Analytical Review on the Modern Optimization Algorithms in Logistics

Akkad, Mohammad Zaher; Bányai, Tamás

doi:10.32971/als.2020.006

Cited by 5 publications

(4 citation statements)

References 22 publications

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“…According to the working principle of the UHF RFID system, the energy received by the tag is roughly divided into two parts. One part is received by the tag antenna, enters the tag chip, and is rectified for the tag to work, and the other part is backscattered by the tag antenna [ 24 ]. To quantify the energy distribution between received and reflected, the tag antenna and tag chip can be modeled as shown in Figure 5 .…”

Section: International Trade Logistics Optimization Methodsmentioning

confidence: 99%

Optimal Design of International Trade Logistics Based on Internet of Things Technology

Wang

2022

Computational Intelligence and Neuroscience

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With the global industrial integration, trade exchanges between countries are becoming more and more frequent and the competition for related international trade logistics is becoming more and more intense. This paper aims to study the optimization design of international trade logistics based on Internet of Things technology. For this reason, this paper proposes an RFID method, through which it is possible to master a journey in the actual international trade logistics process. And it optimizes and improves its related paths, shortens the time delayed on the road, and achieves the purpose of mentioning the carrying capacity. And for the actual use effect, the relevant experiments and analysis parts are designed to simulate it. The experimental results of this paper show that the improved and optimized international trade logistics shortens the carrying time by 28.6% and increases the carrying capacity by 34.2%, which greatly promotes the development of the relevant international trade logistics industry.

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Section: International Trade Logistics Optimization Methodsmentioning

confidence: 99%

Optimal Design of International Trade Logistics Based on Internet of Things Technology

Wang

2022

Computational Intelligence and Neuroscience

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“…Second, optimization is a continuous operation that does not stop at a specific point; therefore, improvements in the mathematical modeling and the used metaheuristic algorithms can be researched. Hybrid algorithms specifically showed promising results in other cases [20]. Third, using case studies with a bigger number of smart bins seems promising to gain more reliable results.…”

Section: Discussion and Further Researchmentioning

confidence: 97%

“…The use of heuristic and metaheuristic algorithms has accelerated the progress of finding optimum solutions in various applications, particularly in logistics and supply chains [20]. Three metaheuristic algorithms were used in this research.…”

Section: Used Algorithmsmentioning

confidence: 99%

Design of Cyber-Physical Waste Management Systems Focusing on Energy Efficiency and Sustainability

Akkad

Haidar

Bányai

2022

Designs

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Industry 4.0 tools, such as the Internet of Things, artificial intelligence, digital twinning, and cloud computing, create a technological revolution that accelerates efforts to optimize the efficiency of cyber-physical operations and services. The waste management system requires a critical share of city logistics optimization, especially when using cyber-physical systems. Modern tools reduce the required municipal waste handling, such as loading and unloading, transportation, and warehousing, which leads to an increase in efficiency and flexibility, saving energy and time, and protecting the environment. In this paper, we present a cyber-physical waste management system solution by providing a cyber-physical model design and description, mathematical modeling, and two cases to investigate the impact on energy consumption and emissions. After an introduction and literature review, we describe the design of the cyber-physical model and tackle the first echelon. The designed system incorporates the IoT, smart bins with multi-percentage sensors, data and information analysis, vehicles’ actual routes, energy and emissions optimization, multi-echelon systems, time windows, and flexibility. Mathematical modeling equations for the optimized total energy consumption are presented. Thirty and twenty smart bins located in VIII District in Budapest are detailed as two case studies, where solutions for the optimized real routes and energy consumption are found using three metaheuristic algorithms: genetic, particle swarm, and simulated annealing optimization algorithms. The accrued emissions of CO, NMHC, CH4, NOx, and PM for the optimized solutions are calculated. Finally, the results are compared with a random traditional solution to measure the effectiveness.

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“…The optimization included the selection of material types and quantities next to the best sequence of materials that should be delivered to each assembly station at each time with the aim of minimizing the total cost related to material transportation and storage at stations [10]. Modern optimization algorithms have become commonly used in logistics applications such as heuristic and metaheuristic approaches [11], and this is reflected directly in the relationships with the sustainability aspect [12], for instance, by raising productivity efficiency [13] or decreasing GHG emissions.…”

Section: Introductionmentioning

confidence: 99%

Energy Consumption Optimization of Milk-Run-Based In-Plant Supply Solutions: An Industry 4.0 Approach

Akkad

Bányai

2023

Processes

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Smart factories are equipped with Industry 4.0 technologies including smart sensors, digital twin, big data, and embedded software solutions. The application of these technologies contributes to better decision-making, and this real-time decision-making can improve the efficiency of both manufacturing and related logistics processes. In this article, the transformation of conventional milk-run-based in-plant supply solutions into a cyber–physical milk-run supply is described, where the application of Industry 4.0 technologies makes it possible to make real-time decisions regarding scheduling, routing, and resource planning. After a literature review, this paper introduces the structure of Industry 4.0 technologies supported by milk-run-based in-plant supply. A mathematical model of milk-run processes is described including both scheduling and routing problems of in-plant supply. This mathematical model makes it possible to analyze the impact of Industry 4.0 technologies on the efficiency, performance, and flexibility of in-plant supply logistics. The scenarios’ analysis validates the mathematical model and shows that significant performance improvement and energy savings can be achieved using Industry 4.0 technologies. This performance improvement can lead to a more cost-efficient and sustainable in-plant supply solution, where not only logistics aspects but also energy efficiency and emissions can be taken into consideration.

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Analytical Review on the Modern Optimization Algorithms in Logistics

Cited by 5 publications

References 22 publications

Optimal Design of International Trade Logistics Based on Internet of Things Technology

Optimal Design of International Trade Logistics Based on Internet of Things Technology

Design of Cyber-Physical Waste Management Systems Focusing on Energy Efficiency and Sustainability

Energy Consumption Optimization of Milk-Run-Based In-Plant Supply Solutions: An Industry 4.0 Approach

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