ABSTRACT
Few problems compete with the bin packing problem in having fascinated so many people for so long a time. Research into the classical bin packing problem dates back over four decades to the early seventies. In the original version, a list L = ( a 1 , a 2 , … , a n ) https://s3-euw1-ap-pe-df-pch-content-public-u.s3.eu-west-1.amazonaws.com/9781351236423/7ef10423-eda9-42b3-a9ea-761fc7500b5b/content/equ_14756.tif"/> of n https://s3-euw1-ap-pe-df-pch-content-public-u.s3.eu-west-1.amazonaws.com/9781351236423/7ef10423-eda9-42b3-a9ea-761fc7500b5b/content/equ_14757.tif"/> items, each with a size no larger than 1, is given along with an infinite supply of unit capacity bins. The goal is to pack the list into as few bins as possible so that no bin capacity is exceeded. Because the problem is NP-hard, most research has concentrated on designing fast approximation algorithms with good performance guarantees. The studies have spanned both online and offline algorithms, and have applied both combinatorial and probabilistic analysis.
