Multi-objective 3D bin packing problem with load balance and product family concerns

Erbayrak, Seda; Özkır, Vildan; Yıldırım, Umman Mahir

doi:10.1016/j.cie.2021.107518

Cited by 31 publications

(13 citation statements)

References 29 publications

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“…The packing problem in a retail context in the BOPS model has not been addressed in the literature thus far. An inspiring point to this work is the bin packing problem [21] or 3D bin packing problem [22], which is usually used for the design of item positioning on unit load devices such as containers and pallets.…”

Section: Literature Reviewmentioning

confidence: 99%

The Buy-Online-Pick-Up-in-Store Retailing Model: Optimization Strategies for In-Store Picking and Packing

et al. 2021

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Online shopping is growing fast due to the increasingly widespread use of digital services. During the COVID-19 pandemic, the desire for contactless shopping has further changed consumer behavior and accelerated the acceptance of online grocery purchases. Consequently, traditional brick-and-mortar retailers are developing omnichannel solutions such as click-and-collect services to fulfill the increasing demand. In this work, we consider the Buy-Online-Pick-up-in-Store concept, in which online orders are collected by employees of the conventional stores. As labor is a major cost driver, we apply and discuss different optimizing strategies in the picking and packing process based on real-world data from a German retailer. With comparison of different methods, we estimate the improvements in efficiency in terms of time spent during the picking process. Additionally, the time spent on the packing process can be further decreased by applying a mathematical model that guides the employees on how to organize the articles in different shopping bags during the picking process. In general, we put forward effective strategies for the Buy-Online-Pick-up-in-Store paradigm that can be easily implemented by stores with different topologies.

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Section: Literature Reviewmentioning

confidence: 99%

The Buy-Online-Pick-Up-in-Store Retailing Model: Optimization Strategies for In-Store Picking and Packing

et al. 2021

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“…Some works consider the physical features and the applications' requirements [9,10]. For example, [11] works under the constraints of load balance and family unity, which encourages packing the same types of products together. Ref.…”

Section: Introductionmentioning

confidence: 99%

Compliant‐based robotic 3D bin packing with unavoidable uncertainties

Shuai

Gao

et al. 2023

IET Control Theory & Appl

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Robotic 3D bin packing (R‐3dBPP), aiming to place deformed cases in various sizes in the container without fences, is a comprehensive application that includes perception, planning, execution, and hardware design. Traditional studies assume that the context of the real space must be accurately perceived and represented. However, disjunctions between the planner and reality are unavoidable in R‐3dBPP, especially with low‐cost sensors. As far as the author knows, there is no practical solution. In this paper, the above assumption is discarded and the typical types of uncertainties prevalent to guide the design of the algorithms are formulated. A new online bin‐packing algorithm is proposed, keeping deformed boxes stacked in close contact with each other, so that the whole pallet is kept stable by friction between the boxes and the container. In order to meet the requirement of close contact under the non‐negligible errors from sensors and planners, a compliant‐based motion planning system is introduced. It replaces the precision‐based feedback with a compliant end‐effector and accompanying motion strategies. Last but not least, a complete online bin‐packing robot system is developed and the system's performance under the influence of the uncertainties mentioned above through simulation and physical experiments is evaluated.

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“…Bódis Attila and Balogh János applied scenarios to BPP in 2019 3 . Erba yrak Seda et al considered multi-objective 3D-BPP with load balance and product family 4 .…”

Section: Introductionmentioning

confidence: 99%

An empirically efficient two-phase heuristic algorithm for two-dimensional bin packing problem

Hu²

2022

6th International Conference on Mechatronics and Intelligent Robotics (ICMIR2022)

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This paper reconsidered the Two-Dimensional Bin Packing Problem from the perspective of practical application based on actual needs of small furniture companies in China. Although there have been many researches on this problem for many years, most of the existed researches put their foremost attention on developing an algorithm with low complexity or approximately best performance which means that it can nearly work out the best solution most of the time. This is the common situation when we do research on such problems, but unfortunately it will leave out abundant practical needs. For example, the computational resources of those small companies are seldom, which makes it impossible to use algorithms that almost gets the best solution but takes much time. The significant goal is to find out a solution satisfactory enough within a short time, so some complex algorithms which aim to get a nearly best result aren't suitable here. Meanwhile, the cutting times are also a rather critical matter for them. Cutting too many times will cause high wastage to machines and is therefore unaffordable for small companies, but this was often ignored in previous researches especially in classic meta-heuristic algorithms since they frequently lead to complicated packing patterns with massive cutting times. This paper reviewed previous related researches and summarized their shortages and some necessary characteristics of a practically efficient algorithm. Based on classic algorithms, it gained a two-stage heuristic algorithm which performed better than current used ones in those small companies, as well as meets their special needs stated in this paper which is a rather important issue. And this algorithm itself may be used to meet needs of those factories or be used as a starter of the further optimization search.

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Multi-objective 3D bin packing problem with load balance and product family concerns

Cited by 31 publications

References 29 publications

The Buy-Online-Pick-Up-in-Store Retailing Model: Optimization Strategies for In-Store Picking and Packing

The Buy-Online-Pick-Up-in-Store Retailing Model: Optimization Strategies for In-Store Picking and Packing

Compliant‐based robotic 3D bin packing with unavoidable uncertainties

An empirically efficient two-phase heuristic algorithm for two-dimensional bin packing problem

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