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.
Papers published on a yearly basis
Papers
More filters
TL;DR: Computational results of instances with sizes of up to 35 jobs prove the efficiency of the-branch-and bound approach in the optimal solution of the instances and cause the branch-and-bound algorithm to become even more efficient.
Abstract: This paper studies the problem of simultaneous minimization of the two criteria of maximum earliness and number of tardy jobs on a single machine. The goal is to generate the set of efficient sequences with respect to the two criteria. A heuristic algorithm named as H1 is developed for this problem and its efficiency is evaluated against a heuristic algorithm reported in the literature. The two algorithms are executed and applied to a set of instance problems. The computational results for instances with problem sizes of up to 150 jobs show that the H1 heuristic works far more efficiently than the competing heuristic. An exact procedure based on the branch-and-bound approach is also presented for the problem, in which the H1 heuristic is used as the upper bound. A lower bound and some dominance rules proposed in this paper cause the branch-and-bound algorithm to become even more efficient. Computational results of instances with sizes of up to 35 jobs prove the efficiency of the-branch-and bound approach in the optimal solution of the instances.
18 citations
TL;DR: A very large scale neighborhood search heuristic based on mathematical programming that makes use of the positional completion time formulation of the problem in which valid inequalities are added is presented.
18 citations
TL;DR: This work addresses a version of the Half-Product Problem and its restricted variant with a linear knapsack constraint and focuses on the development of fully polynomial-time approximation schemes with running times that depend quadratically on the number of variables.
18 citations
TL;DR: This paper addresses the problem of scheduling jobs in a single machine with sequence dependent setup times in order to minimize the total tardiness with respect to job due dates with variants of the GRASP metaheuristic that incorporate memory-based mechanisms for solving this problem.
Abstract: This paper addresses the problem of scheduling jobs in a single machine with sequence dependent setup times in order to minimize the total tardiness with respect to job due dates. We propose variants of the GRASP metaheuristic that incorporate memory-based mechanisms for solving this problem. There are two mechanisms proposed in the literature that utilize a long-term memory composed of an elite set of high quality and sufficiently distant solutions. The first mechanism consists of extracting attributes from the elite solutions in order to influence the construction of an initial solution. The second one makes use of path relinking to connect a GRASP local minimum with a solution of the elite set, and also to connect solutions from the elite set. Reactive GRASP, which probabilistically determines the degree of randomness in the GRASP construction throughout the iterations, is also investigated. Computational tests for instances involving up to 150 jobs are reported, and the proposed method is compared with heuristic and exact methods from the literature.
18 citations
07 Dec 2008
TL;DR: A self-adaptive Ant Colony Optimization approach that exploits a parameter adaptation mechanism to reduce the requirement of a preliminary parameter tuning and compared with recently proposed metaheuristic algorithms for the same problem, highlights the quality of the proposed approach.
Abstract: We propose a self-adaptive Ant Colony Optimization (AD-ACO) approach that exploits a parameter adaptation mechanism to reduce the requirement of a preliminary parameter tuning The proposed AD-ACO is based on an ACO algorithm adopting a pheromone model with a new global pheromone update mechanism We applied this algorithm to the single machine total weighted tardiness scheduling problem with sequence-dependent setup times and we executed an experimental campaign on a benchmark available in literature Results, compared with the ones produced by the ACO algorithm without adaptation mechanism and with those obtained by recently proposed metaheuristic algorithms for the same problem, highlight the quality of the proposed approach
18 citations