COLLECTIONS

Documents published in 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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Articles (Documents not available in Scipedia)

• On using neural networks in UAV structural design for CFD data fitting and classification

  Farrukh Mazhar, Abdul Munem Khan, Imran Ali Chaudhry, Mansoor Ahsan

  Aerospace Science and Technology

• Job shop scheduling problem with alternative machines using genetic algorithms

  IA Chaudhry

  Journal of Central South University

• Minimizing makespan for a no-wait flowshop using genetic algorithm

  Imran Ali Chaudhry, Abdul Munem Khan

  Sadhana

• Simultaneous scheduling of machines and automated guided vehicles in flexible manufacturing systems using genetic algorithms

  I A Chaudhry, S Mahmood, M Shami

  Journal of Central South University

• Minimizing makespan for machine scheduling and worker assignment problem in identical parallel machine models using GA

  Imran Ali Chaudhry, Sultan Mahmood, Riaz Ahmad

  Proceedings of the World Congress on Engineering

• Minimizing flow time for the worker assignment problem in identical parallel machine models using GA

  Imran Ali Chaudhry

  International Journal of Advanced Manufacturing Technology

• Minimizing flow-time variance in a single-machine system using genetic algorithms

  Imran Ali Chaudhry, Paul R Drake

  International Journal of Advanced Manufacturing Technology

• From apes to schedules

  PR Drake, IA Choudhry

  Manufacturing Engineer

Conference papers and presentations (Documents not available in Scipedia)

• Genetic Algorithm to minimize flowtime in a no-wait flowshop scheduling problem

  Imran A Chaudhry, Riaz Ahmed, Abdul Munem Khan

  IOP Conference Series: Materials Science and Engineering

• No-wait flowshop scheduling using genetic algorithm

  Imran Ali Chaudhry, Sultan Mahmood

  Proceedings of the World Congress on Engineering

• A genetic algorithm approach for process planning and scheduling in job shop environment

  Imran Ali Chaudhry

  Proceedings of the World Congress on Engineering