. In this paper, Affinity Propagation Clustering Technique (AP) is used to optimize the performance of the Genetic Algorithm (GA) for solving TSP. The core idea, which is clustering cities into smaller clusters and solving each cluster using GA separately, thus the access to the optimal solution will be in less computational time. Numerical experiments show that the proposed algorithm can give a good results for TSP problem more than the simple GA.


2013 ◽  
Vol 10 (4) ◽  
pp. 1531-1538
Author(s):  
Mahmoud M. Ismail ◽  
Ibrahim M. El-henawy

In this paper, a hybridization of two different swarm intelligent approaches, stochastic diffusion search, and particle swarm optimization techniques is presented  for solving integer programming problems. The hybrid implementation allows us to avoid certain drawbacks and weaknesses of each algorithm, which means that we are able to find an optimal solution in an acceptable computational time. Our hybrid implementation allows the IP algorithm to reach the optimal solution in a considerably shorter time than is needed to solve the model using the entire dataset directly within the model. Our hybrid approach outperforms the results obtained by each technique separately. It is able to find the optimal solution in a shorter time than each technique on its own, and the results are highly competitive with the state-of-the-art in large-scale optimization. Furthermore, according to our results, combining the PSO with SDS approach for solving IP problems appears to be an interesting research area in combinatorial optimization. 


Author(s):  
Kikuo Fujita ◽  
Shinsuke Akagi ◽  
Noriyasu Hirokawa

Abstract In layout design problems including blank nesting, the positions and directions of layout elements must be determined so as to minimize the total space. It is difficult and computationally time-consuming to find the optimal solution for such layout problems, because they include a lot of underlying combinational conditions. In this paper, we present an approach for optimal nesting by combining a genetic algorithm and a local minimization algorithm. In the approach, the genetic algorithm is used for handling the combinations which are represented in the string, and the local minimization algorithm is used for determining the embodiment layout under the fixed combinations so as to minimize the scrap volume which is corresponding to the fitness value in the genetic algorithm. And we present an example for showing the effective nesting result produced by this approach.


Author(s):  
Ebrahim Asadi-Gangraj ◽  
Sina Nayeri

Due to increasing population, increasing number of vehicles as well as environmental pollution, planning vehicles efficiently one of important problems nowadays. This article proposes a Multi-Objective Mixed Integer Programming (MOMIP) model for the vehicle-routing problem with time windows, driver-specific times and vehicles-specific capacities (VRPTDV), a variant of the classical VRPT that uses driver-specific travel and service times and vehicles-specific capacity to model the familiarity of the different drivers with the customers to visit. The first objective function aims to minimize traveled distance and the second objective function minimizing working duration. Since the problem is NP-hard, optimal solution for the instances of realistic size cannot be obtained within a reasonable amount of computational time using exact solution approaches. Hence, the hybrid approach based on LP metric method and genetic algorithm is proposed to solve the given problem.


2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Seyed Mahdi Homayouni ◽  
Sai Hong Tang

According to previous researches, automated guided vehicles and quay cranes in container terminals have a high potential synergy. In this paper, a mixed integer programming model is formulated to optimize the coordinated scheduling of cranes and vehicles in container terminals. Objectives of the model are to minimize total traveling time of the vehicles and delays in tasks of cranes. A genetic algorithm is developed to solve the problem in reasonable computational time. The most appropriate control parameters for the proposed genetic algorithm are investigated in a medium size numerical test case. It is shown that balanced crossover and mutation rates have the best performance in finding a near optimal solution for the problem. Then, ten small size test cases are solved to evaluate the performance of the proposed optimization methods. The results show the applicability of the genetic algorithm since it can find near optimal solutions, precisely and accurately.


Author(s):  
J. Magelin Mary ◽  
Chitra K. ◽  
Y. Arockia Suganthi

Image processing technique in general, involves the application of signal processing on the input image for isolating the individual color plane of an image. It plays an important role in the image analysis and computer version. This paper compares the efficiency of two approaches in the area of finding breast cancer in medical image processing. The fundamental target is to apply an image mining in the area of medical image handling utilizing grouping guideline created by genetic algorithm. The parameter using extracted border, the border pixels are considered as population strings to genetic algorithm and Ant Colony Optimization, to find out the optimum value from the border pixels. We likewise look at cost of ACO and GA also, endeavors to discover which one gives the better solution to identify an affected area in medical image based on computational time.


2017 ◽  
Vol 120 (3) ◽  
pp. 303-322
Author(s):  
D. Pienaar ◽  
B.M. Guy ◽  
C. Pienaar ◽  
K.S. Viljoen

Abstract Mineralogical and textural variability of ores from different sources commonly leads to processing inefficiencies, particularly when a processing plant is designed to treat ore from a single source (i.e. ore of a relatively uniform composition). The bulk of the Witwatersrand ore in the Klerksdorp goldfield, processed at the AngloGold Ashanti Great Noligwa treatment plant, is derived from the Vaal Reef (>90%), with a comparatively small contribution obtained from the Crystalkop Reef (or C-Reef). Despite the uneven contribution, it is of critical importance to ensure that the processing parameters are optimized for the treatment of both the Vaal and C-Reefs. This paper serves to document the results of a geometallurgical study of the C-Reef at the Great Noligwa gold mine in the Klerksdorp goldfield of South Africa, with the primary aim of assessing the suitability of the processing parameters that are in use at the Great Noligwa plant. The paper also draws comparisons between the C-Reef and the Vaal Reef A-facies (Vaal Reef) and attempts to explain minor differences in the recovery of gold and uranium from these two sources. Three samples of the C-Reef were collected in-situ from the underground operations at Great Noligwa mine for mineralogical analyses and metallurgical tests. Laboratory-scale leach tests for gold (cyanide) and uranium (sulphuric acid) were carried out using dissolution conditions similar to that in use at the Great Noligwa plant, followed by further diagnostic leaching in the case of gold. The gold in the ore was found to be readily leachable with recoveries ranging from 95% to 97% (as opposed to 89% to 93% for the Vaal Reef). Additional recoveries were achieved in the presence of excess cyanide (96% to 98%). The recovery of uranium varied between 72% and 76% (as opposed to 30% to 64% for the Vaal Reef), which is substantially higher than predicted, given the amount of brannerite in the ore, which is generally regarded as refractory. Thus, the higher uranium recoveries from the C-Reef imply that a proportion of the uranium was recovered by the partial dissolution of brannerite. As the Vaal Reef contain high amounts of chlorite (3% to 8%), which is an important acid consumer, it is considered likely that this could have reduced the effectiveness of the H2SO4 leach in the case of the ore of the Vaal Reef. Since the gold and uranium recoveries from the C-Reef were higher than the recoveries from the Vaal Reef, the results demonstrate that the processing parameters used for treatment of the Vaal Reef are equally suited to the treatment of the C-Reef. Moreover, small processing modifications, such as increased milling and leach retention times, may well increase the recovery of gold (particularly when e.g. coarse gold, or unexposed gold, is present).


2000 ◽  
Vol 41 (1) ◽  
pp. 223-230 ◽  
Author(s):  
M.F. Sevimli ◽  
A.F. Aydin ◽  
Ì. Öztürk ◽  
H.Z. Sarikaya

The aim of this study is to characterize the wastewater from an opium alkaloid processing plant and to evaluate alternative treatment techniques to upgrade an existing full-scale biological activated sludge treatment plant having problems of high residual COD and unacceptable dark brown color. In this content firstly, long term operational records of the two stage aerobic activated sludge treatment plant of the opium alkaloid factory located in Afyon province of Turkiye were evaluated. The operating results for the last three years were statistically analyzed and median and 95-percentile values were determined for the parameters including chemical and biological oxygen demand (COD and BOD5) and treatment efficiencies. Specific wastewater generation was found as 6.7 m3 per ton of the opium capsule processed. In the following stage of the study, three additional treatment processes were experimentally tested: anaerobic pretreatment, post treatment of aerobically treated effluents with lime and ozone. Pilot scale upflow anaerobic sludge blanket reactor (UASBR) experiments have demonstrated that about 70 percent of the incoming COD can be removed anaerobically. Chemical treatability studies with lime for the aerobically treated effluent have shown that about 78 percent color and 46 percent COD removals can be obtained with lime dosage of 25 gl−1. Post treatment of the effluents of the existing two stage aerobic treatment with ozone also resulted in significant color and COD reduction.


Water ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 514
Author(s):  
Leonardo Bayas-Jiménez ◽  
F. Javier Martínez-Solano ◽  
Pedro L. Iglesias-Rey ◽  
Daniel Mora-Melia ◽  
Vicente S. Fuertes-Miquel

A problem for drainage systems managers is the increase in extreme rain events that are increasing in various parts of the world. Their occurrence produces hydraulic overload in the drainage system and consequently floods. Adapting the existing infrastructure to be able to receive extreme rains without generating consequences for cities’ inhabitants has become a necessity. This research shows a new way to improve drainage systems with minimal investment costs, using for this purpose a novel methodology that considers the inclusion of hydraulic control elements in the network, the installation of storm tanks and the replacement of pipes. The presented methodology uses the Storm Water Management Model for the hydraulic analysis of the network and a modified Genetic Algorithm to optimize the network. In this algorithm, called the Pseudo-Genetic Algorithm, the coding of the chromosomes is integral and has been used in previous studies of hydraulic optimization. This work evaluates the cost of the required infrastructure and the damage caused by floods to find the optimal solution. The main conclusion of this study is that the inclusion of hydraulic controls can reduce the cost of network rehabilitation and decrease flood levels.


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