Optimization of Facility Layout of Tank farms using Genetic Algorithm and Fireball Scenario

2016 ◽  
Vol 11 (2) ◽  
pp. 149-157 ◽  
Author(s):  
S.R. Nabavi ◽  
A.H. Taghipour ◽  
A. Mohammadpour Gorji
Keyword(s):  
Genetic Algorithm ◽  
Cost Function ◽  
Simulated Data ◽  
Sigmoid Function ◽  
Total Cost ◽  
Tank Farm ◽  
Novel Approach ◽  
Good Agreement ◽  
Total Cost Function

Abstract In this study a novel approach is presented to optimize the layout of petrochemical units, considering the most likely scenario. To illustrate the method a real case study, exporting petrochemical tank farm (Esfahan petrochemical, Iran), was selected. Three objective functions like, piping cost, occupied land cost and human losses were combined and the total cost function was minimized. The required data for lethality function were obtained using simulation of different scenario by Phast software. A sigmoid function was fitted to the data which can estimate the lethality based on the distance from incident point. Genetic algorithm (GA) was used to minimize the total cost function. Due to vastness of searching area, more than one optimum layout was obtained. Finally, the optimum layouts were simulated with fire ball scenario and a good agreement was obtained between optimum points and simulated data.

Sustainable optimal ordering quantity for non-instantaneous deteriorating items under joint replenishment with substitution and carbon emission

Kybernetes ◽  
2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ranu Singh ◽  
Vinod Kumar Mishra
Keyword(s):  
Cost Function ◽  
Carbon Emission ◽  
Inventory Model ◽  
Deteriorating Items ◽  
Joint Replenishment ◽  
Content Type ◽  
Total Cost ◽  
Optimal Ordering ◽  
Ordering Quantity ◽  
Total Cost Function

Purpose Carbon emission is a significant issue for the current business market and global warming. Nowadays, most countries have focused to reduce the environmental impact of business with durable financial benefits. The purpose of this study is to optimize the entire cost functions with carbon emission and to find the sustainable optimal ordering quantity for retailers. Design/methodology/approach This paper illustrates a sustainable inventory model having a set of two non-instantaneous substitutable deteriorating items under joint replenishment with carbon emission. In this model demand and deterioration rate are considered as deterministic, constant and triangular fuzzy numbers. The objective is to find the optimal ordering quantity for retailers and to minimize the total cost function per unit time with carbon emission. The model is then solved with the help of Maple software. Findings This paper presents a solution method and also develop an algorithm to determine the order quantities which optimize the total cost function. A numerical experiment illustrates the improvement in optimal total cost of the inventory model with substitution over without substitution. The graphical results show the convexity of the cost function. Finally, sensitivity analysis is given to get the impact of parameters and validity of the model. Originality/value This study considers a set of two non-instantaneous substitutable deteriorating items under joint replenishment with carbon emission. From the literature review, in the authors’ knowledge no researcher has undergone this kind of study.

Multi-product total cost function for higher education: a case of bible colleges

2001 ◽  
Vol 20 (3) ◽  
pp. 297-303 ◽  
Author(s):  
Rajindar K. Koshal ◽  
Manjulika Koshal ◽  
Ashok Gupta
Keyword(s):  
Higher Education ◽  
Cost Function ◽  
Bible Colleges ◽  
Total Cost ◽  
Total Cost Function

scholarly journals Economics of Potato Production for Autumn Season 2015-2016 (Baghdad Governorate as A Practical Case)

2021 ◽  
Vol 8 (2) ◽  
pp. 1-13
Author(s):  
Faisal H. Nasser ◽  
Osamah K. Al-Ukeil
Keyword(s):  
Cost Function ◽  
Production Function ◽  
Cost Efficiency ◽  
Potato Production ◽  
Production Costs ◽  
Optimal Size ◽  
Total Cost ◽  
Autumn Season ◽  
Economic Price ◽  
Total Cost Function

"The research aimed at estimating the production function and the total cost function, as well as measuring the efficiency of resource use, technical, economic, price and cost efficiency. The study was based primarily on a simple random sample of (155) farmers in Baghdad governorate for the autumn season (2015-2016), The double logarithmic formula was the most suitable for the production function. The results of the resource efficiency criteria indicated that potato farmers were efficient in using resources (seed, phosphate fertilizer, human labor) and were inefficient in using irrigation and pesticides. While the cubic formula was more suitable for the total cost function according to the statistical, econometrical and economical tests, and from it we showed that the optimum size of production and size that maximize profit are (119.069, 143.398) ton consequently. Technical, economic and price efficiencies were estimated at (34.25933, 34.25937, 73.521)% consequently, while cost efficiency was estimated at (0.454), and the net farm income that achieved over all the sample less about (10380.741) thousand dinars than that achieved at optimal size. The research concluded that the quantity of seeds had the greatest impact on potato production and that there was waste in using the available resources, which led to actual production being less than optimum production. The research recommends that the related institutions should work to provide a good quality potato seeds to cover the needs of local farmers, from good sources in a timely manner and at the right price to increase the production and productivity of this important crop and reduce production costs. As well as the protection of the local producer by adopting price policies that grant best income of farmers. Corresponding author: E-mail(Faisal@gmail) Al- Muthanna University All rights reserved"

Test Suite Optimization Using Firefly and Genetic Algorithm

2022 ◽  
pp. 1635-1651
Author(s):  
Abhishek Pandey ◽  
Soumya Banerjee
Keyword(s):  
Genetic Algorithm ◽  
Software Engineering ◽  
Software Testing ◽  
Hybrid Approach ◽  
Empirical Evaluation ◽  
Data Generation ◽  
Testing Environment ◽  
Novel Approach ◽  
Test Suite Optimization

Software testing is essential for providing error-free software. It is a well-known fact that software testing is responsible for at least 50% of the total development cost. Therefore, it is necessary to automate and optimize the testing processes. Search-based software engineering is a discipline mainly focussed on automation and optimization of various software engineering processes including software testing. In this article, a novel approach of hybrid firefly and a genetic algorithm is applied for test data generation and selection in regression testing environment. A case study is used along with an empirical evaluation for the proposed approach. Results show that the hybrid approach performs well on various parameters that have been selected in the experiments.

scholarly journals Hydrodynamic Modeling of a Tropical Tidal River Using the Dynamic Estuary Model (DYNHYD5): A Case Study in Sibu Laut River, Sarawak, Malaysia

2018 ◽  
Vol 2018 ◽  
pp. 1-7 ◽  
Author(s):  
Chen-Lin Soo ◽  
Teck-Yee Ling ◽  
Lee Nyanti
Keyword(s):  
Field Data ◽  
Model Simulation ◽  
Simulated Data ◽  
Hydrodynamic Modeling ◽  
Tidal River ◽  
Water Quality Simulation ◽  
Calibration And Validation ◽  
Simulated Flow ◽  
Good Agreement

Application of the Dynamic Estuary Model (DYNHYD5) in a tropical tidal river is limited. The successfully calibrated and validated hydrodynamic model is valuable in subsequent water quality simulation for environmental management. Hence, a hydrodynamic modeling approach using the DYNHYD5 was conducted in a tropical tidal river in Malaysia. Samplings were conducted in the Sibu Laut River to collect the hydrology data for model simulation. The model was calibrated and validated by comparing the simulated flow and mean depth with the field data at different simulation periods of time. The results showed that the model DYNHYD5 was successfully calibrated with channel flows and mean depths and then reproduced with good agreement in validation. The observed and simulated data were linearly correlated (R2 > 0.8) with values of slope γ ranging from 0.891 to 1.204 in both calibration and validation. The Nash–Sutcliffe coefficient of efficiency (NSE) of more than 0.7 in both calibration and validation also indicated satisfactory comparison between the observed and simulated data. The result indicated that the application of the DYNHYD5 is feasible in a tropical tidal river in Malaysia.

A Novel Approach to the Optimisation of Reaction Rate Parameters for Methane Combustion Using Multi-Objective Genetic Algorithms

2003 ◽  
Author(s):  
L. Elliott ◽  
D. B. Ingham ◽  
A. G. Kyne ◽  
N. S. Mera ◽  
M. Pourkashanian ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Reaction Mechanism ◽  
Reaction Rate ◽  
Flame Structure ◽  
Simulated Data ◽  
Methane Combustion ◽  
Rate Coefficients ◽  
Inversion Process ◽  
Multi Objective ◽  
Novel Approach

This study uses a multi-objective genetic algorithm to determine new reaction rate parameters (A’s, β’s and Ea’s in the non-Arrhenius expressions) for the combustion of a methane/air mixture. The multi-objective structure of the genetic algorithm employed allows for the incorporation of both perfectly stirred reactor and laminar premixed flames data in the inversion process, thus enabling a greater confidence in the predictive capabilities of the reaction mechanisms obtained. Various inversion procedures based on reduced sets of data are investigated and tested on methane/air combustion in order to generate efficient inversion schemes for future investigations concerning complex hydrocarbon fuels. The inversion algorithms developed are first tested on numerically simulated data. In addition, the increased flexibility offered by this novel multi-objective GA has now, for the first time, allowed experimental data to be incorporated into our reaction mechanism development. A GA optimised methane air reaction mechanism is presented which offers a remarkable improvement over a previously validated starting mechanism in modelling the flame structure in a stoichiometric methane-air premixed flame (http://www.leeds.ac.uk/ERRI/research/res.html). In addition, the mechanism outperforms the predictions of more detailed schemes and is still capable of modelling combustion phenomena that were not part of the optimisation process. Therefore, the results of this study demonstrate that the genetic algorithm inversion process promises the ability to assess combustion behaviour for fuels where the reaction rate coefficients are not known with any confidence and, subsequently, accurately predict emission characteristics, stable species concentrations and flame characterisation. Such predictive capabilities will be of paramount importance within the gas turbine industry.

scholarly journals A heuristic algorithm for multiple trip vehicle routing problems with time window constraint and outside carrier selection

2019 ◽  
Vol 4 (3) ◽  
pp. 256-273
Author(s):  
Ching-Wu Chu ◽  
Hsiu-Li Hsu
Keyword(s):  
Cost Function ◽  
Vehicle Routing ◽  
Heuristic Algorithm ◽  
Real World ◽  
Time Windows ◽  
Vehicle Routing Problems ◽  
Routing Problems ◽  
Content Type ◽  
Total Cost ◽  
Total Cost Function

Purpose In this paper, the authors introduced a real world new problem, the multi-trip vehicle routing problem with time windows and the possible use of a less-than-truckload carrier to satisfy customer demands. The purpose of this paper is to develop a heuristic algorithm to route the private trucks with time windows and to make a selection between truckload and less-than-truckload carriers by minimizing a total cost function. Design/methodology/approach Both mathematical model and heuristic algorithm are developed for routing the private trucks with time windows and for selecting of less-than-truckload carriers by minimizing the total cost function. Findings In all, 40 test problems were examined with the heuristics. Computational results show that the algorithm obtains the optimal or near-optimal solutions efficiently in terms of time and accuracy. Originality/value The research described in this paper differs from the previous one on fleet planning or vehicle routing, in that it modifies the Clarke and Wright method by shifting the performance measure from a distance to cost and also incorporates the fixed cost of different types of trucks into the model. In addition, the authors simultaneously consider the multiple trip vehicle routing problems with time windows and the selection of less-than-truckload carriers that is an integrated scenario of real-world application. To the best of the authors’ knowledge, this scenario has not been considered in the literature.

Test Suite Optimization Using Firefly and Genetic Algorithm

2019 ◽  
Vol 11 (1) ◽  
pp. 31-46 ◽  
Author(s):  
Abhishek Pandey ◽  
Soumya Banerjee
Keyword(s):  
Genetic Algorithm ◽  
Software Engineering ◽  
Software Testing ◽  
Hybrid Approach ◽  
Empirical Evaluation ◽  
Data Generation ◽  
Testing Environment ◽  
Novel Approach ◽  
Test Suite Optimization

Software testing is essential for providing error-free software. It is a well-known fact that software testing is responsible for at least 50% of the total development cost. Therefore, it is necessary to automate and optimize the testing processes. Search-based software engineering is a discipline mainly focussed on automation and optimization of various software engineering processes including software testing. In this article, a novel approach of hybrid firefly and a genetic algorithm is applied for test data generation and selection in regression testing environment. A case study is used along with an empirical evaluation for the proposed approach. Results show that the hybrid approach performs well on various parameters that have been selected in the experiments.

scholarly journals The Cost Function and Scale Economies in Academic Research Libraries

2002 ◽  
Vol 63 (5) ◽  
pp. 406-420 ◽  
Author(s):  
Lewis Guodo Liu
Keyword(s):  
Cost Function ◽  
Economies Of Scale ◽  
Academic Research ◽  
Scale Economies ◽  
Information Provision ◽  
Total Cost ◽  
Research Libraries ◽  
Wide Range ◽  
The Cost ◽  
Total Cost Function

This empirical research examined scale economies of academic research libraries that belong to the Association of Research Libraries and developed a total cost function for estimating economies of scale. The author argues that libraries in general, and academic research libraries in particular, are information provision organizations that provide multiproducts and multiservices and points out that some previous studies that used the production function have limitations due to the fact that this function only permits a single-output variable. This investigation incorporated a wide range of collections and service output variables into the total cost function. The regression results show that the R square of the cost function model is .8142 and that the coefficients of three very important output variables (volumes held, serials, and group presentations) are statistically significant at high confidence levels. The findings of this research show that the function coefficient is .93, indicating that slight economies of scale exist in academic research libraries.

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