A hybrid NSGA-II and VNS for solving a bi-objective no-wait flexible flowshop scheduling problem

Asefi, Hossein; Jolai, Fariborz; Rabiee, Meysam; Araghi, M. E. Tayebi

doi:10.1007/s00170-014-6177-9

Cited by 75 publications

(35 citation statements)

References 74 publications

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“…There are various popular methods of parameter calibration, such as the response surface methodology (RSM) and the Taguchi method, which could be used for tuning the parameters of our proposed algorithm. Here, the Taguchi method (Asefi et al [55]; Rabiee et al [56]) was applied to tune the algorithm parameters. This method is designed based on orthogonal arrays and the signal-to-noise ratio (S/N).…”

Section: Discussion For a Random Network A Experimental Designmentioning

confidence: 99%

Designing a Flexible Catering System for High-Speed Railway Considering Departure Time Selection and Time Deadline Constraints

Jiang

Chen

2020

IEEE Access

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A new catering mode is introduced into an existing catering service system for high-speed railways. This flexible catering system for high-speed railways aims to make order allocation decisions and service sequencing decisions under tight time constraints. A departure time and route selection model is established to coordinate the delivery times of the orders with the departure times of the trains to mitigate conflicts between the delivery cost and service level. Sequential constraints are reformulated as soft constraints, and an analytical algorithm is designed to solve for the optimal catering vehicle departure time for a given path. The problem is already complex due to its similarity to the vehicle routing problem with time windows (VRPTW). In particular, the route-dependent lead time and constraint-dependent departure time selection make the problem more complex. Therefore, a simulated annealing algorithm based on a variable neighborhood search (VNS-SA) is employed to solve the model. Finally, a random road network experiment is performed to verify the model and algorithm, and the algorithm's performance and computational efficiency with different combinations of subalgorithms are compared and analyzed. INDEX TERMS Rail catering service, routing model, departure time selection, time window. XIN WU was born in Kunming, Yunnan, China, in 1986. He received the B.S. degree from the Dalian Maritime University, China, in 2009, and the Ph.D. degree from Beijing Jiaotong University, China, in 2018. He is currently a Postdoctoral Research Fellow with the School of Sustainable Engineering and the Built Environment with Arizona State University, USA. His research interests include operations research on logistics management, railway management, public transit, machine learning, and traffic flow theories.

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Section: Discussion For a Random Network A Experimental Designmentioning

confidence: 99%

Designing a Flexible Catering System for High-Speed Railway Considering Departure Time Selection and Time Deadline Constraints

Jiang

Chen

2020

IEEE Access

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“…Asefi et al. () solved an MOHFS problem by applying an approach that combines the characteristics of the NSGA‐II and the VNS metaheuristic for the minimization of both makespan and average tardiness. Already in Ying et al.…”

Section: Literature Reviewmentioning

confidence: 99%

An MO‐GVNS algorithm for solving a multiobjective hybrid flow shop scheduling problem

Siqueira

Souza

2019

Int Trans Operational Res

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This paper addresses the multiobjective hybrid flow shop (MOHFS) scheduling problem. In the MOHFS problem considered here, we have a set of jobs that must be performed in a set of stages. At each stage, we have a set of unrelated parallel machines. Some jobs may skip stages. The evaluation criteria are the minimizations of makespan, the weighted sum of the tardiness, and the weighted sum of the earliness. For solving it, an algorithm based on the multiobjective general variable neighborhood search (MO‐GVNS) metaheuristic, named adapted MO‐GVNS, is proposed. This work also presents and compares the results obtained by the adapted MO‐GVNS with those of four other algorithms: multiobjective reduced variable neighborhood search, nondominated sorting genetic algorithm II (NSGA‐II), and NSGA‐III, and another MO‐GVNS from the literature. The results were evaluated based on the Hypervolume, Epsilon, and Spacing metrics, and statistically validated by the Levene test and confidence interval charts. The results showed the efficiency of the proposed algorithm for solving the MOHFS problem.

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“…In order to enhance the exploitation ability of NSGA-II, the local search ability of VNS is used. By using this method, the quality of offspring is improved separately (Asefi et al, 2014;Moghaddam et al, 2012). In the following, this method will be presented.…”

Section: Hybrid Nsga-ii and Vnsmentioning

confidence: 99%

Modelling a bi-objective airport gate scheduling with controllable processing time using hybrid NSGA-II and VNS algorithm

Khatibi

Bafruei

Rahmani

2019

IJOR

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In this research, we address a bi-objective model in a more realistic situation such that airport gate processing time is controllable. It is assumed that the possible compression/expansion processing time of a flight can be continuously controlled. The aim is simultaneously: 1) minimise the total cost of tardiness, earliness, delay and compression as well as expansion costs of job processing time; 2) minimise the passengers overcrowding on gate. In this study, a mixed-integer programming model is proposed. For solving the problem, two multi-objective meta-heuristic algorithms, namely non-dominated sorting genetic algorithm II (NSGA-II) and hybrid NSGA-II and variable neighbourhood search (VNS) are applied. VNS is used for preventing the solution from trapping in the local optimum, instead of mutation operator in NSGA-II. The algorithms are tested with the real life data from Mehrabad International Airport. Computational experiments reveal that hybrid NSGA-II and VNS generate better Pareto-optimal solution as compared to NSGA-II.

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A hybrid NSGA-II and VNS for solving a bi-objective no-wait flexible flowshop scheduling problem

Cited by 75 publications

References 74 publications

Designing a Flexible Catering System for High-Speed Railway Considering Departure Time Selection and Time Deadline Constraints

Designing a Flexible Catering System for High-Speed Railway Considering Departure Time Selection and Time Deadline Constraints

An MO‐GVNS algorithm for solving a multiobjective hybrid flow shop scheduling problem

Modelling a bi-objective airport gate scheduling with controllable processing time using hybrid NSGA-II and VNS algorithm

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