Minimal proper non-IRUP instances of the one-dimensional cutting stock problem

نویسندگان

  • Vadim M. Kartak
  • Artem V. Ripatti
  • Guntram Scheithauer
  • Sascha Kurz
چکیده

We consider the well-known one-dimensional cutting stock problem (1CSP). It is shown that all possible instances of the 1CSP can be divided into a finite number of equivalence classes when the number of items m is fixed. A method for enumerating all these classes is investigated. This method is improved for searching proper non-IRUP instances with minimal number of items. We found the minimal number of items is m = 10 when a proper non-IRUP instance exists. We also found 365 equivalence classes that consist of such instances. keyword Cutting Stock Problem, Integer Round-up Property, Equivalence of instances, Branch and Bound Method, Linear Programming

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Families of Non-irup Instances of the One-dimensional Cutting Stock Problem Families of Non-irup Instances of the One-dimensional Cutting Stock Problem

In case of the one-dimensional cutting stock problem (CSP) one can observe for any instance a very small gap between the integer optimal value and the continuous relaxation bound. These observations have initiated a series of investigations. An instance possesses the integer roundup property (IRUP) if its gap is smaller than 1. It is well-known that there exist instances of the CSP having a gap...

متن کامل

Iterated Local Search Algorithm for the Constrained Two-Dimensional Non-Guillotine Cutting Problem

An Iterated Local Search method for the constrained two-dimensional non-guillotine cutting problem is presented. This problem consists in cutting pieces from a large stock rectangle to maximize the total value of pieces cut. In this problem, we take into account restrictions on the number of pieces of each size required to be cut. It can be classified as 2D-SLOPP (two dimensional single large o...

متن کامل

Solving an one-dimensional cutting stock problem by simulated annealing and tabu search

A cutting stock problem is one of the main and classical problems in operations research that is modeled as Lp < /div> problem. Because of its NP-hard nature, finding an optimal solution in reasonable time is extremely difficult and at least non-economical. In this paper, two meta-heuristic algorithms, namely simulated annealing (SA) and tabu search (TS), are proposed and deve...

متن کامل

An ACO algorithm for one-dimensional cutting stock problem

The one-dimensional cutting stock problem, has so many applications in lots of industrial processes and during the past few years has attracted so many researchers’ attention all over the world. In this paper a meta-heuristic method based on ACO is presented to solve this problem. In this algorithm, based on designed probabilistic laws, artificial ants do select various cuts and then select the...

متن کامل

The trim loss concentration in one-dimensional cutting stock problem (1D-CSP) by defining a virtual cost

Nowadays, One-Dimensional Cutting Stock Problem (1D-CSP) is used in many industrial processes and re-cently has been considered as one of the most important research topic. In this paper, a metaheuristic algo-rithm based on the Simulated Annealing (SA) method is represented to minimize the trim loss and also to fo-cus the trim loss on the minimum number of large objects. In this method, the 1D-...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:
  • Discrete Applied Mathematics

دوره 187  شماره 

صفحات  -

تاریخ انتشار 2015