An integrated approach to the one-dimensional cutting stock problem in coronary stent manufacturing

This paper presents a two-stage approach for pattern generation and cutting plan determination of the one-dimensional cutting stock problem. Calculation of the total number of patterns that will be cut and generation of the cutting patterns are performed in the first stage. On the other hand, the second stage determines the cutting plan. The proposed approach makes use of two separate integer linear programming models. One of these models is employed by the first stage to generate the cutting patterns through a heuristic procedure with the objective of minimizing trim loss. The cutting patterns obtained from Stage 1 are then fed into the second stage. In this stage, another integer linear programming model is solved to form a cutting plan. The objective of this model is to minimize a generalized total cost function consisting of material inputs, number of setups, labor hours and overdue time; subject to demand requirements, material availability, regular and overtime availability, and due date constraints. The study also demonstrates an implementation of the proposed approach in a coronary stent manufacturer. The case study focuses on the cutting phase of the manufacturing process followed by manual cleaning and quality control activities. The experiments show that the proposed approach is suitable to the conditions and requirements of the company.     

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。     

Solution approaches for the soft drink integrated production lot sizing and scheduling problem

In this paper we present a mixed integer programming model that integrates production lot sizing and scheduling decisions of beverage plants with sequence-dependent setup costs and times. The model considers that the industrial process produces soft drink bottles in different flavours and sizes, and it is carried out in two production stages: liquid preparation (stage I) and bottling (stage II). The model also takes into account that the production bottleneck may alternate between stages I and II, and a synchronisation of the production between these stages is required. A relaxation approach and several strategies of the relax-and-fix heuristic are proposed to solve the model. Computational tests with instances generated based on real data from a Brazilian soft drink plant are also presented. The results show that the solution approaches are capable of producing better solutions than those used by the company.     

Heuristics approach to printed circuit board insertion problem

This paper studies the operation of a surface mount technology (SMT) machine which basically consists of three main movable parts: an X–Y table containing a printed circuit board (PCB), ten rotating ‘pick-and-place’ heads and a carriage feeder of reels. The machine inserts electronic components into defined positions on a PCB and the components are supplied from a set of reels each containing a tape of identical components. In the current production setup, the assembly plan comprising both the insertion sequence of components and the placement orders of the reels in the feeder is by human experience. Our study suggests that the problem is computationally difficult for its mathematical optimum with the insertion problem alone being NP-complete. We propose a heuristic solution technique of low computational complexity to find a better assembly plan comprising of the assembly sequence of electronic components and the placement order of the reels in the feeder. The algorithm developed combines the physical constraints of the SMT machine and a ‘grouping’ concept that takes advantage of the natural structure of a PCB. Using multiple reels in the PCB insertion problem are also considered. Simulated results are reported on a set of illustrative data.     

Scheduling and lot sizing models for the single-vendor multi-buyer problem under consignment stock partnership

We consider a centralized supply chain composed of a single vendor serving multiple buyers and operating under consignment stock arrangement. Solving the general problem is hard as it requires finding optimal delivery schedule to the buyers and optimal production lot sizes. We first provide a nonlinear mixed integer programming formulation for the general scheduling and lot sizing problem. We show that the problem is NP-hard in general. We reformulate the problem under the assumption of ‘zero-switch rule’. We also provide a simple sequence independent lower bound to the solution of the general model. We then propose a heuristic procedure to generate a near-optimal delivery schedule. We assess the cost performance of that heuristic by conducting sensitivity analysis on the key model parameters. The results show that the proposed heuristic promises substantial supply-chain cost savings that increase as the number of buyers increases.     

Optimal number and location of storage hubs and biogas production reactors in farmlands with allocation of multiple feedstocks

This paper focuses on the problem for designing a logistics system for bio-methane gas (BMG) production. In practice, farm residues such as crop residue, wood residue, and livestock manure are used in reactors as reactants to generate BMG. A multi-residue, multi-hub, multi-reactor location-allocation model is developed to design the logistics of BMG production system. Both the hubs’ and reactors’ locations, and the residue's distribution plan are investigated to minimize the total construction and logistical cost. The costs of construction, transportation, feedstocks and labor are taken into consideration to reflect the lifecycle cost of the entire undertaking. In this paper, a mixed-integer nonlinear problem is proposed to simulate a BMG production supply chain. In addition to the optimal solution methods, a search-based heuristic was also proposed to determine the locations of hubs and reactors for large instances and along with a proper allocation of residues that are transported from the farms to the hubs to the reactors. Several numerical examples are tested to evaluate the performance of the heuristic as well.     

A useful transform of standard input data for a classical NP-complete problem

The archetypal symmetric travelling salesman problem can be seen in a new and interesting way, by using first a standard preparatory phase of input data, and then by applying a transform from the set D of ‘distances’ among ‘cities’ and the set B of ‘loss of optimality’.The specific form of D→B transform is introduced and discussed. In order to show in realistic terms the interest of the approach proposed, a class of ‘diffusive’ heuristic procedures operating from B is defined.An example of solution by an algorithm included in this class is completely worked out; an outline of computational tests done on the same algorithm is also given.     

A disruption recovery model for a single stage production-inventory system

This paper presents a newly developed disruption recovery model for a single stage production and inventory system, where the production is disrupted for a given period of time during the production up time. The model is categorized as a constrained non-linear optimization program which we have solved using an efficient heuristic developed in this paper. The model was also solved using an evolutionary algorithm and a comparison of the results from both methods was performed. The heuristic was able to accurately solve the model with significantly less time compared to the evolutionary algorithm. It can be shown that the optimal recovery schedule is dependent on the shortage cost parameters, as well as the extent of the disruption. The proposed model offers a potentially useful tool to help manufacturers decide on the optimal recovery plan in real time whenever the production system experiences a sudden disruption.     

Joint rolling-horizon scheduling of materials processing and lot-sizing with sequence-dependent setups

A lot sizing and scheduling problem from a foundry is considered in which key materials are produced and then transformed into many products on a single machine. A mixed integer programming (MIP) model is developed, taking into account sequence-dependent setup costs and times, and then adapted for rolling horizon use. A relax-and-fix (RF) solution heuristic is proposed and computationally tested against a high-performance MIP solver. Three variants of local search are also developed to improve the RF method and tested. Finally the solutions are compared with those currently practiced at the foundry.     

Machine duplication and part subcontracting in the presence of alternative cell locations in manufacturing cell design

In this paper a model and a solution algorithm are reported to simultaneously deal with the processes of machine duplication and part subcontracting in the presence of two significant design issues in cellular manufacturing systems: (i) alternative cell locations; and (ii) the maximum number of machines assigned to a cell. As the problem, formulated as a polynomial programming model, is shown NP-hard in the strong sense, a higher-level heuristic algorithm based upon a concept known as ‘tabu search’ is presented. An example (small) problem is solved to demonstrate the functionality of the algorithm. Additionally, the small problem is solved for its optimal solution under different scenarios, both with linear single-row and linear double-row layout arrangements, and the solutions obtained are shown to match with those obtained with the heuristic algorithm. A comparison of six different versions of tabu search-based heuristics (TSH 1–TSH 6) is performed to investigate the impact of long-term memory and the use of fixed versus variable tabu-list sizes. A carefully constructed statistical experiment, based on randomised complete-block design, is used to test the performance on three different problem structures, classified as small, medium and large. The results show that TSH 6 with variable tabu-list size and long-term memory based on minimal frequencies is preferred for the single-row layout, while TSH 4 with variable tabu-list size and no long-term memory is preferred for the double-row layout. When subject to budgetary restrictions, the proposed approach can be used by parts manufacturing companies to determine which of the following three actions should be undertaken for each bottleneck part: bottleneck part left as in the initial solution, all the bottleneck machines connected to it are duplicated, or the part subcontracted.     

One-dimensional heuristics adapted for two-dimensional rectangular strip packing

We consider two-dimensional rectangular strip packing without rotation of items and without the guillotine cutting constraint. We propose two iterative heuristics. The first one, SVC(SubKP), is based on a single-pass heuristic SubKP which fills every most bottom-left free space in a one-dimensional knapsack fashion, that is, considering only item widths. It appears especially important to assign suitable ‘pseudo-profits’ in this knapsack problem. The second heuristic BS(BLR) is based on the known randomized framework Bubble-Search. It generates different item sequences and runs a new sequence-based heuristic Bottom-Left-Right (BLR), a simple modification of the Bottom-Left heuristic. We investigate the solution sets of SubKP and BLR and their relation to each other. In the tests, SVC(SubKP) improves the results for larger instances of the waste-free classes of Hopper and Turton and, on average, for the tested non-waste-free classes, compared to the latest literature. BS(BLR) gives the best results in some classes with smaller number of items (20,40).     

Optimal and heuristic algorithms for multiproduct uncapacitated facility location

We consider a generalization of the classic uncapacitated facility location problem (UFLP) in which customers require multiple products. We call this the multiproduct uncapacitated facility location problem (MUFLP). In MUFLP, in addition to a fixed cost for opening a facility, a fixed cost is incurred for each product that a facility is equipped to handle. Also, an assignment cost is incurred for satisfying a customer's requirement for a particular product at a chosen facility. We describe a branch-and-bound algorithm for MUFLP. Lower bounds are obtained by solving a UFLP subproblem for each product using a dual ascent routine. We also describe a heuristic branch-and-bound procedure in which the solutions to the subproblems at a given node might not generate a true lower bound. To generate a feasible solution, a ‘superposition’ heuristic based on solving UFLP subproblems for each product, as well as a ‘drop’ heuristic that eliminates facilities and equipment from the solution in a step-by-step manner, are given. Computational results are reported.     

Heuristic for constrained two-dimensional three-staged patterns

Three-staged cutting patterns are often used in dividing large plates into small rectangular items. Vertical cuts separate the plate into segments in the first stage, horizontal cuts split each segment into strips in the second stage, and vertical cuts divide each strip into items in the third stage. A heuristic algorithm for generating constrained three-staged patterns is presented in this paper. The optimization objective is to maximize the pattern value that is the total value of the included items, while the frequency of each item type should not exceed the specified upper bound. The algorithm uses an exact procedure to generate strips and two heuristic procedures to generate segments and the pattern. The pattern-generation procedure first determines an initial solution and then uses its information to generate more segments to extend the solution space. Computational results show that the algorithm is effective in improving solution quality.     

Scheduling a hybrid assembly-differentiation flowshop to minimize total flow time

This study considers a hybrid assembly-differentiation flowshop scheduling problem (HADFSP), in which there are three production stages, including components manufacturing, assembly, and differentiation. All the components of a job are processed on different machines at the first stage. Subsequently, they are assembled together on a common single machine at the second stage. At the third stage, each job of a particular type is processed on a dedicated machine. The objective is to find a job schedule to minimize total flow time (TFT). At first, a mixed integer programming (MIP) model is formulated and then some properties of the optimal solution are presented. Since the NP-hardness of the problem, two fast heuristics (SPT-based heuristic and NEH-based heuristic) and three hybrid meta-heuristics (HGA-VNS, HDDE-VNS and HEDA-VNS) are developed for solving medium- and large-size problems. In order to evaluate the performances of the proposed algorithms, a lower bound for the HADFSP with TFT criteria (HADFSP-TFT) is established. The MIP model and the proposed algorithms are compared on randomly generated problems. Computational results show the effectiveness of the MIP model and the proposed algorithms. The computational analysis indicates that, in average, the HDDE-VNS performs better and more robustly than the other two meta-heuristics, whereas the NEH heuristic consume little time and could reach reasonable solutions.     

Single-job lot streaming in m − 1 two-stage hybrid flowshops

This paper studies the single-job lot streaming problem in a two-stage hybrid flowshop that has m identical machines at the first stage and one machine at the second stage, to minimise the makespan. A setup time is considered before processing each sublot on a machine. For the problem with the number of sublots given, we prove that it is optimal to use a rotation method for allocating and sequencing the sublots on the machines. With such allocation and sequencing, the sublot sizes are then optimised using linear programming. We then consider the problem with equal sublot sizes and develop an efficient solution to determining the optimal number of sublots. Finally optimal and heuristic solution methods for the general problem are proposed and the worst-case performance of the equal-sublot solution is analysed. Computational results are also reported demonstrating the close-to-optimal performances of the heuristic methods in different problem settings.     

Multi-Skilled Workforce Optimisation

This paper describes a problem faced by CS Energy's Swanbank Power Station in the Australian state of Queensland. It involved the personnel scheduling (rostering) of staff with multiple skill levels at the power station. Such a problem can be classified using the six stage construction process proposed by Ernst et al. We assume that the three processes of ‘demand modelling,’ ‘shift starting times’ and ‘task scheduling’ are specified. We are concerned with the essential processes of ‘day off scheduling,’ ‘line of work construction’ and ‘shift assignment to staff’ with requirements to maintain multiple skills. Several other authors have reported results for staff with hierarchical skills while the methods proposed in this paper are for non-hierarchical skill sets. The paper describes a set covering approach to the multi-skilled rostering problem. We propose a number of solution strategies for the set covering approach and give a comparison of the results.     

A penalty-shift-insertion-based algorithm to minimize total flow time in no-wait flow shops

This paper proposes a penalty-shift-insertion (PSI)-based algorithm for the no-wait flow shop scheduling problem to minimize total flow time. In the first phase, a penalty-based heuristic, derived from Vogel’s approximation method used for the classic transportation problem is used to generate an initial schedule. In the second phase, a known solution is improved using a forward shift heuristic. Then the third phase improves this solution using a job-pair and a single-job insertion heuristic. Results of the computational experiments with a large number of randomly generated problem instances show that the proposed PSI algorithm is relatively more effective and efficient in minimizing total flow time in a no-wait flow shop than the state-of-the-art procedures. Statistical significance of better results obtained by the proposed algorithm is also reported.     

Deterministic/stochastic assumptions in job shops

The study investigates the effects which possibly unrealistic assumptions of accurately predicting operation times may have on relative performance of various job shop dispatching rules as compared with using an assumption of not being able to accurately predetermine such times. The experimental design includes factors dealing with the amount of accuracy in the estimated operation times, job dispatching heuristic rules, and shop loading categories. The stochastic operation times represent two different degrees of inaccuracy; one level reflects an estimated ‘normal’ amount of inaccuracy associated with an experienced predictor (shop foreman) while the other level doubles the amount of variance associated with the ‘normal’ predictor's error. These two stochastic levels are compared to a deterministic level where predetermined operation times are absolutely accurate. Five different heuristic rules are evaluated under six different shop loading levels. General conclusions indicate that an assumption of accurately predetermining actual operation times is not likely to weaken the analysis and impact of the research studies which have been performed using such an assumption. However, a specific conclusion indicates that, for at least one shop loading category, researchers should be careful when extending conclusions based on one operation time assumption to situations involving the other assumption.     

Planning and consolidating shipments from a warehouse

A typical warehouse or distribution centre ships material to various customer locations across the country, using various modes of transportation. Each mode has different constraints on size of shipment, different cost structures and different transportation times. Typically, for a given warehouse there are certain customer locations that receive frequent shipments of material. It is often possible, therefore, for the warehouse to consolidate different orders for the same customer location into a single shipment. The transportation mode and the day of shipment must be chosen such that the consolidated shipment meets the size constraints and arrives within an agreed-upon ‘delivery window’. In preparing a warehouse distribution plan, a planner seeks to achieve transportation economies of scale (by consolidating two or more orders into fewer shipments) while levelling the workload on warehouse resources and ensuring that material arrives at a customer location during the acceptable delivery window.The problem of deciding what shipments to make daily can be formulated as a set partitioning problem with side constraints. This paper describes a heuristic solution approach for this problem. Computational experiments using actual warehouse select activity indicate that, for moderate-size problems, the heuristic produces solutions with transportation costs that are within a few percent of optimal. Larger problems found in practice are generally too large to be solved by optimal algorithms; the heuristic easily handles such problems. The heuristic has been integrated into the transportation planning system of a leading distributor of telecommunications products.     

A Greedy Look-ahead Heuristic for Combinatorial Optimization: An Application to Vehicle Scheduling with Time Windows

This paper describes a greedy heuristic for a class of combinatorial optimization problems; a central feature of the method being a look-ahead capability. The power of the heuristic is demonstrated through experimentation using a large, real-life vehicle scheduling problem with tight time-window constraints. Incorporation of the look-ahead feature gave an improvement in performance that was at least as great as, and in addition to, that which had been obtained through use of the well-known ‘savings’ method. Based upon the experimental results, some guidelines are proposed for the application of the heuristic to other problems. One of the conclusions is that designers of heuristics should give greater consideration to the inclusion of a look-ahead element in their algorithms.