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: A simulated annealing approach is applied to two bicriteria scheduling problems on a single machine and yields results that are superior to randomly generated schedules for the minimization of total flowtime and maximum earliness.
Abstract: In this paper, we apply a simulated annealing approach to two bicriteria scheduling problems on a single machine. The first problem is the strongly NP-hard problem of minimizing total flowtime and maximum earliness. The second one is the NP-hard problem of minimizing total flowtime and number of tardy jobs. We experiment on different neighbourhood structures as well as other parameters of the simulated annealing approach to improve its performance. Our computational experiments show that the developed approach yields solutions that are very close to lower bounds and hence very close to the optimal solutions of their corresponding problems for the minimization of total flowtime and maximum earliness. For the minimization of total flowtime and number tardy, our experiments show that the simulated annealing approach yields results that are superior to randomly generated schedules.
38 citations
TL;DR: In this article, the authors considered the single-machine parallel-batching problem with family jobs under on-line setting in the sense that we construct our schedule irrevocably as time proceeds and do not know of the existence of any job until its arrival.
38 citations
TL;DR: Four alternative local search methods are proposed: multi-start descent, simulated annealing, tabu search and a genetic algorithm; the best results are obtained with the genetic algorithm.
38 citations
TL;DR: The learning/aging effect in an n job single machine scheduling problem with common due date is considered and two bounds B[alpha] and for the learning index [alpha] are derived.
38 citations
TL;DR: This paper develops properties of optimal solutions and design a branch and bound algorithm and a dynamic programming algorithm with two extensions and empirically derive parameter settings leading to instances which are hard to solve on a single machine.
Abstract: This paper focuses on single machine scheduling subject to inventory constraints. Jobs add or remove items to or from the inventory, respectively. Jobs that remove items cannot be processed if the required number of items is not available. We consider scheduling problems on a single machine where the objective is to minimize the total weighted completion time. We develop properties of optimal solutions and design a branch and bound algorithm and a dynamic programming algorithm with two extensions. We compare the approaches in our computational study and empirically derive parameter settings leading to instances which are hard to solve.
37 citations