A hybrid artificial neural network, genetic algorithm and column generation heuristic for minimizing makespan in manual order picking operations

Ardjmand, Ehsan; Ghalehkhondabi, Iman; Young, William A.; Sadeghi, Azadeh; Weckman, Gary R.; Shakeri, Heman

doi:10.1016/j.eswa.2020.113566

Cited by 38 publications

(24 citation statements)

References 48 publications

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“…Structurally, and from an operational standpoint, order picking problems are composed of four sub-problems of order batching, batch assignment, batch sequencing, and picker routing [15] , [16] , [17] , among which order batching and picker routing are the subjects of this study. Order batching is primarily revolving around grouping a set of customer orders in such a manner to achieve a set of operational objectives such as total travel time or tardiness minimization [18] , [19] , [20] .…”

Section: Literature Reviewmentioning

confidence: 99%

“…In the picker routing problem, the objective is to form the shortest possible path for picking the batches. Warehouse routing problems are usually modeled as a special case of the traveling salesman problem (TSP), known as Steiner TSP, where each visiting node has a maximum degree of four [17] . Since it was shown that Steiner TSPs encountered in rectangular warehouses with two cross-aisles are solvable in polynomial time [24] , several solvable cases of warehouse TSPs have been introduced, and efficient methodologies are developed for more general warehouse architectures [25] , [26] , [27] .…”

Section: Literature Reviewmentioning

confidence: 99%

“…To tame the complexity of the integrated problem, and replicate a more realistic scenario, some studies have concentrated on exact batching solutions in the presence of heuristic routing policies [7] , [9] , [51] , [61] . On the other hand, some studies have exclusively applied heuristics and metaheuristics [29] , [30] , [46] , [47] , [57] , [62] , [69] , or a different combination of exact and heuristic approaches [17] .…”

Section: Literature Reviewmentioning

confidence: 99%

“…One distinctive feature of order picking problems is their choice of the objective function. Three objectives of total travel time, tardiness, and makespan are the most frequently utilized objectives in the literature, among which total travel time and makespan are the most and least regularly considered objectives [17] . While at least one of these objectives seem to fulfill the requirements of any warehouse, the recent supply chain disruptions pertaining to coronavirus outbreak (COVID-19/SARS-CoV-2) pandemic points to a possible gap in the order picking operational objectives.…”

Section: Literature Reviewmentioning

confidence: 99%

See 3 more Smart Citations

Mitigating the risk of infection spread in manual order picking operations: A multi-objective approach

Ardjmand

Singh²,

Shakeri

et al. 2021

Applied Soft Computing

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In the aftermath of the COVID-19 pandemic, supply chains experienced an unprecedented challenge to fulfill consumers’ demand. As a vital operational component, manual order picking operations are highly prone to infection spread among the workers, and thus, susceptible to interruption. This study revisits the well-known order batching problem by considering a new overlap objective that measures the time pickers work in close vicinity of each other and acts as a proxy of infection spread risk. For this purpose, a multi-objective optimization model and three multi-objective metaheuristics with an effective seeding procedure are proposed and are tested on the data obtained from a major US-based logistics company. Through extensive numerical experiments and comparison with the company’s current practices, the results are discussed, and some managerial insights are offered. It is found that the picking capacity can have a determining impact on reducing the risk of infection spread through minimizing the picking overlap.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

See 2 more Smart Citations

Mitigating the risk of infection spread in manual order picking operations: A multi-objective approach

Ardjmand

Singh²,

Shakeri

et al. 2021

Applied Soft Computing

Self Cite

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“…erefore, this paper uses the method of deleting the individuals with high similarity in the initialized population, and only one similar individual needs to be retained. In the process of offspring genetic evolution, no matter which generation has individuals with high similarity, it is necessary to delete the redundant individuals and keep one [26].…”

Section: Research On the Social Talent Governancementioning

confidence: 99%

Research on Social Talent Governance Based on Genetic Algorithm

Zeng

2021

Scientific Programming

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The existing social talent governance algorithms have a number of issues such as slow convergence rate, relatively low data accuracy, recall rate, and low anti-interference. To address these problems, this paper proposes a research on social talent governance algorithm based on genetic algorithm. We discuss the difference between the traditional and the genetic algorithms and determine the implementation process of genetic algorithm. On this basis, the excellent individuals are determined by independent computing fitness, and the initialization population is designed according to the individual similarity threshold. After the population is defined, the roulette and deterministic sampling selection method are integrated to clarify the selection calculation process. Based on the calculation results, we design the crossover operator by segmented single-point crossover between individuals. The mutation operator is designed by segmented mutation of different gene segments according to the calculation results. The results are incorporated into the simulated annealing acceptance probability to conduct simulated annealing for the individuals after the cross-mutation operation and set relevant conditions after the end of the algorithm. We seek the optimal solution of the data within the number of iterations and finally realize the whole process of social talent governance algorithm. The experimental results show that the proposed algorithm has fast convergence rate, high data precision and recall, and has certain feasibility.

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Technique of Metals Strength Properties Diagnostics Based on the Complex Use of Fuzzy Inference System and Hybrid Neural Network

Babichev

Durnyak

Sharko

et al. 2020

Communications in Computer and Information Science

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A hybrid artificial neural network, genetic algorithm and column generation heuristic for minimizing makespan in manual order picking operations

Cited by 38 publications

References 48 publications

Mitigating the risk of infection spread in manual order picking operations: A multi-objective approach

Mitigating the risk of infection spread in manual order picking operations: A multi-objective approach

Research on Social Talent Governance Based on Genetic Algorithm

Technique of Metals Strength Properties Diagnostics Based on the Complex Use of Fuzzy Inference System and Hybrid Neural Network

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