The one-dimensional cutting stock problem with usable leftover – A heuristic approach

In this work we consider a one-dimensional cutting stock problem in which the non-used material in the cutting patterns may be used in the future, if large enough. This feature introduces difficulties in comparing solutions of the cutting problem, for example, up to what extent a minimum leftover solution is the most interesting one when the leftover may be used. Some desirable characteristics of good solutions are defined and classical heuristic methods are modified, so that cutting patterns with undesirable leftover (not large enough to be used, nor too small to be acceptable waste) are redesigned. The performance of the modified heuristics is observed by solving instances from the literature, practical instances and randomly generated instances.     

Reducing the number of cuts in generating three-staged cutting patterns

Three-staged guillotine patterns are widely used in the manufacturing industry to cut stock plates into rectangular items. The cutting cost often increases with the number of cuts required. This paper focuses on the rectangular two-dimensional cutting stock problem, where three-staged guillotine patterns are used, and the objective is to minimize the sum of plate and cutting costs. The column generation framework is used to solve the problem. It uses a pattern-generation procedure to obtain the patterns. The cutting cost is considered in both the pattern-generation procedure and the objective of the linear programming formulation. The computational results indicate that the approach can reduce the number of cuts, without increasing the plate cost.     

Large gaps in one-dimensional cutting stock problems

Its linear relaxation is often solved instead of the one-dimensional cutting stock problem (1CSP). This causes a difference between the optimal objective function values of the original problem and its relaxation, called a gap. The size of this gap is considered in this paper with the aim to formulate principles for the construction of instances of the 1CSP with large gaps. These principles are complemented by examples for such instances.     

Fixed charge problems with identical fixed charges

The general problem considered by this paper is a special case of the fixed-charge problem. The further condition imposed is that all variables have the same associated fixed-charge. The problem is discussed in the context of a known commercial application, that being the cutting stock problem. The situation considered is that of cutting given numbers of small rectangles from large rectangular stock-plates. In many such situations major aims are to have low stock-plate usage and a low number of setups of the cutting equipment. These represent conflicting objectives capable of being combined by the use of fixed charges upon the setups but this paper presents an alternative approach incorporating direct manipulation of the number of setups involved in the solution. This approach is compared to a solution technique for the general fixed-charge problem.     

Cutting plane method for multiple objective stochastic integer linear programming

This paper grapples with the problem of incorporating integer variables in the constraints of a multiple objective stochastic linear program (MOSLP). After representing uncertain aspirations of the decision maker by converting the original problem into a deterministic multiple objective integer linear program (MOILP), a cutting plane technique may be used to compute all the efficient solutions of the last model leaving the decision maker to choose a solution according to his preferences. A numerical example is also included for illustration.     

ACCPM with a nonlinear constraint and an active set strategy to solve nonlinear multicommodity flow problems

This paper proposes an implementation of a constrained analytic center cutting plane method to solve nonlinear multicommodity flow problems. The new approach exploits the property that the objective of the Lagrangian dual problem has a smooth component with second order derivatives readily available in closed form. The cutting planes issued from the nonsmooth component and the epigraph set of the smooth component form a localization set that is endowed with a self-concordant augmented barrier. Our implementation uses an approximate analytic center associated with that barrier to query the oracle of the nonsmooth component. The paper also proposes an approximation scheme for the original objective. An active set strategy can be applied to the transformed problem: it reduces the dimension of the dual space and accelerates computations. The new approach solves huge instances with high accuracy. The method is compared to alternative approaches proposed in the literature. An erratum to this article can be found at     

Secondary log breakdown optimization with dynamic programming

Log breakdown can be viewed as a two-stage process with logs sawn into slabs of wood known as flitches during the primary stage and flitches further processed during the secondary stage to produce edged (cut lengthwise) and trimmed (cut widthwise) pieces. This paper addresses the secondary problem and describes some procedures for determining the optimal cutting of flitches into graded dimensional boards. The problem is formulated as a set packing problem with the objective being to maximise total value. Extensions to the basic formulation include constraints which restrict the number of saws and which disallow waste between adjacent edged pieces. The problem is solved using dynamic programming techniques and the algorithms incorporated into a sawing simulation system. Comparisons with existing edging and trimming procedures show that substantial reductions in solution time (to as little as 1/25th of the time required for an enumerative search) can be achieved.     

有交货时间限制的大规模实用下料问题

研究的是有交货时间限制的单一原材料下料问题(规模较大).对于一维下料问题,本文得到一个有各自交货时间的模型.针对该模型提出一种新的算法:DP贪婪算法.计算结果是总用料800根即可完成需求任务,材料利用率为99.6%.对于二维下料问题,在一维的基础上建立了二维的求解模型,运用我们自己设计的降维思想结合一维的DP贪婪算法,给出解决该模型的算法.计算结果是总用料451块即可完成需求任务,材料利用率位99.2%.算法设计时考虑了普遍的情况,所以算法在解决大多数实际下料问题,特别是大规模下料问题时是切实有效的.     

Heuristic for the rectangular two-dimensional single stock size cutting stock problem with two-staged patterns

Two-staged patterns are often used in manufacturing industries to divide stock plates into rectangular items. A heuristic algorithm is presented to solve the rectangular two-dimensional single stock size cutting stock problem with two-staged patterns. It uses the column-generation method to solve the residual problems repeatedly, until the demands of all items are satisfied. Each pattern is generated using a procedure for the constrained single large object placement problem to guarantee the convergence of the algorithm. The computational results of benchmark and practical instances indicate the following: (1) the algorithm can solve most instances to optimality, with the gap to optimality being at most one plate for those solutions whose optimality is not proven and (2) for the instances tested, the algorithm is more efficient (on average) in reducing the number of plates used than a published algorithm and a commercial stock cutting software package.     

Set covering and packing formulations of graph coloring: Algorithms and first polyhedral results

We consider two (0, 1)-linear programming formulations of the graph (vertex-) coloring problem, in which variables are associated with stable sets of the input graph. The first one is a set covering formulation, where the set of vertices has to be covered by a minimum number of stable sets. The second is a set packing formulation, in which constraints express that two stable sets cannot have a common vertex, and large stable sets are preferred in the objective function. We identify facets with small coefficients for the polytopes associated with both formulations. We show by computational experiments that both formulations are about equally efficient when used in a branch-and-price algorithm. Next we propose some preprocessing, and show that it can substantially speed up the algorithm, if it is applied at each node of the enumeration tree. Finally we describe a cutting plane procedure for the set covering formulation, which often reduces the size of the enumeration tree.     

MIP models for two-dimensional non-guillotine cutting problems with usable leftovers

In this study we deal with the two-dimensional non-guillotine cutting problem of how to cut a set of larger rectangular objects to a set of smaller rectangular items in exactly a demanded number of pieces. We are concerned with the special case of the problem in which the non-used material of the cutting patterns (objects leftovers) may be used in the future, for example if it is large enough to fulfill future item demands. Therefore, the problem is seen as a two-dimensional non-guillotine cutting/packing problem with usable leftovers, also known in the literature as a two-dimensional residual bin-packing problem. We use multilevel mathematical programming models to represent the problem appropriately, which basically consists of cutting the ordered items using a set of objects of minimum cost, among all possible solutions of minimum cost, choosing one that maximizes the value of the usable leftovers, and, among them, selecting one that minimizes the number of usable leftovers. Because of special characteristics of these multilevel models, they can be reformulated as one-level mixed integer programming (MIP) models. Illustrative numerical examples are presented and analysed.     

考虑生产计划的多周期切割问题优化研究

切割生产广泛存在于工业企业,是原材料加工的重要环节。已有文献主要关注单周期切割问题,但是切割计划也是生产计划的一部分,切割计划和生产计划应该协调优化,达到全局最优。本文研究考虑生产计划的多周期切割问题,目标是最小化运营成本,包括准备成本、切割成本、库存成本以及母材消耗成本。首先建立混合整数规划模型;提出动态规划启发式算法;最后对算例在多种情境下测试,分析成本因子变化对最优结果的影响。算法结果与CPLEX最优结果比较,平均误差为1.85%,表明算法是有效的。     

Algorithms for Unconstrained Two-Dimensional Guillotine Cutting

In this paper we consider the unconstrained, two-dimensional, guillotine cutting problem. This is the problem that occurs in the cutting of a number of rectangular pieces from a single large rectangle, so as to maximize the value of the pieces cut, where any cuts that are made are restricted to be guillotine cuts.We consider both the staged version of the problem (where the cutting is performed in a number of distinct stages) and the general (non-staged) version of the problem.A number of algorithms, both heuristic and optimal, based upon dynamic programming are presented. Computational results are given for large problems.     

Method for optimum cutting of rectangular sheets

This paper describes a method to divide a large rectangle into smaller ones of given size which gives minimum wastage if one is restricted to a certain class of technologically convenient cutting procedures. The method should be useful for obtaining cutting procedures for sheet metal, presspan, mica, etc.     

A Cutting Stock and Scheduling Problem in the Copper Industry

This case study was carried out for Thomas Bolton Ltd, a copper component manufacturer. The focus was on the first major production operation that is carried out in the foundry. This operation consists of three processes — melting scrap metal, casting it as ‘logs’ and cutting logs into ‘billets’. The timely production of the billets is essential as these feed a bottleneck process. The objective of the study was to investigate alternative methods of generating a production plan for the foundry that minimized costs whilst meeting the demand for billets at the bottleneck. The production plan was required to include a daily production schedule and a list of the cutting patterns to use when cutting the logs into billets. Thus, both the scheduling and cutting stock problems were addressed. A two-stage solution procedure was proposed. Alternative heuristic methods were investigated at the first stage and an optimal solution using Integer Programming (IP) was proposed for the second stage. It is shown that current performance could be improved using all of the heuristics considered at the first stage, but that using an IP-based heuristic method gives the best results.     

A Decomposition Method for Transfer Line Life Cycle Cost Optimisation

A new method to search best parameters of a transfer line so that the cost of each manufactured part will be minimised. The synchronised transfer lines with parallel machining are considered. Such lines are widely used in mass and large-scale mechanical production. The objective is to minimise the line life cycle cost per part under the given productivity and technological constraints. The design decisions to be optimised are: number of spindles and workstations. This will be accomplished by defining subsets of tasks which are performed by one spindle head and cutting conditions for each spindle. The paper focuses on a mathematical model of the problem and methods used to solve it. This model is formulated in terms of mixed (discrete and non-linear) programming and graph theory. A special decomposition scheme based on the parametric decomposition technique is proposed. For solving the sub-problems obtained after decomposition, a Branch-and-Bound algorithm as well as a shortest path technique are used.     

On the convergence of a class of outer approximation algorithms for convex programs

This paper presents a new class of outer approximation methods for solving general convex programs. The methods solve at each iteration a subproblem whose constraints contain the feasible set of the original problem. Moreover, the methods employ quadratic objective functions in the subproblems by adding a simple quadratic term to the objective function of the original problem, while other outer approximation methods usually use the original objective function itself throughout the iterations. By this modification, convergence of the methods can be proved under mild conditions. Furthermore, it is shown that generalized versions of the cut construction schemes in Kelley-Cheney-Goldstein's cutting plane method and Veinott's supporting hyperplane method can be incorporated with the present methods and a cut generated at each iteration need not be retained in the succeeding iterations.     

A Partitioned Cutting-stock Problem Applied in the Meat Industry

The paper reports on a linear programming application in the meat industry. The problem is formulated as a variant of the cutting-stock or trim problem, where the objective is to maximize the return from selling products yielded from cutting patterns applied to animal carcasses. One feature of the formulation is the partitioning of cutting patterns among carcass sections. Since the sections are relatively independent, this partitioning vastly reduces the number of cutting patterns in the formulation. Implementation is on a personal computer, and the system is used by a meat company for market planning. The system uses a commercial database to handle data entry and solution reporting, and has been found to be extremely user-friendly.     

The cutting stock problem for large sections in the iron and steel industries

The characteristics of a cutting stock problem for large sections in the iron and steel industries are as follows:(1) There is a variety of criterions such as maximizing yield and increasing effeciency of production lines. (2) A cutting stock problem is accompanied by an optimal stock selection problem. A two-phase algorithm is developed, using an heuristic method. This algorithm gives nearly optimal solutions in real time. It is applied to both batch-solving and on-line solving of one-dimensional cutting of large section. The new algorithm has played an important role in a large-section production system to increase the yield by approximately 2.5%.     

A cutting plane method for bilevel linear programming with interval coefficients

This article considers the bilevel linear programming problem with interval coefficients in both objective functions. We propose a cutting plane method to solve such a problem. In order to obtain the best and worst optimal solutions, two types of cutting plane methods are developed based on the fact that the best and worst optimal solutions of this kind of problem occur at extreme points of its constraint region. The main idea of the proposed methods is to solve a sequence of linear programming problems with cutting planes that are successively introduced until the best and worst optimal solutions are found. Finally, we extend the two algorithms proposed to compute the best and worst optimal solutions of the general bilevel linear programming problem with interval coefficients in the objective functions as well as in the constraints.