A memetic algorithm for the total tardiness single machine scheduling problem

França, Paulo Morelato; Mendes, Alexandre; Moscato, Pablo

doi:10.1016/s0377-2217(00)00140-5

Cited by 156 publications

(71 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The limited time and other parameters can be obtained by an adjustment method [18,21]. An image set for training should be selected from the database before the adjustment.…”

Section: Evaluation Indicator and Parametersmentioning

confidence: 99%

See 1 more Smart Citation

Heuristic hybrid genetic algorithm based shape matching approach for the pose detection of backlight units in LCD module assembly

Cai

2016

Int J Adv Manuf Technol

View full text Add to dashboard Cite

Backlight unit (BLU) and open cell are two critical parts of the liquid crystal display (LCD) module (LCM) which is the most significant component of LCD TV.To place the open cell into a BLU automatically using an assembly robot, this paper proposes a heuristic hybrid genetic algorithm (HHGA) based shape matching approach to detect the pose (orientation and position) of the BLU. The approach takes advantages of line structures of the BLUs to avoid the most time-consuming exhaustive search. Firstly, obtain initial orientation of a BLU by the dominant orientations which can be obtained with the statistical gradient orientation histograms. Secondly, search the optimal pose through the HHGA which mainly consists of local search strategy, crossover strategy, clone strategy, and mutation strategy. Local search strategy is designed according to the rising trend of matching features around the optimal pose and along the lines. Crossover and clone are heuristic strategies designed according to the distribution characteristics of local maxima to produce new meaningful offspring. Mutation is a necessary strategy to keep the diversity of the population. The performance of the proposed approach has been tested on an image database acquired from the LCM assembly lines and compared with standard hybrid

show abstract

“…The limited time and other parameters can be obtained by an adjustment method [18,21]. An image set for training should be selected from the database before the adjustment.…”

Section: Evaluation Indicator and Parametersmentioning

confidence: 99%

“…The ranges for different parameters in second column are computed according to the probability of finding the optimal position in next generation through different strategies. The steps in third column are empirical values [18,21,22]. The best parameters got by the adjustment method are shown in last two columns.…”

Section: Evaluation Indicator and Parametersmentioning

confidence: 99%

Heuristic hybrid genetic algorithm based shape matching approach for the pose detection of backlight units in LCD module assembly

Cai

2016

Int J Adv Manuf Technol

View full text Add to dashboard Cite

show abstract

“…MAs aim to balance the exploration and exploitation capabilities of both genetic algorithms and local search. Many researchers already highlighted the effectiveness of integrating meme(s) into evolutionary algorithms for solving complex optimization problems based on various frameworks [1,2,13,30,38,40,48,53,54]. In a canonical MA, a prefixed single meme is employed after mutation and evaluation steps of a GA. Obviously, a variety of memes might be designed for solving a specific problem.…”

Section: 2 Memes and Self-generationmentioning

confidence: 99%

A case study of memetic algorithms for constraint optimization

Özcan

Başaran

2008

Soft Comput

View full text Add to dashboard Cite

There is a variety of knapsack problems in the literature. Multidimensional 0-1 Knapsack Problem (MKP) is an NP-hard combinatorial optimization problem having many application areas. Many approaches have been proposed for solving this problem. In this paper, an empirical investigation of memetic algorithms (MAs) that hybridize genetic algorithms (GAs) with hill climbing for solving MKPs is provided. Two distinct sets of experiments are performed.During the initial experiments, MA parameters are tuned. GA and four MAs each using a different hill climbing method based on the same configuration are evaluated. In the second set of experiments, a self-adaptive (co-evolving) multimeme memetic algorithm (MMA) is compared to the best MA from the parameter tuning experiments. MMA utilizes the evolutionary process as a learning mechanism for choosing the appropriate hill climbing method to improve a candidate solution at a given time. Two well-known MKP benchmarks are used during the experiments.

show abstract

“…They compared the performance of four different algorithms namely; branch-and-bound, genetic search, SA and random-start pair wise interchange algorithms. França et al (2001) proposed a MA and also a GA for the total tardiness single machine scheduling problem. Gagne et al (2002) developed an ACO algorithm for the single machine scheduling problem with sequence-dependent setup times.…”

Section: Introductionmentioning

confidence: 99%

A hybrid cuckoo search metaheuristic algorithm for solving single machine total weighted tardiness scheduling problems with sequence dependent setup times

Marichelvam¹,

Mani²

2016

IJCCIA

View full text Add to dashboard Cite

Abstract:In this paper, we present a hybrid algorithm based on cuckoo search algorithm to solve the single machine total weighted tardiness (SMTWT) scheduling problems with sequence dependent setup times which have been proved to be strongly NP-hard. Three different dispatching rules are incorporated with the initial random solutions of the cuckoo search (CS) algorithm to improve the solution quality. Computational results show that the proposed algorithm is very competitive to many metaheuristic algorithms in the literature.Keywords: metaheuristics; cuckoo search; total weighted tardiness; NP-hard; scheduling.Reference to this paper should be made as follows: Marichelvam, M.K. and Geetha, M. (2016) 'A hybrid cuckoo search metaheuristic algorithm for solving single machine total weighted tardiness scheduling problems with sequence dependent setup times', Int.

show abstract

A memetic algorithm for the total tardiness single machine scheduling problem

Cited by 156 publications

References 19 publications

Heuristic hybrid genetic algorithm based shape matching approach for the pose detection of backlight units in LCD module assembly

Heuristic hybrid genetic algorithm based shape matching approach for the pose detection of backlight units in LCD module assembly

A case study of memetic algorithms for constraint optimization

A hybrid cuckoo search metaheuristic algorithm for solving single machine total weighted tardiness scheduling problems with sequence dependent setup times

Contact Info

Product

Resources

About