Simulated annealing based simulation optimization method for solving integrated berth allocation and quay crane scheduling problems

Taşoğlu, Gökçeçiçek Tuna; Yildiz, Gokalp

doi:10.1016/j.simpat.2019.101948

Cited by 40 publications

(14 citation statements)

References 39 publications

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“…SA and simulation models can be integrated for the optimization purposes. Some of the areas in which SA-based simulation optimization have been applied include scheduling (Mattila & Virtanen, 2015;Tasoglu & Yildiz, 2019), production planning Alphanumeric Journal Volume 9, Issue 1, 2021 and control (Güçdemir & Selim, 2017), decision support systems (Ozcan, Tànfani, & Testi, 2017) and design alternative selection (Ameli, Mansour, & Ahmadi-Javid, 2019).…”

Section: Simulated Annealingmentioning

confidence: 99%

Disassembly Line Balancing by Using Simulation Optimization

Akpınar

Ilgın

Aktaş

2021

Alphanumeric Journal

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Increasing environmental awareness in today's society and stricter environmental regulations have forced manufacturing firms to take necessary actions for the recovery of end-of-life (EOL) products through different options (e.g., recycling, remanufacturing,). Disassembly is regarded as a critical operation in EOL treatment of used products since all product recovery options require the disassembly of EOL products at certain levels. This critical operation is generally carried out by forming disassembly lines in product recovery facilities. Miscellaneous methodologies based on heuristics, metaheuristics and mathematical programming have been proposed for the balancing of disassembly lines. Majority of those methodologies assume that disassembly line parameters are deterministic by ignoring the fact that a disassembly line involves great deal of uncertainty mainly due to uncertain conditions of arriving EOL products. Considering this high level of uncertainty, simulation modeling can be an effective tool for the modeling of disassembly lines. In this study, a simulation-based disassembly line balancing methodology is proposed for the explicit consideration of stochastic parameters. First, simulation model of a disassembly line is constructed. Since the disassembly line balancing problem has a combinatorial nature, two commonly used metaheuristics (i.e., genetic algorithms (GAs) and simulated annealing (SA)) are integrated with the simulation model in order to balance the disassembly line. The disassembly sequence and task assignments proposed by GA are compared with the sequence and task assignments proposed by SA. This comparison indicates that GA outperforms SA in four of eight performance measures while both algorithms have the same value for line efficiency measure.

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Section: Simulated Annealingmentioning

confidence: 99%

Disassembly Line Balancing by Using Simulation Optimization

Akpınar

Ilgın

Aktaş

2021

Alphanumeric Journal

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“…This type of approach for solving problems has been adopted to optimize Multi-Criteria Model Sequencing Problem (MC-MSP) of Mixed-Model Assembly Lines (MMALs) using a modified simulation integrated Smart Multi-Criteria Nawaz, Enscore, and Ham (SMC-NEH) algorithm [4]. Also, it has been applied to integrate planning and scheduling problem of multiple projects with different release dates and execution modes while considering the renewable and non-renewable resource constraints using raccoon family optimization (RFO) algorithm [5]. This approach has wide usage in the industry such as the unified representation model, and a simulated annealing-based approach used to facilitate the integration and optimization of process planning and scheduling modules of job shop to increase the flexibility and responsiveness [6].…”

Section: Related Workmentioning

confidence: 99%

Model for Integrating Production Scheduling and Maintenance Planning of Flow Shop Production System

et al. 2020

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In this paper, a model for integrating production scheduling and maintenance planning is proposed for flow shop production system. The suggested model in this paper is based on the optimal jobs sequence for jobs that will be processed in multiple machines connected in series. The objective of this study is to find the optimal sequence for jobs while reducing the total production and maintenance costs. The model works by generating an initial solution using longest processing time (LPT) dispatching rule. Then, tabu search algorithm is established to obtain the optimal sequence for jobs. Computational experiments are performed on problems with five serially machines which are assigned to process eight diverse jobs from the same product family. The result is compared with the genetic algorithm optimization technique under individual PM scheme for obtaining superior solutions that has been proved in the literature to be one of the best approach. The computational results show that the recommended approach is qualified over the simulation based genetic algorithm optimization technique. INDEX TERMS Integrated model, Job scheduling, Maintenance planning, Tabu search algorithm.

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“…Focusing on the confusion of the container terminal operation plan caused by uncertain events, most scholars at home and abroad have conducted relevant research from the perspective of multilevel handlings scheduling. Tasoglu et al [2] considered the dynamic arrival of ships and the integrated scheduling between berths and quay cranes (QCs) under random loading and unloading time and proposed a solution method based on simulation optimization. Xiang et al [3] studied the influence of four uncertain conditions, including deviation of arrival time of ships, deviation of loading and unloading operation time of ships, unplanned arriving of ships, and failure of QCs, on the simultaneous allocation strategy of berths and QCs under discrete berths.…”

Section: Introductionmentioning

confidence: 99%

Propagation of Uncertain Events in Multilevel Handlings at Container Terminals from the Perspective of Hypernetwork

Wang

2021

Discrete Dynamics in Nature and Society

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Due to the complexity and dynamics of container terminal multilevel handlings, the occurrence of uncertain events often leads to the disruption of many operation plans and forms a chain reaction, resulting in economic losses and impacts. In this paper, the uncertain event propagation network model of container terminal multilevel handlings is constructed by using the hypernetwork theory, and the propagation influence of uncertain events between multilevel handlings at container terminals is considered. Through the topological characteristics of the uncertain event propagation network, the risk analysis is carried out for the relevance of nodes and the influence extent of uncertain events, and a simulation analysis is carried out to verify the validity of this model. The simulation results show that the model conforms to power law distribution, and the number of old nodes has an impact on the growth of hyperedge. The research provides a powerful tool for analysing the influence of uncertain events and their derivative events in the multilevel handlings at container terminals and has positive significance for reducing the losses caused by the changes of terminal plans and improving the operation efficiency.

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Simulated annealing based simulation optimization method for solving integrated berth allocation and quay crane scheduling problems

Cited by 40 publications

References 39 publications

Disassembly Line Balancing by Using Simulation Optimization

Disassembly Line Balancing by Using Simulation Optimization

Model for Integrating Production Scheduling and Maintenance Planning of Flow Shop Production System

Propagation of Uncertain Events in Multilevel Handlings at Container Terminals from the Perspective of Hypernetwork

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