The wafer probing scheduling problem (WPSP)

The wafer probing scheduling problem (WPSP) is a variation of the parallel-machine scheduling problem, which has many real-world applications, particularly, in the integrated circuit (IC) manufacturing industry. In the wafer probing factories, the jobs are clustered by their product types, which must be processed on groups of identical parallel machines and be completed before the due dates. Further, the job processing time depends on the product type, and the machine setup time is sequence dependent on the orders of jobs processed. Since the wafer probing scheduling problem involves constraints on job clusters, job-cluster dependent processing time, due dates, machine capacity, and sequence dependent setup time, it is more difficult to solve than the classical parallel-machine scheduling problem. In this paper, we formulate the WPSP as an integer programming problem. We also transform the WPSP into the vehicle routing problem with time windows (VRPTW), a well-known network routing problem which has been investigated extensively. An illustrative example is given to demonstrate the proposed transformation. Based on the provided transformation, we present three efficient algorithms to solve the WPSP near-optimally.     

Algorithms for the wafer probing scheduling problem with sequence-dependent set-up time and due date restrictions

In this paper, we consider the wafer probing scheduling problem (WPSP) to sequence families of jobs on identical parallel machines with due date restrictions. The machine set-up time is sequentially dependent on the product types of the jobs processed on the machine. The objective is to minimize the total machine workload without violating the machine capacity and job due date restrictions. The WPSP is a variation of the classical parallel-machine scheduling problem, that can be transformed into the vehicle-routing problem with time windows (VRPTW). One can therefore solve the WPSP efficiently using existing VRPTW algorithms. We apply four existing savings algorithms presented in the literature including sequential, parallel, generalized, and matching based savings, and develop three modifications called the modified sequential, the compound matching based, and the modified compound matching-based savings algorithms, to solve the WPSP. Based on the characteristics of the wafer probing process, a set of test problems is generated for testing purposes. Computational results show that the three proposed modified algorithms perform remarkably well.     

Bicriteria problems to minimize maximum tardiness and due date assignment cost in various scheduling environments

We study bicriteria problems of minimizing maximum tardiness and total due date assignment cost in various scheduling environments. We assume that each job can be assigned a different due date without any restriction, and that each due date assignment cost is a non-decreasing function of the quoted due date. We settle the complexity of most of the problems studied by either proving that they are NP-hard or finding a polynomial time solution for them. We also include approximation and non-approximability results for several parallel-machine problems.     

Scheduling arrivals to a production system in a fuzzy environment

A frequently encountered scheduling problem is to determine a material and job ready time while simultaneously finding a production sequence given customer-specified due dates. Often the production times and due dates are vague. This paper presents an investigation of scheduling ready times for a set of jobs with fuzzy service times and due dates. The ready time is constrained in that the possibility that a job is late must not exceed a predefined value. The objective in such an instance is to maximize the ready time without violating these constraints. The steps necessary to determine the maximum ready time and cases in which this effort may be significantly reduced are presented for single machine and flow shop production systems. Finally, a branch and bound technique is developed for cases in which the optimal job sequence cannot be determined a priori.     

Single machine scheduling and due date assignment with positionally dependent processing times

We consider single machine scheduling and due date assignment problems in which the processing time of a job depends on its position in a processing sequence. The objective functions include the cost of changing the due dates, the total cost of discarded jobs that cannot be completed by their due dates and, possibly, the total earliness of the scheduled jobs. We present polynomial-time dynamic programming algorithms in the case of two popular due date assignment methods: CON and SLK. The considered problems are related to mathematical models of cooperation between the manufacturer and the customer in supply chain scheduling.     

A branch and bound algorithm for scheduling jobs with controllable processing times on a single machine to meet due dates

In most deterministic scheduling problems, job-processing times are regarded as constant and known in advance. However, in many realistic environments, job-processing times can be controlled by the allocation of a common resource to jobs. In this paper, we consider the problem of scheduling jobs with arbitrary release dates and due dates on a single machine, where job-processing times are controllable and are modeled by a non-linear convex resource consumption function. The objective is to determine simultaneously an optimal processing permutation as well as an optimal resource allocation, such that no job is completed later than its due date, and the total resource consumption is minimized. The problem is strongly NP\mathcal{NP}-hard. A branch and bound algorithm is presented to solve the problem. The computational experiments show that the algorithm can provide optimal solution for small-sized problems, and near-optimal solution for medium-sized problems in acceptable computing time.     

Equivalent time-dependent scheduling problems

We introduce a general transformation of parallel-machine time-dependent scheduling problems with critical lines. Using the transformation we define the class of equivalent time-dependent scheduling problems. We show that given an initial parallel-machine time-dependent scheduling problem with linear job processing times and the total weighted starting time criterion, the problem can be transformed in a unique way into another problem of this type in such a way that both these problems are mutually dual. We prove that a schedule is optimal for the initial problem if and only if the schedule constructed by this transformation is optimal for the transformed problem. The presented results explain remarkable similarities between different time-dependent scheduling problems and simplify the proofs of properties of such problems.     

Isomorphic scheduling problems

We consider general properties of isomorphic scheduling problems that constitute a new class of pairs of mutually related scheduling problems. Any such a pair is composed of a scheduling problem with fixed job processing times and its time-dependent counterpart with processing times that are proportional-linear functions of the job starting times. In order to introduce the class formally, first we formulate a generic scheduling problem with fixed job processing times and define isomorphic problems by a one-to-one transformation of instances of the generic problem into instances of time-dependent scheduling problems with proportional-linear job processing times. Next, we prove basic properties of isomorphic scheduling problems and show how to convert polynomial algorithms for scheduling problems with fixed job processing times into polynomial algorithms for proportional-linear counterparts of the original problems. Finally, we show how are related approximation algorithms for isomorphic problems. Applying the results, we establish new worst-case results for time-dependent parallel-machine scheduling problems and prove that many single- and dedicated-machine time-dependent scheduling problems with proportional-linear job processing times are polynomially solvable.     

工件具有子工件工期的排序问题

研究了工件具有子工件工期的排序问题.需要在一台单机上加工若干个给定的工件.每个工件由若干个子工件组成,每个子工件都有各自的工期.只有当工件的每个子工件都按时完成,才能称该工件是按时完工工件,否则,称该工件产生延误.目标是最大化按时完工的工件个数.证明当每个工件都被分成两个子工件时,该问题是NP-难的,而且不存在完全多项式时间近似方案(fully polynomial time approximation scheme,简记为FPTAS).提出两个启发式算法,利用数值模拟比较它们的性能,并且将这两个启发式算法的解与最优解的上界进行比较.     

Parallel-machine scheduling with past-sequence-dependent delivery times and learning effect

This paper considers identical parallel-machine scheduling problem with past-sequence-dependent (psd) delivery times and learning effect. In electronic manufacturing industry, an electronic component may be exposed to certain electromagnetic field and requires an extra time for eliminating adverse effect after the main processing. The extra time is modeled as past-sequence-dependent delivery time in the literature, which is proportional to the waiting time in the system. It is also observed that the learning process reflects a decrease in the processing time as a function of the number of repetitions, i.e., as a function of the job position in the sequence. In practice, one often has to deal with the scheduling problems with psd delivery times and learning effect. Identical parallel-machine setting is considered because the occurrence of resources in parallel is common in the real world. In this paper, three objectives are the minimization of the total absolute deviation of job completion times, the total load on all machines and the total completion time. We develop polynomial algorithms to optimally solve these problems.     

Precedence constrained parallel-machine scheduling of position-dependent jobs

We consider parallel-machine job scheduling problems with precedence constraints. Job processing times are variable and depend on positions of jobs in a schedule. The objective is to minimize the maximum completion time or the total weighted completion time. We specify certain conditions under which the problem can be solved by scheduling algorithms applied earlier for fixed job processing times.     

Scheduling with batch setup times and earliness-tardiness penalties

We consider a scheduling model in which several batches of jobs need to be processed by a single machine. During processing, a setup time is incurred whenever there is a switch from processing a job in one batch to a job in another batch. All the jobs in the same batch have a common due date that is either externally given as an input data or internally determined as a decision variable. Two problems are investigated. One problem is to minimize the total earliness and tardiness penalties provided that each due date is externally given. We show that this problem is NP-hard even when there are only two batches of jobs and the two due dates are unrestrictively large. The other problem is to minimize the total earliness and tardiness penalties plus the total due date penalty provided that each due date is a decision variable. We give some optimality properties for this problem with the general case and propose a polynomial dynamic programming algorithm for solving this problem with two batches of jobs. We also consider a special case for both of the problems when the common due dates for different batches are all equal. Under this special case, we give a dynamic programming algorithm for solving the first problem with an unrestrictively large due date and for solving the second problem. This algorithm has a running time polynomial in the number of jobs but exponential in the number of batches.     

A survey of the state-of-the-art of common due date assignment and scheduling research

We aim at providing a unified framework of the common due date assignment and scheduling problems in the deterministic case by surveying the literature concerning the models involving single machine and parallel machines. The problems with due date determination have received considerable attention in the last 15 years due to the introduction of new methods of inventory management such as just-in-time (JIT) concepts. The common due date model corresponds, for instance, to an assembly system in which the components of the product should be ready at the same time, or to a shop where several jobs constitute a single customer's order. In the problems under consideration, the objective is to find an optimal value of the common due date and the related optimal schedule in order to optimize a given criterion based on the due date and the completion times of jobs. The results on the algorithms and complexity of the common due date assignment and scheduling problems are summarized.     

Strong NP-hardness of minimizing total deviation with generalized and periodic due dates

We consider a single-machine scheduling problem with generalized and periodic due dates such that each due date is assigned not to a specific job but to a position and the lengths of the intervals between consecutive due dates are identical. The objective is to minimize the total deviation, which is calculated as the sum of the earliness and tardiness of each job. We show that the problem is strongly NP-hard. We develop a heuristic and verify its performance via experiments.     

Scheduling jobs with position-dependent processing times

The paper is devoted to some single machine scheduling problems, where job processing times are defined by functions dependent on their positions in the sequence. It is assumed that each job is available for processing at its ready time. We prove some properties of the special cases of the problems for the following optimization criteria: makespan, total completion time and total weighted completion time. We prove strong NP-hardness of the makespan minimization problem for two different models of job processing time. The reductions are done from the well-known 3-Partition Problem. In order to solve the makespan minimization problems, we suggest the Earliest Ready Date algorithms, for which the worst-case ratios are calculated. We also prove that the makespan minimization problem with job ready times is equivalent to the maximum lateness minimization problem.     

Tropical optimization problems in time-constrained project scheduling

We consider a project that consists of activities to be performed in parallel under various temporal constraints, which include start-start, start-finish and finish-start precedence relationships, release times, deadlines and due dates. Scheduling problems are formulated to find optimal schedules for the project with respect to different objective functions to be minimized, such as the project makespan, the maximum deviation from the due dates, the maximum flow-time and the maximum deviation of finish times. We represent these problems as optimization problems in terms of tropical mathematics, and then solve them by applying direct solution methods of tropical optimization. As a result, new direct solutions of the scheduling problems are obtained in a compact vector form, which is ready for further analysis and practical implementation. The solutions are illustrated by simple numerical examples.     

工件优先级图为非连接图且含环的单机总加权拖期调度问题

为满足实际生产环境对工件加工顺序和工件到达时间的要求,提出了具有新特征的单机总加权拖期调度问题,其特点体现在:工件有动态到达时间,且由工件优先级关系构成的优先级图为非连接图且存在环的情况,对该问题建立数学规划模型,在扩展Tang和Xuan等的基础上,提出了结合双向动态规划的拉格朗日松弛算法求解该问题。在该算法的设计中,提出双向动态规划算法求解拉格朗日松弛问题,使得它可处理优先级图中一个工件可能有多个紧前或紧后工件的情况,采用次梯度算法更新拉格朗日乘子,基于拉格朗日松弛问题的解设计启发式算法构造可行解。实验测试结果显示,所设计的拉格朗日松弛算法能够在较短的运行时间内得到令人满意的近优解,为更复杂的调度问题的求解提供了思路。     

Multi-job Cutting Stock Problem with Due Dates and Release Dates

The common feature of cutting stock problems is to cut some form of stock materials to produce smaller pieces of materials in quantities matching orders received. Most research on cutting stock problems focuses on either generating cutting patterns to minimize wastage or determining the required number of stock materials to meet orders. In this paper, we examine a variation of cutting stock problems that arises in some industries where meeting orders' due dates is more important than minimizing wastage of materials. We develop two two-dimensional cutting stock models with due date and release date constraints. Since adding due dates and release dates makes the traditional cutting stock problem even more difficult to solve, we develop both LP-based and non-LP-based heuristics to obtain good solutions. The computational results show that the solution procedures are easy to implement and work very well.     

订单带多工类工件时的极小迟后范围问题

本文考虑下述由多工类工件组成的订单的单机排序问题：每一个客户提供一个由若干工件组成的订单,总共n个工件又分成k个类．当机器从加工某类中的工件转向加工不同于它的第i类工件时,需一调整时间si．每一订单有一给定的应交工时间,订单的完工时间定义为该定单所含全部工件完工时的时间．我们希望适当排列这n个工件,使得订单的迟后范围最小．相应这一排序问题,文中依不同的背景给出了以下二种模式：同类工件一起连续加工,工件的完工时间为其所属类中全部工件完工时的时间,用GT,Ba来表示；同类工件一起连续加工,工件的完工时间为其本身的完工时间,用GT,Ja来表示．对于这两种模式的排序同题,我们均证明了其NP-hard性并给出了对应的分枝定界算法．     

On unit time open shops with additional restrictions

We consider open shop problems with unit processing times,n jobs have to be processed onm machines. The order in which a given job is processed on the machines is not fixed. For each job a release time or a due date may be given. Additional, we consider the restriction that every machine must perform all corresponding operations without any delay time. Unit time open shop problems with release times to minimize total completion time were unsolved up to now for both allowed and forbidden delay times. We will solve these problems in the case of two and three machines. Furthermore we will give polynomial algorithms for several no-delay-problems with due dates.