Imran Ali Chaudhry's personal collection : Scipedia

Preliminary Aircraft Design Optimization Using Genetic Algorithms
I. Chaudhry, A. Ahmed

(2014). Journal of Scientific and Industrial Research

Abstract
Aircraft design is a highly nonlinear problem and inherently multidisciplinary activity that involves a large number of design variables and different models and tools for various aspects of design. A spreadsheet based genetic algorithm (GA) approach is presented to optimize the preliminary design of an aircraft. A domain independent general purpose genetic algorithm is proposed to implement the optimization routine. Breguet range equation is used as the objective function for the design evaluation. A total of sixteen design variables are considered in the optimization process. It has also been demonstrated that the proposed approach can be adapted to any objective function without changing the optimization routine. The model is applicable to commercial airliner as well as a multirole jet fighter. The proposed model has been validated against known configurations of various aircraft.
Abstract
Aircraft design is a highly nonlinear problem and inherently multidisciplinary activity that involves a large number of design variables and different models and [...]
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Case Based Reasoning Support for Adaptive Finite Element Analysis - Mesh Selection for an Integrated System
A. Research, . May, I. Chaudhry

(2014). Applied Physics Research

Abstract
An Adaptive Finite Element Analysis Integrated System supported through application of Case Based Reasoning (CBR) methodology is being proposed in this paper. The approach is fruitful for selection of an initial mesh from a library of solutions to initiate analysis process, as already tested optimal mesh will have lesser refinement iterations. The optimal mesh distribution, represented by object-oriented method, can be easily adapted to the topology of new problem in same domain. An integrated and universal structural analysis system models human reasoning by forming solutions through the retrieval and adaptation of successful strategies used in the past. Basic insight of two distinct subjects along with resolution of involved issues and integration strategy for development of an intelligent system is elaborated here. The research explains an algorithm for case retrieval and mesh generation procedures based on the principles of mapping method.
Abstract
An Adaptive Finite Element Analysis Integrated System supported through application of Case Based Reasoning (CBR) methodology is being proposed in this paper. The approach [...]
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Object Oriented Case Representation for CBR Application in Structural Analysis
A. Khan, I. Chaudhry

Applied Artificial Intelligence (2015). Applied Artificial Intelligence

Abstract
Knowledge representation is an essential element of a problem-solving technique through computational work. This article describes the knowledge representation scheme formulated to represent a problem in the structural analysis domain for solution through case-based reasoning (CBR). The numerical knowledge is extracted from a real-life problem that can be used as an input in a case-based reasoner. The geometric topology, loading, and mesh distribution for structure from a solved problem is represented in the form of numerical values for easy adaptation by the new problem. The representation scheme is a step forward in development of a system to be utilized for the time-consuming structural analysis requiring heavy computational power, such as an aircraft wing and fuselage components. The success of the representation strategy is a proof that CBR can work as a powerful problem-solving tool in this domain.
Abstract
Knowledge representation is an essential element of a problem-solving technique through computational work. This article describes the knowledge representation scheme [...]
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Identical parallel-machine scheduling and worker assignment problem using genetic algorithms to minimize makespan
I. Chaudhry, S. Mahmood

Lecture Notes in Electrical Engineering (2011).

Abstract
dentical parallel machine scheduling problem for minimizing the makespan is a very important production scheduling problem which has been proven to be NP-hard. The problem further compounds with additional constraints. Genetic algorithms (GA) have shown great advantages in solving the combinatorial optimization problem in view of its characteristic that has high efficiency and that is fit for practical application. In this chapter we present a spreadsheet based GA approach for minimizing the makespan for scheduling of a set of tasks for identical parallel machines and worker assignment to machines. The results obtained from the proposed approach are compared with two sets of benchmark problems consisting of 100 problems each. It has been demonstrated that the performance of proposed approach is superior to the results that have been obtained earlier. The proposed approach produces optimal solution for almost 95% of the problems demonstrating the effectiveness of the proposed approach. An empirical analysis of GA parameters has also been carried out to see the effect on the performance of the proposed algorithm.
Abstract
dentical parallel machine scheduling problem for minimizing the makespan is a very important production scheduling problem which has been proven to be NP-hard. The problem [...]
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A research survey: review of flexible job shop scheduling techniques
I. Chaudhry, A. Khan

International Transactions in Operational Research (2016).

Abstract
In the last 25 years, extensive research has been carried out addressing the flexible job shop scheduling (JSS) problem. A variety of techniques ranging from exact methods to hybrid techniques have been used in this research. The paper aims at presenting the development of flexible JSS and a consolidated survey of various techniques that have been employed since 1990 for problem resolution. The paper comprises evaluation of publications and research methods used in various research papers. Finally, conclusions are drawn based on performed survey results. A total of 404 distinct publications were found addressing the FJSSP. Some of the research papers presented more than one technique/algorithm to solve the problem that is categorized into 410 different applications. Selected time period of these research papers is between 1990 and February 2014. Articles were searched mainly on major databases such as SpringerLink, Science Direct, IEEE Xplore, Scopus, EBSCO, etc. and other web sources. All databases were searched for “flexible job shop” and “scheduling” in the title and
Abstract
In the last 25 years, extensive research has been carried out addressing the flexible job shop scheduling (JSS) problem. A variety of techniques ranging from exact methods [...]
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A layered genetic algorithm with iterative diversification for optimization of flexible job shop scheduling problems
I. Chaudhry

Advances in Production Engineering & Management (2020).
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Integrated process planning and scheduling using genetic algorithms
I. Chaudhry

Tehnički Vjesnik–Technical Gazette (2017).
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Minimisation of total tardiness for identical parallel machine scheduling using genetic algorithm
I. Chaudhry, I. ELBADAWI

Sadhana – Academy Proceedings in Engineering Sciences (2017).

Abstract
In recent years research on parallel machine scheduling has received an increased attention. This paper considers minimisation of total tardiness for scheduling of n jobs on a set of m parallel machines. A spread-sheet-based genetic algorithm (GA) approach is proposed for the problem. The proposed approach is a domain-independent general purpose approach, which has been effectively used to solve this class of problem. The performance of GA is compared with branch and bound and particle swarm optimisation approaches. Two set of problems having 20 and 25 jobs with number of parallel machines equal to 2, 4, 6, 8 and 10 are solved with the proposed approach. Each combination of number of jobs and machines consists of 125 benchmark problems; thus a total for 2250 problems are solved. The results obtained by the proposed approach are comparable with two earlier approaches. It is also demonstrated that a simple GA can be used to produce results that are comparable with problem-specific approach. The proposed approach can also be used to optimise any objective function without changing the basic GA routine.
Abstract
In recent years research on parallel machine scheduling has received an increased attention. This paper considers minimisation of total tardiness for scheduling of n jobs [...]
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Minimising total flowtime in a no-wait flow shop (NWFS) using genetic algorithms
I. Chaudhry

Ingeniería e Investigación (2018).

Abstract
This paper considers a no-wait flow shop scheduling (NWFS) problem, where the objective is to minimise the total flowtime. We propose a genetic algorithm (GA) that is implemented in a spreadsheet environment. The GA functions as an add-in in the spreadsheet. It is demonstrated that with proposed approach any criteria can be optimised without modifying the GA routine or spreadsheet model. Furthermore, the proposed method for solving this class of problem is general purpose, as it can be easily customised by adding or removing jobs and machines. Several benchmark problems already published in the literature are used to demonstrate the problem-solving capability of the proposed approach. Benchmark problems set ranges from small (7-jobs, 7 machines) to large (100-jobs, 10-machines). The performance of the GA is compared with different meta-heuristic techniques used in earlier literature. Experimental analysis demonstrate that solutions obtained in this research offer equal quality as compared to algorithms already developed for NWFS problems.
Abstract
This paper considers a no-wait flow shop scheduling (NWFS) problem, where the objective is to minimise the total flowtime. We propose a genetic algorithm (GA) that is implemented [...]
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Effect of cutting conditions on surface roughness of machined parts in CO2 laser cutting of pure titanium
I. Chaudhry, M. Boujelbene, A. Boudjemline

Materials Today: Proceedings (2021).

Abstract
Titanium (Ti) and its alloys machining has been a long standing issue in the manufacturing industry. The extraordinary Ti machining costs restrict its used in the specialised applications. To achieve improved surface quality, researchers are working tirelessly to optimize various cutting parameters. In this study, high-power CO
Abstract
Titanium (Ti) and its alloys machining has been a long standing issue in the manufacturing industry. The extraordinary Ti machining costs restrict its used in the specialised [...]
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Minimization of completion time variance in flowshops using genetic algorithms
I. Chaudhry, I. Elbadawi, A. Rafique, A. Boudjemline, M. Boujelbene, M. Usman, M. Aichouni

Rev. int. métodos numér. cálc. diseño ing. (2022). Vol. 38, (2), 22

Abstract
The majority of the flowshop scheduling literature focuses on regular performance measures like makespan, flowtime etc. In this paper a flowshop scheduling problem is addressed where the objective is to minimize completion time variance (CTV). CTV is a non-regular performance measure that is closely related to just-in-time philosophy. A Microsoft Excel spreadsheet-based genetic algorithm (GA) is proposed to solve the problem. The proposed GA methodology is domain-independent and general purpose. The flowshop model is developed in the spreadsheet environment using the built-in formulae and function. Addition of jobs and machines can be catered for without the change in the basic GA routine and minimal change to the spreadsheet model. The proposed methodology offers an easy to handle framework whereby the practitioners can implement a heuristic-based optimization tool with the need for advanced programming tools. The performance of the proposed methodology is compared to previous studies for benchmark problems taken from the literature. Simulation experiments demonstrate that the proposed methodology solves the benchmark problems efficiently and effectively with a reasonable accuracy. The solutions are comparable to previous studies both in terms of computational time and solution quality.
Abstract
The majority of the flowshop scheduling literature focuses on regular performance measures like makespan, flowtime etc. In this paper a flowshop scheduling problem is addressed [...]
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Chaudhry, Imran Ali 2625
University of Ha'il

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Preliminary Aircraft Design Optimization Using Genetic Algorithms

Case Based Reasoning Support for Adaptive Finite Element Analysis - Mesh Selection for an Integrated System

Object Oriented Case Representation for CBR Application in Structural Analysis

Identical parallel-machine scheduling and worker assignment problem using genetic algorithms to minimize makespan

A research survey: review of flexible job shop scheduling techniques

A layered genetic algorithm with iterative diversification for optimization of flexible job shop scheduling problems

Integrated process planning and scheduling using genetic algorithms

Minimisation of total tardiness for identical parallel machine scheduling using genetic algorithm

Minimising total flowtime in a no-wait flow shop (NWFS) using genetic algorithms

Effect of cutting conditions on surface roughness of machined parts in CO2 laser cutting of pure titanium

Minimization of completion time variance in flowshops using genetic algorithms

editors

Chaudhry, Imran Ali 2625

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