The two-dimensional vector packing problem with general costs

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

5 Scopus Citations
View graph of relations

Author(s)

  • Qian Hu
  • Lijun Wei
  • Andrew Lim

Related Research Unit(s)

Detail(s)

Original languageEnglish
Pages (from-to)59-69
Journal / PublicationOmega (United Kingdom)
Volume74
Online published24 Jan 2017
Publication statusPublished - Jan 2018

Abstract

The two-dimensional vector packing problem with general costs (2DVPP-GC) arises in logistics where shipping items of different weight and volume are packed into cartons before being transported by a courier company. In practice, the delivery cost of a carton of items is usually retrieved from a cost table. The costs may not preserve any known mathematical function since it could specify arbitrary price at any possible weight. Such a general pricing scheme meets a majority of real-world bin packing applications, where the price of delivery service is determined by many complicated and correlated factors. Compared to the classical bin packing problem and its variants, the 2DVPP-GC is more complex and challenging. To solve the 2DVPP-GC with minimizing the total cost, we propose a memetic algorithm to compute solutions of high quality. Fitness functions and improved operators are proposed to achieve effectiveness. Computational experiments on a variety of test instances show that the algorithm is competent to solve the 2DVPP-GC. In particular, optimal solutions are found in a second for all the test instances that have a known optimal solution.

Research Area(s)

  • Application, Bin packing, General costs, Memetic algorithm, Two-dimensional vector packing

Citation Format(s)

The two-dimensional vector packing problem with general costs. / Hu, Qian; Wei, Lijun; Lim, Andrew.

In: Omega (United Kingdom), Vol. 74, 01.2018, p. 59-69.

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review