The theory of deterministic sequencing and scheduling has expanded rapidly during the past years. In this paper we survey the state of the art with respect to optimization and approximation algorithms and interpret these in terms of computational complexity theory. Special cases considered are single machine scheduling, identical, uniform and unrelated parallel machine scheduling, and open shop, flow shop and job shop scheduling. We indicate some problems for future research and include a selective bibliography.

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Optimization and Approximation in Deterministic Sequencing and Scheduling: a Survey

We survey and extend the results on the complexity of machine scheduling problems. After a brief review of the central concept of NP-completeness we give a classification of scheduling problems on single, different and identical machines and study the influence of various parameters on their complexity. The problems for which a polynomial-bounded algorithm is available are listed and NP-completeness is established for a large number of other machine scheduling problems. We finally discuss some questions that remain unanswered.

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Complexity of machine scheduling problems

/pdf/sequencing-and-scheduling-algorithms-and-complexity-lnutyrr3kz.pdf

Sequencing and scheduling: algorithms and complexity

Static scheduling of a program represented by a directed task graph on a multiprocessor system to minimize the program completion time is a well-known problem in parallel processing. Since finding an optimal schedule is an NP-complete problem in general, researchers have resorted to devising efficient heuristics. A plethora of heuristics have been proposed based on a wide spectrum of techniques, including branch-and-bound, integer-programming, searching, graph-theory, randomization, genetic algorithms, and evolutionary methods. The objective of this survey is to describe various scheduling algorithms and their functionalities in a contrasting fashion as well as examine their relative merits in terms of performance and time-complexity. Since these algorithms are based on diverse assumptions, they differ in their functionalities, and hence are difficult to describe in a unified context. We propose a taxonomy that classifies these algorithms into different categories. We consider 27 scheduling algorithms, with each algorithm explained through an easy-to-understand description followed by an illustrative example to demonstrate its operation. We also outline some of the novel and promising optimization approaches and current research trends in the area. Finally, we give an overview of the software tools that provide scheduling/mapping functionalities.

http://charm.cs.uiuc.edu/users/arya/docs/6.pdf

Static scheduling algorithms for allocating directed task graphs to multiprocessors

Scheduling subject to resource constraints: classification and complexity

Branch-and-bound methods are commonly used to find a permutation schedule that minimizes maximum completion time in an m-machine flow-shop. In this paper we describe a classification scheme for lower bounds that generates most previously known bounds and leads to a number of promising new ones as well. After a discussion of dominance relations within this scheme and of the implementation of each bound, we report on computational experience that indicates the superiority of one of the new bounds.

A General Bounding Scheme for the Permutation Flow-Shop Problem

Suppose we have n jobs that arrive simultaneously to be processed on a continuously available machine that can handle only one job at a time. Each job has a fixed processing time and a cost function that is nondecreasing in its finishing time. We want to find a schedule that minimizes total costs. After reviewing the relevant work on this problem, we present a new algorithm for a general cost function. The algorithm is tested for the well known case of a weighted tardiness criterion.

Minimizing total costs in one-machine scheduling

/pdf/minimizing-total-costs-in-one-machine-scheduling-3fvertu1qk.pdf

Minimizing Total Costs in One-Machine Scheduling

The classical combinatorial optimization problem of minimizing maximum completion time in a general job-shop has been the subject of extensive research. In this paper we review and extend this work. A general bounding approach is developed which includes all previously presented lower bounds as special cases. The strongest bound obtainable in this way is combined with two enumeration schemes, the relative merits of which are discussed. The results of some computational experiments and a large bibliography are included as well.

Job-Shop Scheduling by Implicit Enumeration

This paper adresses certain types of scheduling problems that arise when a parallel computation is to be executed on a multiprocessor. We define a model that allows for communication delays between precedence-related tasks, and propose a classification of various submodels. We also review complexity results and optimization and approximation algorithms that have been presented in the literature.

/pdf/multiprocessor-scheduling-with-communication-delays-5fiv2cbbqq.pdf

B.J. Lageweg

Papers

A General Bounding Scheme for the Permutation Flow-Shop Problem

Minimizing total costs in one-machine scheduling

Minimizing Total Costs in One-Machine Scheduling

Job-Shop Scheduling by Implicit Enumeration

Multiprocessor scheduling with communication delays