A hybrid genetic algorithm approach for the “no-wait” flowshop scheduling problem

Gonazelez, B.; Torres, Michel Soriano; Moreno, José A.

doi:10.1049/cp:19951025

Cited by 10 publications

(4 citation statements)

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“…In general, GA, hybridised with a local search scheme, acts as a global search scheme to enhance both diversification and intensification (Reeves, 1994). Gonazelez et al (1995) hybridised the GA with three problem-oriented operators based on the heuristics developed by Gupta (1971), Palmer (1965) and Rajendran (1994). Park (2001) and Reeves (1995) embedded a greedy local optimisation algorithm in a hybrid GA to solve vehicle scheduling problems.…”

Section: Literature Reviewmentioning

confidence: 99%

An efficient hybrid heuristic method for prioritising large transportation projects with interdependent activities

Bagloee

Tavana

2012

IJLSM

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Transportation projects are generally large, with limited resources and highly interdependent activities. The complexities and interdependencies apparent in large transportation projects have prohibited effective application of management science and economics methods to these problems. We propose a heuristic method with several hybrid components. We formulate the problem as a Travelling Salesman Problem (TSP). A Neural Network (NN) is used to cope with the interdependency concerns. An algorithm with an iterative process is confined to search for the longest path (most benefit or most reduction in the user-time) in the NN as a solution to the TSP. The solution from each iteration step is utilised to update and train the NN and enhance its prediction. A search engine inspired by the concept of Ant Colony (AC) and hybridised with Genetic Algorithm (GA) is developed to find a suitable solution to the TSP. The hybrid heuristic method proposed in this study is applied to the real data for the city of Winnipeg in Canada to demonstrate the applicability of the proposed framework and exhibit the efficacy of the procedures and algorithms.Reference to this paper should be made as follows: Bagloee, S.A. and Tavana, M. (2012) 'An efficient hybrid heuristic method for prioritising large transportation projects with interdependent activities', Int.Biographical notes: Saeed Asadi Bagloee is a Senior Transportation Planner and lead modeller at Parsons Overseas Limited in Dubai, UAE. He received his BS in Civil Engineering from Khaje Nasir Toosi University of Technology and his MS in Transportation Planning and Engineering from Sharif University of Technology in Tehran, Iran. His research interest is transportation planning and modelling including travel demand forecasting, traffic impact studies, road network design and transit planning and economic analysis of transportation projects. He has conducted extensive research at the Institute for Transportation Studies and Research at Sharif University of Technology and has presented and published his research in several international conferences and proceedings.

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Section: Literature Reviewmentioning

confidence: 99%

An efficient hybrid heuristic method for prioritising large transportation projects with interdependent activities

Bagloee

Tavana

2012

IJLSM

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“…Manufacturing engineering applications fall into the two general categories of planning functions and shape design [11]. Many manufacturing applications are systems-based, including job-shop scheduling [12], flow-shop scheduling [13], assembly line balancing [14] and production planning [15].…”

Section: Literature Reviewmentioning

confidence: 99%

Shape modification using genetic algorithms

Case

Graham

Wood

2004

Proceedings of the Institution of Mechanical Engineers, Part B:

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This paper describes research into the use of a genetic algorithm within a computer aided design tool. The genetic algorithm allows the evolution of shape aspects of designs against a subjective rating carried out by the designer. Shapes considered by the designer to contain pleasing characteristics are used to generate subsequent generations of different, but related, shapes. A genetic data structure made up of chromosomes is briefly described along with the methods used to evolve new generations of objects using reproduction methods involving crossover of chromosomes and the chance of mutation. Examples are given where the technique is used to generate 'animal sculptures', product concepts and a variety of concepts for seating.

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“…In this case, jobs consisted of splitable lots, and an efficient EA was used to simultaneously optimize the ordering of jobs and the lot sizing. Gonzalez et al [88] considered the "no-wait" version of the job-sequencing problem, where once the processing of a job has started in the first machine of the production line, there must be no time delay between the consequent operations of the job in the following machines. An EA enhanced with heuristic methods was used for the solution of the problem.…”

Section: ) Variations From the Basic Formmentioning

confidence: 99%

“…It was originally deigned for the TSP, and its main characteristic is that it preserves adjacency information from the parents. It has recently been used by Sikora [82], Lee et al [87], and Gonzalez et al [88] in job-sequencing problems.…”

Section: Operators 1) Crossover Operatormentioning

confidence: 99%

Recent developments in evolutionary computation for manufacturing optimization: problems, solutions, and comparisons

Dimopoulos

Zalzala

2000

IEEE Trans. Evol. Computat.

229

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The use of intelligent techniques in the manufacturing field has been growing the last decades due to the fact that most manufacturing optimization problems are combinatorial and NP hard. This paper examines recent developments in the field of evolutionary computation for manufacturing optimization. Significant papers in various areas are highlighted, and comparisons of results are given wherever data are available. A wide range of problems is covered, from job shop and flow shop scheduling, to process planning and assembly line balancing.

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A hybrid genetic algorithm approach for the “no-wait” flowshop scheduling problem

Cited by 10 publications

References 0 publications

An efficient hybrid heuristic method for prioritising large transportation projects with interdependent activities

An efficient hybrid heuristic method for prioritising large transportation projects with interdependent activities

Shape modification using genetic algorithms

Recent developments in evolutionary computation for manufacturing optimization: problems, solutions, and comparisons

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