Topic
Single-machine scheduling
About: Single-machine scheduling is a research topic. Over the lifetime, 2473 publications have been published within this topic receiving 56288 citations.
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TL;DR: In this paper, the authors consider a single machine scheduling problem in which the objective is to minimize the mean absolute deviation of job completion times about a common due date and present an algorithm for determining multiple optimal schedules under restrictive assumptions about the due date, and an implicit enumeration procedure when the assumptions do not hold.
Abstract: We consider a single machine scheduling problem in which the objective is to minimize the mean absolute deviation of job completion times about a common due date. We present an algorithm for determining multiple optimal schedules under restrictive assumptions about the due date, and an implicit enumeration procedure when the assumptions do not hold. We also establish the similarity of this problem to the two parallel machines mean flow time problem.
165 citations
10 May 1999
TL;DR: A new genetic algorithm to solve the flexible job-shop scheduling problem with makespan criterion and it is shown that this algorithm can find out high-quality schedules.
Abstract: Genetic algorithms have been applied to the scheduling of job shops-a class of very complicated combinatorial optimization problems. Among these algorithms for job shops, a common assumption is that the routes that jobs visit machines are fixed, this is not true for flexible job shops such as flexible manufacturing systems, where jobs have machine route flexibility. The paper presents a new genetic algorithm to solve the flexible job-shop scheduling problem with makespan criterion. The representation of solutions for the problem by chromosomes consists of two parts. The first part defines the routing policy and the second part the sequence of the operations on each machine. Genetic operators are introduced and used in the reproduction process of the algorithm. Numerical experiments show that our algorithm can find out high-quality schedules.
165 citations
TL;DR: This work describes an Ant Colony Optimization (ACO) algorithm having a new feature using look-ahead information in the transition rule that shows an improvement in performance.
Abstract: We compare several heuristics for solving a single machine scheduling problem. In the operating situation modelled, setup times are sequence-dependent and the objective is to minimize total tardiness. We describe an Ant Colony Optimization (ACO) algorithm having a new feature using look-ahead information in the transition rule. This feature shows an improvement in performance. A comparison with a genetic algorithm, a simulated annealing approach, a local search method and a branch-and-bound algorithm indicates that the ACO that we describe is competitive and has a certain advantage for larger problems.
160 citations
TL;DR: It is proved that the worst-case ratio of the classical LPT algorithm is 2 and there is no polynomial time approximation algorithm with a worst- case ratio less than 2 unless P = NP, which implies that the L PT algorithm is the best possible.
159 citations
TL;DR: This work considers the scheduling problem in which jobs with release dates and delivery times are to be scheduled on one machine, and presents a 4/3-approximation algorithm for the problem with precedence constraints among the jobs, and two polynomial approximation schemes for the problems without precedence constraints.
Abstract: We consider the scheduling problem in which jobs with release dates and delivery times are to be scheduled on one machine. We present a 4/3-approximation algorithm for the problem with precedence constraints among the jobs, and two polynomial approximation schemes for the problem without precedence constraints. At the core of each of the algorithms presented is Jackson's Rule-a simple but seemingly robust heuristic for the problem.
159 citations