A note on dual approximation algorithms for class constrained bin packing problems

Computational results on a large testbed of instances from the literature suggest that solving a lexicographic pricer is indeed advantageous, and that the adoption of the weight

In Section 4 we choose one such finite plan π 0 which need not be an optimal plan and prove a dual attainment result for a modified Monge–Kantorovich problem which is restricted to

A solution of the problem consists in assigning each item i to a bin and defining its position, denoted by ( x i , y i ) which corresponds to the coordinates of its bottom

Given an instance I of GEOSP (GEOSC) let OP T pack (I ) ( OP T cover (I)) denote the value of the optimal solution of the corresponding problem instance.. Also, let v LP be equal to

Using the "equally likely signature model" of Balinski [4] which supposes that at every pivot step, each possible succeeding column signature is equally likely, i.e.,

Our signature method is a variant of Balinski's [3] compétitive (dual) simplex algorithm. It constructs rooted trees that have precisely the same primai structure as Balinski's

The experimental results were later presented by showing the influence of the number of containers in a chromosome and the influence of the number of

We first prove that the minimum and maximum traveling salesman prob- lems, their metric versions as well as some versions defined on parameterized triangle inequalities