Journal Article10.1016/J.COR.2008.11.009
A genetic algorithm for the proportionate multiprocessor open shop
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TL;DR: A compu-search methodology (a genetic algorithm (GA) is developed to schedule the shop with the objective of minimizing the makespan and successful experiments on large-scale problem instances suggest the readiness of the GA for industrial use.
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About: This article is published in Computers & Operations Research. The article was published on 01 Sep 2009. The article focuses on the topics: Schedule & Job shop scheduling.
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Citations
Optimization of capacity and operation for CCHP system by genetic algorithm
TL;DR: Based on the energy flow of combined cooling, heating and power (CCHP) system, the capacity and operation of CCHP system are optimized by genetic algorithm (GA) so as to maximize the technical, economical and environmental benefits achieved by CCHPs system in comparison to separation production system.
436
Mixed-integer linear programming and constraint programming formulations for solving distributed flexible job shop scheduling problem
TL;DR: The results show that the sequence-based MILP model is the most efficient one, and the proposed CP model is effective in finding good quality solutions for the both the small-sized and large-sized instances.
214
A hybrid imperialist competitive algorithm for minimizing makespan in a multi-processor open shop
TL;DR: A hybrid imperialist competitive algorithm (ICA) with genetic algorithm (GA) is presented to solve the multi-processor open shop scheduling problems to minimize the makespan with considering independent setup time and sequence dependent removal time.
66
Multi-disciplinary planning in health care: a review.
TL;DR: A review of the literature and cross-relations between different applications is provided and multiple fields to classify the literature upon are identified, which provides a broad and thorough overview of the present research.
52
A bi-objective possibilistic programming model for open shop scheduling problems with sequence-dependent setup times, fuzzy processing times, and fuzzy due dates
Samane Noori-Darvish,Iraj Mahdavi,Nezam Mahdavi-Amiri +2 more
- 01 Apr 2012
TL;DR: A novel bi-objective possibilistic mixed-integer linear programming model is presented and the results are compared with the ones obtained by the well-known SPEA-II, using design of experiments (DOE) based on some performance metrics.
45
References
•Book
Adaptation in natural and artificial systems
John H. Holland
- 01 Jan 1975
TL;DR: Names of founding work in the area of Adaptation and modiication, which aims to mimic biological optimization, and some (Non-GA) branches of AI.
•Book
Scheduling: Theory, Algorithms, and Systems
Michael Pinedo
- 15 Jul 1994
TL;DR: Scheduling will serve as an essential reference for professionals working on scheduling problems in manufacturing and computing environments and Graduate students in operations management, operations research, industrial engineering and computer science will find the book to be an accessible and invaluable resource.
7.2K
The Complexity of Flowshop and Jobshop Scheduling
TL;DR: The results are strong in that they hold whether the problem size is measured by number of tasks, number of bits required to express the task lengths, or by the sum of thetask lengths.
2.6K
•Book
Genetic Algorithms and Simulated Annealing
Lawrence Davis
- 01 Jan 1987
TL;DR: A detergent composition mainly for automatic laundering machines which comprises, on the basis of 100 parts by weight of total composition, at least 60 parts of soap and no more than 10 parts of a mixture of surfactants which impart an excellent detergent ability and foam control even in very soft waters and non-polluting properties.
1.8K
Genetic Algorithms and Random Keys for Sequencing and Optimization
TL;DR: A general genetic algorithm to address a wide variety of sequencing and optimization problems including multiple machine scheduling, resource allocation, and the quadratic assignment problem is presented.
1.5K