A Simulated Annealing Approach to Bicriteria Scheduling Problems on a Single Machine

In this paper, we apply a simulated annealing approach to two bicriteria scheduling problems on a single machine. The first problem is the strongly NP-hard problem of minimizing total flowtime and maximum earliness. The second one is the NP-hard problem of minimizing total flowtime and number of tardy jobs. We experiment on different neighbourhood structures as well as other parameters of the simulated annealing approach to improve its performance. Our computational experiments show that the developed approach yields solutions that are very close to lower bounds and hence very close to the optimal solutions of their corresponding problems for the minimization of total flowtime and maximum earliness. For the minimization of total flowtime and number tardy, our experiments show that the simulated annealing approach yields results that are superior to randomly generated schedules.     

Scheduling a deteriorating maintenance activity on a single machine

We study a problem of scheduling a maintenance activity on a single machine. Following several recent papers, the maintenance is assumed to be deteriorating, that is, delaying the maintenance increases the time required to perform it. The following objective functions are considered: makespan, flowtime, maximum lateness, total earliness, tardiness and due-date cost, and number of tardy jobs. We introduce polynomial time solutions for all these problems.     

Single machine scheduling to minimize weighted earliness subject to no tardy jobs

This paper considers the single machine scheduling problem where the objective is to minimize the total weighted earliness subject to no tardy jobs. Known results for a well researched single machine scheduling problem where the objective is to minimize the weighted completion time subject to no tardy jobs have been used in analyzing this problem. Several important results are proved and both exact and approximate methods are developed to solve this problem.     

Minimizing due date related performance measures on two batch processing machines

This paper considers a scheduling problem in a two-machine flowshop of two batch processing machines. On each batch processing machine, jobs are processed in a batch, and each batch is allowed to contain jobs up to the maximum capacity of the associated machine. The scheduling problem is analyzed with respect to three due date related objectives including maximum tardiness, number of tardy jobs and total tardiness. In the analysis, several solution properties are characterized and based upon these properties, three efficient polynomial time algorithms are developed for minimizing the due date related measures.     

Serial-batching scheduling with time-dependent setup time and effects of deterioration and learning on a single-machine

This paper deals with serial-batching scheduling problems with the effects of deterioration and learning, where time-dependent setup time is also considered. In the proposed scheduling models, all jobs are first partitioned into serial batches, and then all batches are processed on a single serial-batching machine. The actual job processing time is a function of its starting time and position. In addition, a setup time is required when a new batch is processed, and the setup time of the batches is time-dependent, i.e., it is a linear function of its starting time. Structural properties are derived for the problems of minimizing the makespan, the number of tardy jobs, and the maximum earliness. Then, three optimization algorithms are developed to solve them, respectively.     

Fabrication scheduling on a single machine with due date constraints

There is a fabrication machine available for processing a set of jobs. Each job is associated with a due date and consists of two parts, one is common among all products and the other is unique to itself. The unique components are processed individually and the common parts are grouped into batches for processing. A constant setup time is incurred when each batch is formed. The completion time of a job is defined as the time when both of its unique and common components are completed. In this paper, we consider two different objectives. The first problem seeks to minimize the maximum tardiness, and the second problem is to minimize the number of tardy jobs. To minimize the maximum tardiness, we propose a dynamic programming algorithm that optimally solves the problem in polynomial time. Next, we show NP-hardness proof and design a pseudo-polynomial time dynamic programming algorithm for the problem of minimizing the number of tardy jobs.     

Minimizing the weighted number of early and tardy jobs in a stochastic single machine scheduling problem

We study a static stochastic single machine scheduling problem in which jobs have random processing times with arbitrary distributions, due dates are known with certainty, and fixed individual penalties (or weights) are imposed on both early and tardy jobs. The objective is to find an optimal sequence that minimizes the expected total weighted number of early and tardy jobs. The general problem is NP-hard to solve; however, in this paper, we develop certain conditions under which the problem is solvable exactly. An efficient heuristic is also introduced to find a candidate for the optimal sequence of the general problem. Our illustrative examples and computational results demonstrate that the heuristic performs well in identifying either optimal sequences or good candidates with low errors. Furthermore, we show that special cases of the problem studied here reduce to some classical stochastic single machine scheduling problems including the problem of minimizing the expected weighted number of early jobs and the problem of minimizing the expected weighted number of tardy jobs which are both solvable by the proposed exact or heuristic methods.     

Single machine scheduling problems with financial resource constraints: Some complexity results and properties

We consider single machine scheduling problems with a non-renewable resource. These types of problems have not been intensively investigated in the literature so far. For several problems of these types with standard objective functions (namely the minimization of makespan, total tardiness, number of tardy jobs, total completion time and maximum lateness), we present some complexity results. Particular attention is given to the problem of minimizing total tardiness. In addition, for the so-called budget scheduling problem with minimizing the makespan, we present some properties of feasible schedules.     

Scheduling unit-length jobs with machine eligibility restrictions

We consider uniform parallel machine scheduling problems with unit-length jobs where every job is only allowed to be processed on a specified subset of machines. We develop efficient methods to solve problems with various objectives, including minimizing a total tardiness function, a maximum tardiness function, total completion time, the number of tardy jobs, the makespan, etc.     

Minimizing mean tardiness subject to unspecified minimum number tardy for a single machine

In this paper we propose a hybrid branch and bound algorithm for solving the problem of minimizing mean tardiness for a single machine problem subject to minimum number of tardy jobs. Although the minimum number of tardy jobs is known, the subset of tardy job is not known. The proposed algorithm uses traditional branch and bound scheme where lower bounds on mean tardiness are calculated coupled with using the information that the number of tardy jobs is known. It also uses an insertion algorithm which determines the optimal mean tardiness once the subset of tardy jobs is specified. An example is solved to illustrate the developed procedure.     

Two due date assignment problems in scheduling a single machine

We study two single-machine scheduling problems: minimizing the sum of weighted earliness, tardiness and due date assignment penalties and minimizing the weighted number of tardy jobs and due date assignment costs. We prove that both problems are strongly NP-hard and give polynomial solutions for some important special cases.     

Minimizing number of tardy jobs on a batch processing machine with incompatible job families

In this paper we consider the problem of minimizing number of tardy jobs on a single batch processing machine. The batch processing machine is capable of processing up to B jobs simultaneously as a batch. We are given a set of n jobs which can be partitioned into m incompatible families such that the processing times of all jobs belonging to the same family are equal and jobs of different families cannot be processed together. We show that this problem is NP-hard and present a dynamic programming algorithm which has polynomial time complexity when the number of job families and the batch machine capacity are fixed. We also show that when the jobs of a family have a common due date the problem can be solved by a pseudo-polynomial time procedure.     

一类变工时的单机排序问题

提出了一类可变加工时间的单台机器排序问题,着重考虑如下的目标函数：最小化工件排序长度、完工时间之和误工工件数等等,且用受束的等规模划分问题证明了可变加工时间的单台机器排序问题是ＮＰ－完全的。     

Scheduling a single machine to minimize earliness penalties subject to the SLK due-date determination method

This paper considers a single machine scheduling problem. There are n jobs to be processed on a single machine. The problem is to minimize total earliness penalties subject to no tardy jobs. The problem is NP-complete if the due-dates are arbitrary. We study the problem when the due-dates are determined by the equal slack (SLK) method. Two special cases of the problem are solved in polynomial time. The first one is the problem with equally weighted monotonous penalty objective function. The second one is the problem with weighted linear penalty objective function.     

一个双目标单机调度问题及其几个多项式可解情形

研究了一个双目标单机调度问题及其几个多项式可解的情形。问题的主目标是延误工件数最小,在此条件下,最小化各工件加权提前期的总和,由于该问题是NP一难的,故研究求解它的一个启发式算法及问题的几个多项式可解的特殊情形。     

工件加工时间是开工时间线性函数的单机排序问题

研究了具有线性恶化工件的单机排序问题,其中线性恶化工件指的是工件的加工时间是开工时间的线性增长函数.在一般情况下,对目标函数为极小化完工时间平方和与极小化总误工数问题分别给出了最优算法.此外,在分段情况下,对目标函数为极小化最大完工时间问题也给出了最优算法.     

Single machine SLK/DIF due window assignment problem with job-dependent linear deterioration effects

We consider single machine scheduling problems with deteriorating jobs and SLK/DIF due window assignment, where the deteriorating rates of jobs are assumed to be job-dependent. We consider two different objectives under SLK and DIF due window assignment, respectively. The first objective is to minimise total costs of earliness, tardiness, due window location and due window size, while the second objective is to minimise a cost function that includes number of early jobs, number of tardy jobs and the costs for due window location and due window size. We study the optimality properties for all problems and develop algorithms for solving these problems in polynomial time.     

带强制工期的可中断单机排序问题

工件带强制工期,指工件必须在已给定的工期内完工,不得延迟.这种环境在实际应用中随处可见.如果工件过早提前完工,意味着工件还需要保管,将会产生额外费用.本文讨论了在单机上,加工带准备时间与强制工期的n个可中断工件,在机器可空闲条件下,确定一个工件排序,使得提前完工时间和最小.先考虑了问题的复杂性,通过奇偶划分问题归约,证明了其是NP-complete的.而后,讨论了加工时间相等的特殊情形,由于工件不允许延迟,问题可能会无可行排序,因此提出了—个多项式时间算法,既能判定可行性,又能针对可行问题获得最优排序.     

Single machine scheduling to minimize total weighted earliness subject to minimal number of tardy jobs

Motivated by just-in-time manufacturing, we consider a single machine scheduling problem with dual criteria, i.e., the minimization of the total weighted earliness subject to minimum number of tardy jobs. We discuss several dominance properties of optimal solutions. We then develop a heuristic algorithm with time complexity O(n³) and a branch and bound algorithm to solve the problem. The computational experiments show that the heuristic algorithm is effective in terms of solution quality in many instances while the branch and bound algorithm is efficient for medium-size problems.     

Minimizing the weighted number of tardy jobs and maximum tardiness in relocation problem with due date constraints

The relocation problem addressed in this paper is to determine a reconstruction sequence for a set of old buildings, under a limited budget, such that there is adequate temporary space to house the residents decanted during rehabilitation. It can be regarded as a resource-constrained scheduling problem where there is a set of jobs to be processed on a single machine. Each job demands a number of resources for processing and returns probably a different number of resources on its completion. Given a number of initial resources, the problem seeks to determine if there is a feasible sequence for the successful processing of all the jobs. Two generalizations of the relocation problem in the context of single machine scheduling with due date constraints are studied in this paper. The first problem is to minimize the weighted number of tardy jobs under a common due date. We show that it is NP-hard even when all the jobs have the same tardy weight and the same resource requirement. A dynamic programming algorithm with pseudo-polynomial computational time is proposed for the general case. In the second problem, the objective is to minimize the maximum tardiness when each job is associated with an individual due date. We prove that it is strongly NP-hard. We also propose a pseudo-polynomial time dynamic programming algorithm for the case where the number of possible due dates is predetermined.