A non-delayed relax-and-cut algorithm for scheduling problems with parallel machines, due dates and sequence-dependent setup times

Paula, Mateus Rocha de; Mateus, Geraldo Robson; Ravetti, Martı́n Gómez

doi:10.1016/j.cor.2009.07.006

Cited by 15 publications

(11 citation statements)

References 31 publications

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“…Paula et al [45] propose a variant of the Lagrangian Relaxation to obtain good bounds to the problem of parallel machines scheduling with sequencedependent setup times. In this effort, the Lagrangian Relaxation is improved by the use of a metaheuristic as an internal procedure of the Lagrangian Relaxation.…”

Section: Location Of a Cross-docking Is Analyzed In Campbellmentioning

confidence: 99%

A hybrid Lagrangian metaheuristic for the cross-docking flow shop scheduling problem

Fonseca¹,

Nogueira²,

Ravetti³

2019

European Journal of Operational Research

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Cross-docking is a logistics strategy that minimizes the storage and picking functions of conventional warehouses. The objective is to unload the cargo from inbound trucks and directly load it into outbound trucks, with little or no storage. The success of the strategy depends on an efficient transshipment operation. This work undertakes a study of truck scheduling in a parallel dock cross-docking center. The problem is first modeled as a two-machine flow shop scheduling problem with precedence constraints, with the objective of minimizing the makespan, and later we generalize it to the parallel-dock case. We propose a hybrid method based on a Lagrangian relaxation technique through the volume algorithm. Using information from the Lagrangian multipliers, constructive heuristics with local search procedures generates good feasible solutions. With a series of cuts, the methodology finds tight bounds for small and large instance sizes, outperforming current results.

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Section: Location Of a Cross-docking Is Analyzed In Campbellmentioning

confidence: 99%

A hybrid Lagrangian metaheuristic for the cross-docking flow shop scheduling problem

Fonseca¹,

Nogueira²,

Ravetti³

2019

European Journal of Operational Research

Self Cite

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“…Dinh and Bae (2012) proposed a MILP model, as did Li et al (2012), who also proposed a Genetic Algorithm. Kang et al (2007), Armentano and de Franca Filho (2007), Chen (2009), de Paula et al (2010, Lin and Hsieh (2014) also presented meta-heuristic procedures, such as GRASP (Greedy Randomized Adaptive Search Procedure), Ant Colony Optimization, Iterated hybrid algorithms, and simulated annealing, among others. Exact approaches based on branch-and-bound was presented by Aramon Bajestani and Tavakkoli-Moghaddam (2009).…”

Section: Scheduling Problemmentioning

confidence: 99%

Improving effectiveness of parallel machine scheduling with earliness and tardiness costs: A case study

Muñoz-Villamizar¹,

Santos²,

Montoya‐Torres³

et al. 2019

10.5267/j.ijiec

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This paper assesses the effectiveness in scheduling independent jobs with earliness/tardiness costs and variable setup times applying the Overall Equipment Effectiveness (OEE). The OEE is a common metric for measuring the manufacturing productivity. We defined a mixed-integer linear programming formulation of the parallel machine scheduling problem with four different objective functions in order to compare different scheduling configurations. Real data, from a plastic container manufacturing company located in the Basque Country (Spain), were used to validate this approach. A sensitivity analysis was performed with different production capacities and earliness/tardiness costs in order to evaluate the trade-offs between economic performance (i.e., costs) and the partial rates of OEE (i.e., quality, performance and availability). The objective of this study is to propose a guideline to help management make decisions regarding the measurement and improvement of scheduling effectiveness through contemplating earliness, tardiness and variable setup times.

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“…In addition, the authors developed a hybrid genetic algorithm to minimize the makespan. Rocha de Paula et al (2010) proposed non-delayed relax-and-cut algorithm, based on the Lagrangian relaxation, for scheduling a set of jobs to be processed exactly once, on any machine of a set of unrelated parallel machines. In that paper, the authors assumed each job has a due date, weight, and, for each machine, an associated processing time and sequence-dependent setup time and the objective function is the total weighted tardiness of the jobs.…”

Section: Literature Reviewmentioning

confidence: 99%

Bi-objective parallel machines scheduling with sequence-dependent setup times using hybrid metaheuristics and weighted min–max technique

2010

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In the literature of multi-objective problem, there are different algorithms to solve different optimization problems. This paper presents a min-max multiobjective procedure for a dual-objective, namely make span, and sum of the earliness and tardiness of jobs in due window machine scheduling problems, simultaneously. In formulation of min-max method when this method is combined with the weighting method, the decision maker can have the flexibility of mixed use of weights and distance parameter to yield a set of Pareto-efficient solutions. This research extends the new hybrid metaheuristic (HMH) to solve parallel machines scheduling problems with sequence-dependent setup time that comprises three components: an initial population generation method based on an ant colony optimization (ACO), a simulated annealing (SA) as an evolutionary algorithm employs certain probability to avoid becoming trapped in a local optimum, and a variable neighborhood search (VNS) which involves three local search procedures to improve the population. In addition, two VNS-based HMHs, which are a combination of two methods, SA/VNS and ACO/VNS, are also proposed to solve the addressed scheduling problems. A design of experiments approach is employed to calibrate the parameters. The non-dominated sets obtained from HMH and two best existing bi-criteria scheduling algorithms are compared in terms of various indices and the computational results show that the proposed algorithm is capable of producing a number of high-quality Pareto optimal scheduling plans. Aside, an extensive computational experience is carried out to analyze the different parameters of the algorithm.

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A non-delayed relax-and-cut algorithm for scheduling problems with parallel machines, due dates and sequence-dependent setup times

Cited by 15 publications

References 31 publications

A hybrid Lagrangian metaheuristic for the cross-docking flow shop scheduling problem

A hybrid Lagrangian metaheuristic for the cross-docking flow shop scheduling problem

Improving effectiveness of parallel machine scheduling with earliness and tardiness costs: A case study

Bi-objective parallel machines scheduling with sequence-dependent setup times using hybrid metaheuristics and weighted min–max technique

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