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.     

A tabu search algorithm for scheduling pharmaceutical packaging operations

This paper addresses a practical scheduling problem arising in the packaging department of a pharmaceutical industrial plant. The problem is modeled as a multi-purpose machine scheduling problem with setup and removal times, release and due dates and additional constraints related to the scarce availability of tools and human operators. The objective functions are minimization of makespan and maximum tardiness in lexicographic order. Representing a solution with a directed graph allows us to devise an effective tabu search algorithm to solve the problem. Computational experiments, carried on real and randomly generated instances, show the effectiveness of this approach.     

Approximability of single machine scheduling with fixed jobs to minimize total completion time

We consider the single machine scheduling problem to minimize total completion time with fixed jobs, precedence constraints and release dates. There are some jobs that are already fixed in the schedule. The remaining jobs are free to be assigned to any free-time intervals on the machine in such a way that they do not overlap with the fixed jobs. Each free job has a release date, and the order of processing the free jobs is restricted by the given precedence constraints. The objective is to minimize the total completion time. This problem is strongly NP-hard. Approximability of this problem is studied in this paper. When the jobs are processed without preemption, we show that the problem has a linear-time n-approximation algorithm, but no pseudopolynomial-time (1 − δ)n-approximation algorithm exists even if all the release dates are zero, for any constant δ > 0, if P ≠ NP, where n is the number of jobs; for the case that the jobs have no precedence constraints and no release dates, we show that the problem has no pseudopolynomial-time (2 − δ)-approximation algorithm, for any constant δ > 0, if P ≠ NP, and for the weighted version, we show that the problem has no polynomial-time 2^q(n)-approximation algorithm and no pseudopolynomial-time q(n)-approximation algorithm, where q(n) is any given polynomial of n. When preemption is allowed, we show that the problem with independent jobs can be solved in O(n log n) time with distinct release dates, but the weighted version is strongly NP-hard even with no release dates; the problems with weighted independent jobs or with jobs under precedence constraints are shown having polynomial-time n-approximation algorithms. We also establish the relationship of the approximability between the fixed job scheduling problem and the bin-packing problem.     

Preemptive scheduling of independent jobs on parallel machines subject to financial constraints

The paper deals with the preemptive scheduling of independent jobs on parallel unrelated machines with the use of additional renewable resources (manpower, facilities) and the consumption of a nonrenewable resource (money). Money becomes available at different dates in specified amounts (financial constraints). Two scheduling criteria are considered: schedule length and total cost. The algorithm consists in solving a parametric linear program and using its results to construct a most satisfactory schedule in polynomial time. The reduction of job preemptions in a feasible schedule is considered.     

Infinite split scheduling: a new lower bound of total weighted completion time on parallel machines with job release dates and unavailability periods

This paper addresses an identical parallel machine scheduling problem with job release dates and unavailability periods to minimize total weighted completion time. This problem is known to be NP-hard in the strong sense. We propose a new lower bound that can be computed in polynomial time. The test on more than 8 400 randomly generated instances shows a very significant improvement with respect to existing results for previously studied special cases: without unavailability constraints, unweighted version, or identical job release dates. For instance, the average improvement for the unweighted problem is as much as 20.43% for 2 machines, 53.03% for 7 machines and 66.70% for 15 machines. For some instances, the improvement can be even as much as 93%.     

Maximization of solution flexibility for robust shop scheduling

We consider the problem of introducing flexibility in the schedule determination phase, for shop scheduling problems with release dates and deadlines. The flexibility is provided by generating a family of schedules, instead of a unique one. We represent a family of schedules by an ordered group assignment defining for each machine a sequence of groups where the operations within a group are totally permutable. We propose a polynomial time algorithm to evaluate the worst case completion time of operations in an ordered group assignment. We then consider the single machine problem with heads and deadlines associated to operations, as a sub-problem of the job shop problem. We propose polynomial time dynamic programming algorithms for minimizing the number of groups and for maximizing the number of characterized sequences, under specific constraints. Finally, computational experiences on job shop benchmarks, show the impact of grouping operations on the solution makespan value.     

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.     

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.     

资源量与开工时刻限制下航空公司地面作业调度问题

根据航空公司实际地面作业背景,提出了一个资源量与开工时刻双重限制下的排序模型.已知有若干个任务和有限的资源量,每个任务有一个到达时刻及要求完工期限.以极小化最大的延误时间为目标给出了一个启发式的多项式算法,并界定了近似解与最优解的误差范围.     

The multi-mode resource-constrained project scheduling problem with generalized precedence relations

In this paper, we tackle the challenging problem of scheduling activities to minimize the project duration, in which the activities (a) are subject to generalized precedence relations, (b) require units of multiple renewable, non-renewable and doubly constrained resources for which a limited availability is imposed, and (c) can be performed in one of several different ways, reflected in multiple activity scenarios or modes. These multiple modes give rise to several kinds of trade-offs (time/resource, time/cost and resource/resource trade-offs) which allow for a more efficient allocation and use of resources. We present a local search-based solution methodology which is able to handle many real-life project scheduling characteristics such as time-varying resource requirements and availabilities, activity ready times, due dates and deadlines, activity overlaps, activity start time constraints and other types of temporal constraints.     

Considerations of single-machine scheduling with deteriorating jobs

This paper considers some scheduling problems with deteriorating jobs. The objectives are to minimize the makespan, the total completion time, the total absolute deviation of completion time, the earliness, tardiness, and due date penalty, the sum of earliness penalties subject to no tardy jobs, respectively. We also explore two resource constrained scheduling problems: how to minimize the resource consumption with makespan constraints and how to minimize the makespan with the total resource consumption constraints. Several polynomial time algorithms are proposed to optimally solve the problems with the above objective functions.     

Single Machine Earliness-Tardiness Scheduling Problems Using the Equal—Slack Rule

The purpose of this paper is to analyse a special case of the non-pre-emptive single machine scheduling problem where the distinct due dates for each job are related to processing times according to the Equal–Slack rule. The scheduling objective is to minimize the sum of earliness and tardiness penalties. After determining some properties of the problem, the unrestricted case is shown to be equivalent to a polynomial time solvable problem, whereas the restricted case is shown to be NP-hard, and suggestions are made for further research.     

A graph coloring approach to scheduling of multiprocessor tasks on dedicated machines with availability constraints

We address a generalization of the classical 1- and 2-processor unit execution time scheduling problem on dedicated machines. In our chromatic model of scheduling machines have non-simultaneous availability times and tasks have arbitrary release times and due dates. Also, the versatility of our approach makes it possible to generalize all known classical criteria of optimality. Under these stipulations we show that the problem of optimal scheduling of sparse tree-like instances can be solved in polynomial time. However, if we admit dense instances then the problem becomes NP-hard, even if there are only two machines.     

On the single machine serial batching scheduling problem to minimize total completion time with precedence constraints, release dates and identical processing times

We consider the single machine, serial batching, total completion time scheduling problem with precedence constraints, release dates and identical processing times in this paper. The complexity of this problem is reported as open in the literature. We provide an O(n⁵) time algorithm to solve this problem.     

Review of properties of different precedence graphs for scheduling problems

Precedence constraints are a part of a definition of any scheduling problem. After recalling, in precise graph-theoretical terms, the relations between task-on-arc and task-on-node representations, we show the equivalence of two distinct results for scheduling problems. Furthermore, again using these links between representations, we exhibit several new polynomial cases for various problems of scheduling preemptable tasks on unrelated parallel machines under arbitrary resource constraints.     

极小化完工时间和的有界批调度问题

考虑m台并行批加工同型机上n个带有释放时间的工件的调度问题,目标是极小化完工时间和.给出了一个多项时间近似方案.     

Single machine scheduling with symmetric earliness and tardiness penalties

This research focuses on scheduling jobs with varying processing times and distinct due dates on a single machine subject to earliness and tardiness penalties. Hence, this work will find application in a just-in-time (JIT) production environment. The scheduling problem is formulated as a 0–1 linear integer program with three sets of constraints, where the objective is to minimize the sum of the absolute deviations between job completion times and their respective due dates. The first two sets of constraints are equivalent to the supply and demand constraints of an assignment problem. The third set, which represents the process time non-overlap constraints, is relaxed to form the Lagrangian dual problem. The dual problem is then solved using the subgradient algorithm. Efficient heuristics have also been developed in this work to yield initial primal feasible solutions and to convert primal infeasible solutions to feasibility. The computational results show that the relative deviation from optimality obtained by the subgradient algorithm is less than 3% for problem sizes varying from 10 to 100 jobs.     

Single machine total tardiness maximization problems: complexity and algorithms

In this paper, we consider some scheduling problems on a single machine, where weighted or unweighted total tardiness has to be maximized in contrast to usual minimization problems. These problems are theoretically important and have also practical interpretations. For the total weighted tardiness maximization problem, we present an NP-hardness proof and a pseudo-polynomial solution algorithm. For the unweighted total tardiness maximization problem with release dates, NP-hardness is proven. Complexity results for some other classical objective functions (e.g., the number of tardy jobs, total completion time) and various additional constraints (e.g., deadlines, weights and/or release dates of jobs may be given) are presented as well.     

Single machine unbounded parallel-batch scheduling with forbidden intervals

In this paper we consider the single machine parallel-batch scheduling with forbidden intervals. There are some forbidden intervals in which the machine cannot be available. The jobs are processed in batches form in the remaining free time-slots without preemption, where the processing time of a batch is defined to be the maximum processing time of the jobs in this batch. We show that, when the objective is bottleneck form, maximum lateness, or makespan with release dates of jobs, the considered problem can be solved in polynomial time.     

Single machine scheduling problem with controllable processing times and resource dependent release times

We consider two single machine scheduling problems with resource dependent release times and processing times, in which the release times and processing times are linearly decreasing functions of the amount of resources consumed. The objective is to minimize the total cost of makespan and resource consumption function that is composed of release time reduction and processing time reduction. In the first problem, the cost of reducing a unit release time for each job is common. We show that the problem can be solved in polynomial time. The second problem assumes different reduction costs of job release times. We show that the problem can be reduced polynomially from the partition problem and thus, is NP-complete.