A survey of maintenance policies of deteriorating systems

An important class of machine scheduling problems is characterized by a no-wait or blocking production environment, where there is no intermediate buffer between machines. In a no-wait environment, a job must be processed from start to completion, without any interruption either on or between machines. Blocking occurs when a job, having completed processing on a machine, remains on the machine until a downstream machine becomes available for processing. A no-wait or blocking production environment typically arises from characteristics of the processing technology itself, or from the absence of storage capacity between operations of a job. In this review paper, we describe several well-documented applications of no-wait and blocking scheduling models and illustrate some ways in which the increasing use of modern manufacturing methods gives rise to other applications. We review the computational complexity of a wide variety of no-wait and blocking scheduling problems and describe several problems which remain open as to complexity. We study several deterministic flowshop, jobshop, and openshop problems and describe efficient and enumerative algorithms, as well as heuristics and results about their performance. The literature on stochastic no-wait and blocking scheduling problems is also reviewed. Finally, we provide some suggestions for future research directions.

A Survey of Machine Scheduling Problems with Blocking and No-Wait in Process

In most real-world environments, scheduling is an ongoing reactive process where the presence of a variety of unexpected disruptions is usually inevitable, and continually forces reconsideration and revision of pre-established schedules. Many of the approaches developed to solve the problem of static scheduling are often impractical in real-world environments, and the near-optimal schedules with respect to the estimated data may become obsolete when they are released to the shop floor. This paper outlines the limitations of the static approaches to scheduling in the presence of real-time information and presents a number of issues that have come up in recent years on dynamic scheduling.

The paper defines the problem of dynamic scheduling and provides a review of the state-of-the-art of currently developing research on dynamic scheduling. The principles of several dynamic scheduling techniques, namely, heuristics, meta-heuristics, multi-agent systems, and other artificial intelligence techniques are described in detail, followed by a discussion and comparison of their potential.

/pdf/a-survey-of-dynamic-scheduling-in-manufacturing-systems-1u4bc63f51.pdf

A survey of dynamic scheduling in manufacturing systems

http://akturk.bilkent.edu.tr/ie573/aytug.pdf

Executing production schedules in the face of uncertainties: a review and some future directions

Dynamic mapping (matching and scheduling) heuristics for a class of independent tasks using heterogeneous distributed computing systems are studied. Two types of mapping heuristics are considered: on-line and batch mode heuristics. Three new heuristics, one for batch and two for on-line, are introduced as part of this research. Simulation studies are performed to compare these heuristics with some existing ones. In total, five on-line heuristics and three batch heuristics are examined. The on-line heuristics consider; to varying degrees and in different ways, task affinity for different machines and machine ready times. The batch heuristics consider these factors, as well as aging of tasks waiting to execute. The simulation results reveal that the choice of mapping heuristic depends on parameters such as: (a) the structure of the heterogeneity among tasks and machines, (b) the optimization requirements, and (c) the arrival rate of the tasks.

https://www.engr.colostate.edu/~hj/conferences/211.pdf

Dynamic matching and scheduling of a class of independent tasks onto heterogeneous computing systems

Dynamic scheduling—a survey of research

An efficient heuristic approach to the scheduling of jobs in a flowshop

In this article we present two heuristic algorithms for scheduling in the constrained or continuous flow shop to minimize total flow time of jobs. Two heuristic preference relations are used as the basis for job insertion to build up a schedule by the heuristics. When evaluated over a large number of problems of various sizes, the heuristics are found to be very effective in yielding near-optimal solutions.

Dipak Chaudhuri

Papers

Dynamic scheduling—a survey of research

An efficient heuristic approach to the scheduling of jobs in a flowshop

Heuristic algorithms for continuous flow-shop problem

A multi-stage parallel-processor flowshop problem with minimum flowtime

Bicriteria scheduling problem for unrelated parallel machines