scholarly journals Metaheuristic algorithms for one-dimensional bin-packing problems: A survey of recent advances and applications

2021 ◽  
Vol 30 (1) ◽  
pp. 636-663
Author(s):  
Chanaleä Munien ◽  
Absalom E. Ezugwu
Keyword(s):  
Bin Packing ◽  
Optimization Problems ◽  
Packing Problem ◽  
Population Based ◽  
Metaheuristic Algorithms ◽  
Packing Problems ◽  
One Dimensional ◽  
Reference Guide ◽  
Recent Advances ◽  
The One

Abstract The bin-packing problem (BPP) is an age-old NP-hard combinatorial optimization problem, which is defined as the placement of a set of different-sized items into identical bins such that the number of containers used is optimally minimized. Besides, different variations of the problem do exist in practice depending on the bins dimension, placement constraints, and priority. More so, there are several important real-world applications of the BPP, especially in cutting industries, transportation, warehousing, and supply chain management. Due to the practical relevance of this problem, researchers are consistently investigating new and improved techniques to solve the problem optimally. Nature-inspired metaheuristics are powerful algorithms that have proven their incredible capability of solving challenging and complex optimization problems, including several variants of BPPs. However, no comprehensive literature review exists on the applications of the metaheuristic approaches to solve the BPPs. Therefore, to fill this gap, this article presents a survey of the recent advances achieved for the one-dimensional BPP, with specific emphasis on population-based metaheuristic algorithms. We believe that this article can serve as a reference guide for researchers to explore and develop more robust state-of-the-art metaheuristics algorithms for solving the emerging variants of the bin-parking problems.

A New Branch-and-Price-and-Cut Algorithm for One-Dimensional Bin-Packing Problems

2020 ◽  
Vol 32 (2) ◽  
pp. 428-443
Author(s):  
Lijun Wei ◽  
Zhixing Luo ◽  
Roberto Baldacci ◽  
Andrew Lim
Keyword(s):  
Bin Packing ◽  
Large Family ◽  
Exact Algorithm ◽  
Packing Problem ◽  
Set Partitioning ◽  
Branch And Price ◽  
Packing Problems ◽  
One Dimensional ◽  
Bin Packing Problem ◽  
The One

In this paper, a new branch-and-price-and-cut algorithm is proposed to solve the one-dimensional bin-packing problem (1D-BPP). The 1D-BPP is one of the most fundamental problems in combinatorial optimization and has been extensively studied for decades. Recently, a set of new 500 test instances were proposed for the 1D-BPP, and the best exact algorithm proposed in the literature can optimally solve 167 of these new instances, with a time limit of 1 hour imposed on each execution of the algorithm. The exact algorithm proposed in this paper is based on the classical set-partitioning model for the 1DBPPs and the subset row inequalities. We describe an ad hoc label-setting algorithm to solve the pricing problem, dominance, and fathoming rules to speed up its computation and a new primal heuristic. The exact algorithm can easily handle some practical constraints, such as the incompatibility between the items, and therefore, we also apply it to solve the one-dimensional bin-packing problem with conflicts (1D-BPPC). The proposed method is tested on a large family of 1D-BPP and 1D-BPPC classes of instances. For the 1D-BPP, the proposed method can optimally solve 237 instances of the new set of difficult instances; the largest instance involves 1,003 items and bins of capacity 80,000. For the 1D-BPPC, the experiments show that the method is highly competitive with state-of-the-art methods and that it successfully closed several open 1D-BPPC instances.

scholarly journals An Adaptive Fitness-Dependent Optimizer for the One-Dimensional Bin Packing Problem

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 97959-97974 ◽  
Author(s):  
Diaa Salama Abdul-Minaam ◽  
Wadha Mohammed Edkheel Saqar Al-Mutairi ◽  
Mohamed A. Awad ◽  
Walaa H. El-Ashmawi
Keyword(s):  
Bin Packing ◽  
Packing Problem ◽  
One Dimensional ◽  
Bin Packing Problem ◽  
The One

Solving the one-dimensional bin packing problem with a weight annealing heuristic

2008 ◽  
Vol 35 (7) ◽  
pp. 2283-2291 ◽  
Author(s):  
Kok-Hua Loh ◽  
Bruce Golden ◽  
Edward Wasil
Keyword(s):  
Bin Packing ◽  
Packing Problem ◽  
One Dimensional ◽  
Bin Packing Problem ◽  
The One

GENERALIZED FIRST-FIT ALGORITHMS IN TWO AND THREE DIMENSIONS

1990 ◽  
Vol 01 (02) ◽  
pp. 131-150 ◽  
Author(s):  
KEQIN LI ◽  
KAM-HOI CHENG
Keyword(s):  
Bin Packing ◽  
Three Dimensional ◽  
Packing Problem ◽  
Three Dimensions ◽  
Performance Ratio ◽  
Dimensional Case ◽  
Performance Bound ◽  
Worst Case ◽  
Packing Problems ◽  
The One

We investigate the two and three dimensional bin packing problems, i.e., packing a list of rectangles (boxes) into unit square (cube) bins so that the number of bins used is a minimum. A simple on-line packing algorithm for the one dimensional bin packing problem, the First-Fit algorithm, is generalized to two and three dimensions. We first give an algorithm for the two dimensional case and show that its asymptotic worse case performance ratio is [Formula: see text]. The algorithm is then generalized to the three dimensional case and its performance ratio [Formula: see text]. The second algorithm takes a parameter and we prove that by choosing the parameter properly, it has an asymptotic worst case performance bound which can be made as close as desired to 1.72=2.89 and 1.73=4.913 respectively in two and three dimensions.

Effective Data Structure for the Multidimensional Orthogonal Bin Packing Problems

2014 ◽  
Vol 962-965 ◽  
pp. 2868-2871 ◽  
Author(s):  
Alexander V. Chekanin ◽  
Vladislav A. Chekanin
Keyword(s):  
Data Structure ◽  
Linked Data ◽  
Bin Packing ◽  
High Efficiency ◽  
Optimization Problems ◽  
Packing Problem ◽  
Strong Sense ◽  
Np Hard ◽  
Packing Problems ◽  
Orthogonal Packing Problem

The actual in industry multidimensional orthogonal packing problem is considered in the article. Solution of a large number of different practical optimization problems, including resources saving problem, optimization problems in logistics, scheduling and planning comes down to the orthogonal packing problem which is NP-hard in strong sense. One of the indicators characterizing the efficiency of packing constructing algorithm is the efficiency of the used data structure. In the article a multilevel linked data structure that increases the speed of constructing of a packing is proposed. The carried out computational experiments show the high efficiency of the new data structure. Multilevel linked data structure is applicable for multidimensional orthogonal bin packing problems any kind.

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