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: This paper considers the problem of scheduling n jobs on a single machine to minimise the sum of maximum earliness and tardiness, and proposes a branch-and-bound scheme that is consistent with the just-in-time production system.
Abstract: In this paper, we consider the problem of scheduling n jobs on a single machine to minimise the sum of maximum earliness and tardiness. Since this problem is trying to minimise the earliness and tardiness values, the model is consistent with the just-in-time production system. Most of publications on this subject have studied 'min-sum' objective functions, but in many settings balancing the costs of the jobs by minimising the cost of the worst scheduled job as 'min-max' criteria is more important. Using efficient lower and upper bounds and new dominance rules, a branch-and-bound scheme is proposed. The proposed algorithm is then tested on a set of randomly generated problems of different sizes, varying from 5 to 1,000 jobs. Using these approaches, we are able to solve all problems in a reasonable time. Computational results demonstrate the efficiency of our branch-and-bound algorithm over the existing methods reported in the literature.
17 citations
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TL;DR: In this article, the authors proposed a heuristic named simple weighted search procedure (SWSP) and a general variable neighborhood search algorithm (GVNS) to minimize the total tardiness for a set of independent jobs.
Abstract: This paper studies a single-machine scheduling problem with the objective of minimizing the total tardiness for a set of independent jobs. The processing time of a job is modeled as a step function of its starting time and a specific deteriorating date. The total tardiness as one important objective in practice has not been concerned in the studies of single-machine scheduling problems with step-deteriorating jobs. To overcome the intractability of the problem, we propose a heuristic named simple weighted search procedure (SWSP) and a general variable neighborhood search algorithm (GVNS) to obtain near optimal solutions. Extensive numerical experiments are carried out on randomly generated test instances in order to evaluate the performance of the proposed algorithms. By comparing to the CPLEX optimization solver, the heuristic SWSP and the standard variable neighborhood search, it is shown that the proposed GVNS algorithm can provide better solutions within a reasonable running time.
16 citations
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TL;DR: This work shows that the single machine scheduling problems with resource dependent release times and processing times are linearly decreasing functions of the amount of resources consumed and thus, is NP-complete.
16 citations
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TL;DR: Two meta-heuristics such as genetic algorithm and hybrid kangaroo simulated annealing are taken into consideration and Taguchi method is employed to tune the parameters of these algorithms and analyze the parametersof the studying problem simultaneously.
Abstract: We consider a single machine scheduling problem consisted of two groups of jobs with two different criteria that are minimizing total weighted completion time for the first group and minimizing maximum lateness for the second one. This problem which minimizes a mix of these criteria is in the NP-hard class of problems. Hence, inevitably we make use of meta-heuristic methods to tackle large scale problems. In this paper two meta-heuristics such as genetic algorithm and hybrid kangaroo simulated annealing are taken into consideration. Taguchi method is employed to tune the parameters of these algorithms and analyze the parameters of the studying problem simultaneously.
16 citations
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TL;DR: One of these algorithms allows us to compute a lower bound for the NP-hard problem NSP–NSD, which is used in a branch-and-bound (B&B) algorithm to solve problem N SP-NSD.
Abstract: In this paper, we study an integrated production and outbound distribution scheduling model with one manufacturer and one customer. The manufacturer has to process a set of jobs on a single machine and deliver them in batches to the customer. Each job has a release date and a delivery deadline. The objective of the problem is to issue a feasible integrated production and distribution schedule minimizing the transportation cost subject to the delivery deadline constraints. We consider three problems with different ways how a job can be produced and delivered: non-splittable production and delivery (NSP-NSD) problem, splittable production and non-splittable delivery (SP-NSD) problem and splittable production and delivery (SP-SD) problem. We provide a polynomial-time algorithm that solves two special cases of SP-NSD and SP-SD problems. Solving these problems allows us to compute a lower bound for the NP-hard problem NSP-NSD, which we use in a branch and bound (B&B) algorithm to solve problem NSP-NSD. The computational results show that the B&B algorithm outperforms a MILP formulation of the problem implemented on a commercial solver. keywords: single machine scheduling production and delivery release dates deadlines transportation costs branch and bound.
16 citations