A multi-objective optimization framework for a sustainable closed-loop supply chain network in the olive industry: Hybrid meta-heuristic algorithms

Expert Systems with Applications, Journal Year: 2022, Volume and Issue: 203, P. 117566 - 117566

Published: May 13, 2022

Language: Английский

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An Enhanced Social Engineering Optimizer for Solving an Energy-Efficient Disassembly Line Balancing Problem Based on Bucket Brigades and Cloud Theory

IEEE Transactions on Industrial Informatics, Journal Year: 2022, Volume and Issue: 19(5), P. 7148 - 7159

Published: July 26, 2022

A disassembly line is an industrialized and automated production which should be scheduled with high efficiency. Although many balancing optimization studies are contributed recently, they increase or reduce the number of workstations to balance line. From real-world managerial settings, decrease workstations, too expensive not realistic. The bucket brigades' self-balancing self-organizing, constrained by workstation beat time only needs distribute workers on according certain rules achieve after a period time. In this article, brigades method considering uncertainty proposed, in cloud model used represent uncertain proposed handles multiple objectives including smoothness, cost energy consumption minimized. To solve complex problem, article innovates new heuristic based social engineering optimizer as enhanced local search metaheuristic. Finally, ball collector verify effectiveness extensive analysis done compare performance other recent algorithms.

Language: Английский

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Sustainable and Robust Home Healthcare Logistics: A Response to the COVID-19 Pandemic

Symmetry, Journal Year: 2022, Volume and Issue: 14(2), P. 193 - 193

Published: Jan. 19, 2022

Today, research on healthcare logistics is an important challenge in developing and developed countries, especially when a pandemic such as COVID-19 occurs. The responses required during would benefit from efficiently designed model for robust sustainable logistics. In this study, we focus home services planning the routing scheduling of caregivers to visit patients’ homes. Due need social distancing pandemic, these are highly applicable reducing growth epidemic. addition challenge, must be redesigned meet standards triple bottom line approach based development goals. A finds balance between economic, environmental, criteria making decision. Although, recently, concept green has been studied total cost emissions services, far know, no conducted formulation services. To achieve justice caregivers, goal balancing working time find unemployment overtime. Another contribution develop scenario-based optimization address uncertainty assist with decisions planning. Since our multi-objective more complex than other studies, last novel establish efficient heuristic algorithm Lagrangian relaxation theory. An initial solution found by defining three algorithms. Our algorithms use symmetric pattern allocating patients pharmacies caregivers. Then, combination epsilon constraint method theory proposed generate high-quality Pareto-based solutions reasonable period. Finally, extensive analysis done show that practical, well some sensitivities provide managerial insights achieving practice.

Language: Английский

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Hybrid neural network-based metaheuristics for prediction of financial markets: a case study on global gold market

Journal of Computational Design and Engineering, Journal Year: 2023, Volume and Issue: 10(3), P. 1110 - 1125

Published: April 29, 2023

Abstract Technical analysis indicators are popular tools in financial markets. These help investors to identify buy and sell signals with relatively large errors. The main goal of this study is develop new practical methods fake obtained from technical the precious metals market. In paper, we analyze these different ways based on recorded for 10 months. novelty research propose hybrid neural network-based metaheuristic algorithms analyzing them accurately while increasing performance indicators. We combine a convolutional network bidirectional gated recurrent unit whose hyperparameters optimized using firefly algorithm. To determine select most influential variables target variable, use another successful recently developed metaheuristic, namely, moth-flame optimization Finally, compare proposed models other state-of-the-art single deep learning machine literature. finding that metaheuristics can be useful as decision support tool address control enormous uncertainties

Language: Английский

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A customized multi-neighborhood search algorithm using the tabu list for a sustainable closed-loop supply chain network under uncertainty

Applied Soft Computing, Journal Year: 2023, Volume and Issue: 144, P. 110495 - 110495

Published: June 15, 2023

Language: Английский

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Compressive strength prediction of high-strength oil palm shell lightweight aggregate concrete using machine learning methods

Environmental Science and Pollution Research, Journal Year: 2022, Volume and Issue: 30(1), P. 1096 - 1115

Published: Aug. 1, 2022

Language: Английский

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Implementation of Total Productive Maintenance to Improve Overall Equipment Effectiveness of Linear Accelerator Synergy Platform Cancer Therapy

International Journal of Engineering, Journal Year: 2022, Volume and Issue: 35(7), P. 1246 - 1256

Published: Jan. 1, 2022

The Jakarta Government Hospital provides cancer services with several available types of equipment, one which is the Linear accelerator (LINAC) Synergy Platform (SP) machine. phenomenon this machine experiencing a low effectiveness value because it not able to handle patient queue so reduce severity cancer. purpose study was determine factors causing Overall Equipment Effectiveness (OEE) and provide suggestions for improvement increase OEE value. new approach research using Total Productive Maintenance (TPM) analysis as success parameter TPM more identical in manufacturing industry. Another update Failure Mode Effect Analysis (FMEA) through Focus Group Discussions (FGD) experts. results found that influenced on LINAC SP were caused by breakdown loss 76.29%, setup 9.59%, idling minor stop 8.80%, decrease speed 5.29%. continuous consistent implementation Pillar has increased

Language: Английский

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A Sustainable Decision Support System for Drinking Water Systems: Resiliency Improvement against Cyanide Contamination

Infrastructures, Journal Year: 2022, Volume and Issue: 7(7), P. 88 - 88

Published: June 23, 2022

Maintaining drinking water quality is considered important in building sustainable cities and societies. On the other hand, insecurity an obstacle to achieving development goals based on issues of threatening human health well-being global peace. One dangers sources cyanide contamination due industrial wastewater leakage or sabotage. The present study investigates provides potential strategies remove by chlorination. In this regard, main novelty propose a decision support system for dirking case Iran. First, three scenarios have been defined with low ([CN−] = 2.5 mg L−1), medium 5 high 7.5 L−1) levels contamination. Then, optimal chlorine dosage has suggested as 2.9 L−1, 4.7 6.1 respectively, these scenarios. next step, residual was modelled mathematical approaches, which revealed that Gaussian distribution best performance accordingly. methodology developing hybrid approach model genetic algorithm. outcomes statistical evaluations illustrated both injected initial load greatest effects ions. Finally, proposed algorithm characterized multilayer perceptron algorithm, can forecast anion regression coefficient greater than 0.99 soft sensor. output demonstrate strong positive relationship between cyanide- (RCN−) chlorine. finding our improves resiliency against treatments.

Language: Английский

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A multi-criteria group-based decision-making method considering linguistic neutrosophic clouds

Expert Systems with Applications, Journal Year: 2023, Volume and Issue: 226, P. 119936 - 119936

Published: April 25, 2023

Language: Английский

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Data Envelopment Analysis models with imperfect knowledge of input and output values: An application to Portuguese public hospitals

Expert Systems with Applications, Journal Year: 2023, Volume and Issue: 231, P. 120543 - 120543

Published: June 1, 2023

Assessing the technical efficiency of a set observations requires that associated data composed inputs and outputs are perfectly known. If this is not case, then biased estimates will likely be obtained. Data Envelopment Analysis (DEA) one most extensively used mathematical models to estimate efficiency. It constructs piecewise linear frontier against which all compared. Since empirically defined, any deviation resulting from low quality (imperfect knowledge or IKD) may lead under/overestimation. In study, we model IKD and, then, apply so-called Hit & Run procedure randomly generate admissible observations, following some prespecified probability density functions. Sets limit domain with each observation. Any point belonging candidate figure out as observation for assessment. Hence, sampling must run sizable number times (infinite, in theory) such way it populates whole sets. The DEA technique during execution iteration bootstrapped scores We use scenarios show proposed routine can outperform available alternatives. also explain how estimations statistical inference. An empirical case study based on Portuguese public hospitals database (2013–2016) was addressed using method.

Language: Английский

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