General Variable Neighborhood Search for the Order Batching and Sequencing Problem

Menéndez, Borja; Bustillo, Manuel; Pardo, Eduardo G.; Duarte, Abraham

doi:10.1016/j.ejor.2017.05.001

Cited by 67 publications

(18 citation statements)

References 26 publications

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“…In our numerical experiments, the set of instances considers 4 different number of distribution tasks (N={24,48,72,96}), where the number of items per task is uniformly distributed in {5,6,...,25}. The carrying capacity of vehicles is fixed to 45 [12] . The delivery time for each task is chosen from the interval…”

Section: Methodsmentioning

confidence: 99%

Workstation-oriented distribution optimization of shipbuilding materials

et al. 2019

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The optimization of material distribution is of great importance on shipbuilding project, which determines whether the production capacity of the ship is fully embodied. A workstation-oriented material distribution problem is formulated with reference to the production characteristics of shipyards. This problem can be considered as a complex vehicle routing problem (VRP) with capacity constraints, time windows and multiple distribution centers. In order to minimize the impact of distribution problems on production, a multi-population genetic algorithm (MPGA) that can minimize the sum of earliness and tardiness penalties is proposed in this paper. The proposed algorithm looks for near-optimal solutions for assigning distribution tasks and optimizing vehicle routing. Then, the evaluation of the solutions generated with MPGA is achieved with a priority-based heuristic algorithm. Simulation results of different cases show that the proposed MPGA allows logistics distribution system to operate more efficiently and solutions can be improved by 71% on average compared to those obtained with the traditional priority rule method.

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Section: Methodsmentioning

confidence: 99%

Workstation-oriented distribution optimization of shipbuilding materials

et al. 2019

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“…Computational results were presented for a warehouse with six aisles. Menendez et al [2017a] presented a variable neighbourhood search heuristic for order batching where each order has a specified due date. They aim to batch orders and route the batches so as to minimise total tardiness.…”

Section: Early Workmentioning

confidence: 99%

Order batching using an approximation for the distance travelled by pickers

Valle

Beasley

2020

European Journal of Operational Research

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In this paper we investigate the problem of order batching for picker routing. Our approach is applicable to warehouses (storage areas) arranged in the standard rectangular grid layout, so with parallel aisles and two or more cross-aisles. The motivation underlying our work is online grocery shopping in which orders may be composed of dozens of items. The approach presented directly addresses order batching, but uses a distance approximation to influence the batching of orders without directly addressing the routing problem.We present a basic formulation based on deciding the orders to be batched together so as to optimise an objective that approximates the picker routing distance travelled. We extend our formulation by improving the approximation for cases where we have more than one block in the warehouse. We present constraints to remove symmetry in order to lessen the computational effort required, as well as constraints that significantly improve the value of the linear programming relaxation of our formulation. A heuristic algorithm based on partial integer optimisation of our mathematical formulation is also presented. Once order batching has been decided we optimally route each individual picker using a previous approach presented in the literature.Extensive computational results for publicly available test problems involving up to 75 orders are given for both single and multiple block warehouse configurations.

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“…Concerning to achieve picking efficiency, the order batching groups customer orders into batches with a maximum fixed capacity [6], then the batches are assigned to a picking device and batch sequencing determines the picking scheduling and the completion time batches and customer orders [3,7]. Therefore, the joint order batching and sequencing problem with multiple pickers (OBSPMP) is pivotal to enhance the efficiency and customer service [8][9][10].…”

Section: Introductionmentioning

confidence: 99%

Solving the order batching and sequencing problem with multiple pickers: A grouped genetic algorithm

Cano

Cortés

Campo³

et al. 2021

IJECE

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This paper introduces a grouped genetic algorithm (GGA) to solve the order batching and sequencing problem with multiple pickers (OBSPMP) with the objective of minimizing total completion time. To the best of our knowledge, for the first time, an OBSPMP is solved by means of GGA considering picking devices with heterogeneous load capacity. For this, an encoding scheme is proposed to represent in a chromosome the orders assigned to batches, and batches assigned to picking devices. Likewise, the operators of the proposed algorithm are adapted to the specific requirements of the OBSPMP. Computational experiments show that the GGA performs much better than six order batching and sequencing heuristics, leading to function objective savings of 18.3% on average. As a conclusion, the proposed algorithm provides feasible solutions for the operations planning in warehouses and distribution centers, improving margins by reducing operating time for order pickers, and improving customer service by reducing picking service times.

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General Variable Neighborhood Search for the Order Batching and Sequencing Problem

Cited by 67 publications

References 26 publications

Workstation-oriented distribution optimization of shipbuilding materials

Workstation-oriented distribution optimization of shipbuilding materials

Order batching using an approximation for the distance travelled by pickers

Solving the order batching and sequencing problem with multiple pickers: A grouped genetic algorithm

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