Iterated Local Search for single-machine scheduling with sequence-dependent setup times to minimize total weighted tardiness

Xu, Hongyun; Lu, Zhengding; Cheng, T.C.E.

doi:10.1007/s10951-013-0351-z

Cited by 47 publications

(19 citation statements)

References 29 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Moreover, ILS-RVND F ast found or improved the average solutions of ILS XLC , ILS-RVND SBP and LOX⊕B in only 1.9, 4.1 and 3.0 seconds, respectively, on average. It is worth mentioning that the average solutions of ILS XLC in Xu et al (2013) and LOX⊕B in Xu et al (2014) were obtained in 100 seconds on an Intel Core i3 3.10 GHz with 2.0 GB of RAM, whereas the average solutions of ILS-RVND SBP were obtained in 23.4 seconds on an Intel Core i5 3.20 GHz with 4.0 GB of RAM. The hardware configuration of these two machines is slightly inferior than the one used in our experiments (Intel Core i7 with 3.40 GHz and 16 GB of RAM), and thus does not justify the considerable difference in terms of CPU time between ILS-RVND F ast and the three other methods.…”

Section: Ddementioning

confidence: 99%

“…Our proposed strategy enables the use of a large number of neighborhoods, such as moving blocks of consecutive jobs, which is likely to lead to high quality solutions. In fact, Xu et al (2013) showed that this type of neighborhood may indeed lead to better solutions for problem 1|s ij | w j T j .…”

Section: Introductionmentioning

confidence: 99%

“…Given the complexity of problem 1|s ij | w j T j , most methods proposed in the literature are based on (meta)heuristics. In particular, local search based metaheuristics had been quite effective in generating high quality solutions for this problem (Kirlik and Oguz, 2012;Xu et al, 2013;Subramanian et al, 2014). Nevertheless, one of the main limitations of such methods is the computational cost of evaluating a move during the local search.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Efficient local search limitation strategy for single machine total weighted tardiness scheduling with sequence-dependent setup times

Subramanian

Farias

2017

Computers & Operations Research

View full text Add to dashboard Cite

This paper concerns the single machine total weighted tardiness scheduling with sequence-dependent setup times, usually referred as 1|sij | wj Tj. In this N P-hard problem, each job has an associated processing time, due date and a weight. For each pair of jobs i and j, there may be a setup time before starting to process j in case this job is scheduled immediately after i. The objective is to determine a schedule that minimizes the total weighted tardiness, where the tardiness of a job is equal to its completion time minus its due date, in case the job is completely processed only after its due date, and is equal to zero otherwise. Due to its complexity, this problem is most commonly solved by heuristics. The aim of this work is to develop a simple yet effective limitation strategy that speeds up the local search procedure without a significant loss in the solution quality. Such strategy consists of a filtering mechanism that prevents unpromising moves to be evaluated. The proposed strategy has been embedded in a local search based metaheuristic from the literature and tested in classical benchmark instances. Computational experiments revealed that the limitation strategy enabled the metaheuristic to be extremely competitive when compared to other algorithms from the literature, since it allowed the use of a large number of neighborhood structures without a significant increase in the CPU time and, consequently, high quality solutions could be achieved in a matter of seconds. In addition, we analyzed the effectiveness of the proposed strategy in two other well-known metaheuristics. Further experiments were also carried out on benchmark instances of problem 1|sij | Tj.

show abstract

Section: Ddementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Efficient local search limitation strategy for single machine total weighted tardiness scheduling with sequence-dependent setup times

Subramanian

Farias

2017

Computers & Operations Research

View full text Add to dashboard Cite

show abstract

“…1 This benchmark set has been used by many researchers for a variety of search algorithms, such as dynamic programming [34], neighborhood search [24], iterated local search [39], valuebiased stochastic sampling [14], genetic algorithms [7], simulated annealing [8], ant colony optimization [23], etc.…”

Section: Sequence-dependent Setup Schedulingmentioning

confidence: 99%

Genetic Algorithm Parameter Control: Application to Scheduling with Sequence-Dependent Setups

Cicirello¹

2016

Proceedings of the 9th EAI International Conference on Bio-Inspired Information and Communications Technologies (Formerly BIONE

View full text Add to dashboard Cite

Genetic algorithms, and other forms of evolutionary computation, are controlled by numerous parameters, such as crossover and mutation rates, population size, among others depending upon the specific form of evolutionary computation as well as which operators are employed. Setting the values for these parameters is no simple task. In this paper, we develop a genetic algorithm with adaptive control parameters for an NP-Hard scheduling problem known as weighted tardiness scheduling with sequence-dependent setups. Our genetic algorithm uses the permutation representation along with the non-wrapping order crossover and insertion mutation operators. We encode the control parameters within the members of the population and evolve these during search using Gaussian mutation. We demonstrate this approach out-performs a manually tuned genetic algorithm for the problem, and that it converges upon effective parameter values very early in the run.

show abstract

“…The basic idea is to use larger neighborhood move operators rather than the swap and insertion move operators. Relying on this idea, Xu et al [45] presented a neighborhood structure called a Block Move in which l consecutive jobs (called a block) are inserted into another position in the sequence. They represent a block move by a triplet (i, k, l), where i represents the position of the first job of the block, k denotes the target position of the block to be inserted and l represents the size of the block.…”

Section: Variable Block Insertion Heuristicmentioning

confidence: 99%

A Variable Block Insertion Heuristic for the Blocking Flowshop Scheduling Problem with Total Flowtime Criterion

et al. 2016

View full text Add to dashboard Cite

Abstract:In this paper, we present a variable block insertion heuristic (VBIH) algorithm to solve the blocking flowshop scheduling problem with the total flowtime criterion. In the VBIH algorithm, we define a minimum and a maximum block size. After constructing the initial sequence, the VBIH algorithm starts with a minimum block size being equal to one. It removes the block from the current sequence and inserts it into the partial sequence sequentially with a predetermined move size. The sequence, which is obtained after several block moves, goes under a variable local search (VLS), which is based on traditional insertion and swap neighborhood structures. If the new sequence obtained after the VLS local search is better than the current sequence, it replaces the current sequence. As long as it improves, it keeps the same block size. However, if it does not improve, the block size is incremented by one and a simulated annealing-type of acceptance criterion is used to accept the current sequence. This process is repeated until the block size reaches at the maximum block size. Furthermore, we present a novel constructive heuristic, which is based on the profile fitting heuristic from the literature. The proposed constructive heuristic is able to further improve the best known solutions for some larger instances in a few seconds. Parameters of the constructive heuristic and the VBIH algorithm are determined through a design of experiment approach. Extensive computational results on the Taillard's well-known benchmark suite show that the proposed VBIH algorithm outperforms the discrete artificial bee colony algorithm, which is one of the most efficient algorithms recently in the literature. Ultimately, 52 out of the 150 best known solutions are further improved with substantial margins.

show abstract

Iterated Local Search for single-machine scheduling with sequence-dependent setup times to minimize total weighted tardiness

Cited by 47 publications

References 29 publications

Efficient local search limitation strategy for single machine total weighted tardiness scheduling with sequence-dependent setup times

Efficient local search limitation strategy for single machine total weighted tardiness scheduling with sequence-dependent setup times

Genetic Algorithm Parameter Control: Application to Scheduling with Sequence-Dependent Setups

A Variable Block Insertion Heuristic for the Blocking Flowshop Scheduling Problem with Total Flowtime Criterion

Contact Info

Product

Resources

About