A computer-based heuristic for packing pooled shipment containers

Gehring, Hermann; Menschner, K.; Meyer, Mark J.

doi:10.1016/0377-2217(90)90363-g

Cited by 112 publications

(52 citation statements)

References 2 publications

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“…According to the optimized performance criteria and constraints, the CLP may have several variants including the knapsack loading, bin packing, and strip packing problems. The knapsack loading problem (Gehring et al, 1990;Pisinger, 2002) aims to load rectangular boxes into a rectangular container of fixed dimensions such that volume utilization is maximized. In the bin packing problem (BPP) (Martello et al, 2000;Faroe et al, 2003) the objective is to minimize the total number of containers (bins), or minimize the shipping cost, required to pack all items; containers can have fixed or varying dimensions.…”

Section: Literature Reviewmentioning

confidence: 99%

A New Prioritizing-Stacking Heuristic Algorithm for the Inner-City Truck Loading Problem

Altarazi¹

2013

IJBM

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Efficiently solving the truck loading problem (TLP) is crucial for achieving urban logistics objectives. Many heuristics, mainly based on wall-building and layer-building concepts, are presented in literature to solve this NP-hard problem. The current research presents a two-step novel prioritization-stacking heuristic algorithm for solving the TLP. The new algorithm primarily aims to improve the truck space utilization and reduce inventory costs at origin and destination points. In particular, the current work considers developing countries conditions in which demand is uncertain, cost minimization is prioritized over customer service, and routing optimization is complicated by a lot of traffic jams. The performance of the proposed heuristic is evaluated by applying it to a real-life case study from the Jordanian market. Additionally, the stacking part of the proposed heuristic is benchmarked with a literature data sample. Both implementations have proved the validity of the suggested heuristic algorithm.

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Section: Literature Reviewmentioning

confidence: 99%

A New Prioritizing-Stacking Heuristic Algorithm for the Inner-City Truck Loading Problem

Altarazi¹

2013

IJBM

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“…Gehring et al's paper [9] presents a heuristic for packing non-identical items within a container. They, like George and Robinson [4], utilized the idea of packing sections of the container across the full width and height.…”

Section: Review Of Relevant Literaturementioning

confidence: 99%

Solving the Three-Dimensional Palet-Paking Problem Using Mixed 0 - 1 Model

Al-Shayea¹

2011

JSSM

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“…In this study, the width of each layer L w is set equal to the width of the Layer Determining Box (LDB) (Gehring et al 1990). In order to determine the LDB, rst, the boxes among the set of available boxes are sorted by width dimension in a non-increasing order.…”

Section: Determination Of Layer Dimensionsmentioning

confidence: 99%

“…Numerous papers have been published on CL problem and related problems. e overview of literature reveals that most of the published works on the subject utilizes di erent types of data structures (Morabito and Arenales 1994;Eley 2002;Lim et al 2005), heuristic algorithms (George and Robinson 1980;Bischo and Marriott 1990;Gehring et al 1990;Haessler and Talbot 1990;Ngoi et al 1994;Pisinger 2002;Bischo 2003;Moura and Oliveira 2005), meta-heuristic algorithms Bortfeldt 1997, 2002;Yeung and Tang 2005;Faina 2000;Bortfeldt and Gehring 2001) and some parallel approaches (Gehring and Bortfeldt 2002;Bortfeldt et al 2003;Mack et al 2004). In most of these approaches, the aim was to ll the container with better volume utilization than the others.…”

Section: Introductionmentioning

confidence: 99%

Development of a Decision Support System for Solving Container Loading Problems

Dereli

Daş

2010

Transport

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Abstract. e globalization of supply chains and rising fuel costs are forcing container carriers both to minimize the number of trips and to maximize available container space. is makes container loading (CL) a critical process especially in real-life applications. Container loading (CL), which is a di cult problem to be solved, has many applications in container transportation and distribution industries. is article presents a container loading support system (CLSS). e proposed CLSS composes of three main components, including a hybrid Bees Algorithm as the main computational algorithm, the graphical user interface (GUI) and a simulation program. e aim of the designed system is to make the packing pattern more visible to the user in order to simplify the loading process. An illustrative examplea CL problem from literature -is also provided to introduce the operation of the system and to prove its e ciency.

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A computer-based heuristic for packing pooled shipment containers

Cited by 112 publications

References 2 publications

A New Prioritizing-Stacking Heuristic Algorithm for the Inner-City Truck Loading Problem

A New Prioritizing-Stacking Heuristic Algorithm for the Inner-City Truck Loading Problem

Solving the Three-Dimensional Palet-Paking Problem Using Mixed 0 - 1 Model

Development of a Decision Support System for Solving Container Loading Problems

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