Optimization of Just-In-Sequence Supply: A Flower Pollination Algorithm-Based Approach

Bányai, Tamás; Illés, Béla; Gubán, Miklós; Gubán, Ákos; Schenk, Fabian; Bányai, Ágota

doi:10.3390/su11143850

Cited by 9 publications

(4 citation statements)

References 109 publications

(110 reference statements)

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“…Also, an upgraded firefly algorithm (UFA) [19] was presented to enhance the performance in solving constrained engineering optimization problems. Bányai et al [20] presented a mathematical model of just-in-sequence supply and a flower pollination algorithm-based heuristic was used to determine the optimal assignment and schedule for each sequence to minimize the total purchasing cost, which supports improving cost efficiency, and its performance to increase cost-efficiency in just-in-sequence solutions was validated. Inventory control of reverse logistics for shipping electronic commerce was presented [21] based on an improved multi-objective particle swarm algorithm, and it showed effective results.…”

Section: Content Analysis and Discussionmentioning

confidence: 99%

Analytical Review on the Modern Optimization Algorithms in Logistics

Akkad

Bányai

2020

ALS

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Optimization algorithms are used to reach the optimum solution from a set of available alternatives within a short time relatively. With having complex problems in the logistics area, the optimization algorithms evolved from traditional mathematical approaches to modern ones that use heuristic and metaheuristic approaches. Within this paper, the authors present an analytical review that includes illustrative and content analysis for the used modern algorithms in the logistics area. The analysis shows accelerated progress in using the heuristic/metaheuristic algorithms for logistics applications. It also shows the strong presence of hybrid algorithms that use heuristic and metaheuristic approaches. Those hybrid algorithms are providing very efficient results.

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Section: Content Analysis and Discussionmentioning

confidence: 99%

Analytical Review on the Modern Optimization Algorithms in Logistics

Akkad

Bányai

2020

ALS

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“…In general, these studies focus primarily on a specific problem. Furthermore, the solutions that are used also vary (e.g., [1]).…”

Section: Path Planningmentioning

confidence: 99%

A Path Planning Model for Stock Inventory Using a Drone

et al. 2022

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In this study, a model and solution are shown for controlling the inventory of a logistics warehouse in which neither satellite positioning nor IoT solutions can be used. Following a review of the literature on path planning, a model is put forward using a drone that can be moved in all directions and is suitable for imaging and transmission. The proposed model involves three steps. In the first step, a traversal path definition provides an optimal solution, which is pre-processing. This is in line with the structure and capabilities of the warehouse. In the second step, the pre-processed path determines the real-time movement of the drone during processing, including camera movements and image capture. The third step is post-processing, i.e., the processing of images for QR code identification, the interpretation of the QR code, and the examination of matches and discrepancies for inventory control. A key benefit for the users of this model is that the result can be achieved without any external orientation tools, relying solely on its own movement and the organization of a pre-planned route. The proposed model can be effective not only for inventory control, but also for exploring the structure of a warehouse shelving system and determining empty cells.

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“…The algorithm was presented by Xin-She Yang in 2012 [64]. The algorithm is a universal tool for optimization in different areas of science, economics and also social behavior studies [65][66][67][68]. It belongs to swarm-based metaheuristic algorithms.…”

Section: Nature Inspired Optimization Algorithm-the Flower Pollinatio...mentioning

confidence: 99%

Speed Control Based on State Vector Applied for Electrical Drive with Elastic Connection

et al. 2022

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The paper is focused on issues related to the control of electrical drives with oscillations of state variables. The main problem deals with the construction of the mechanical part, which contains elastic elements used as a coupling between the motor machine and the load. In such cases, strict tracking of the reference trajectory is difficult, so damping of the disturbances is necessary. For this purpose, the full state vector of the object is applied as the feedback signal for the speed controller. This method is efficient and relatively easy to implement (including the hardware part). However, the control accuracy is dependent on the quality of the parameters identification and the invariance of the object. Thus, two adaptive structures are proposed for the two-mass system. Moreover, selected coefficients were optimized using metaheuristic algorithms (symbiotic organism search and flower pollination algorithm). After presentation of the preliminaries and mathematical background, tests were conducted, and the numerical simulations are shown. Finally, the experimental verification for the 0.5 kW DC machines was performed. The results confirm the theoretical concept and the initial assumptions: the state controller leads to the precise control of the drive with a long shaft; recalculation of the parameters can improve the work of the drive under changes of time constants; modern design tools are appropriate for this application.

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Optimization of Just-In-Sequence Supply: A Flower Pollination Algorithm-Based Approach

Cited by 9 publications

References 109 publications

Analytical Review on the Modern Optimization Algorithms in Logistics

Analytical Review on the Modern Optimization Algorithms in Logistics

A Path Planning Model for Stock Inventory Using a Drone

Speed Control Based on State Vector Applied for Electrical Drive with Elastic Connection

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