Analytical Review on the Modern Optimization Algorithms in Logistics

2020 ◽  
Vol 14 (1) ◽  
pp. 25-31
Author(s):  
Mohammad Zaher Akkad ◽  
Tamás Bányai
Keyword(s):  
Content Analysis ◽  
Optimization Algorithms ◽  
Hybrid Algorithms ◽  
Metaheuristic Algorithms ◽  
Complex Problems ◽  
Analytical Review ◽  
Optimum Solution ◽  
Short Time ◽  
Modern Optimization

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.

scholarly journals Research of Optimization Algorithms used in MIMO-OFDM Systems

2019 ◽  
Vol 8 (6S3) ◽  
pp. 1707-1712
Keyword(s):  
Optimization Algorithms ◽  
Pso Algorithm ◽  
Least Square ◽  
Advanced Technology ◽  
Ofdm Systems ◽  
Matlab Simulation ◽  
Broadband Wireless ◽  
Mimo Ofdm ◽  
Narrowband Channels ◽  
Optimum Solution

Orthogonal Frequency Diνision Multiplexing (OFDM) technology is used to split large amount of data into several parallel narrowband channels with different frequencies orthogonally such that interference is reduced. Multiple Input M𝒖ltiple Output (MIMO) technology uses diversity ƫechnique such that capɑcity of the system and data throughput can be improved. Thereby combining both the technologies as MIMOOFDM achieves great spectral efficiency and it is the most advanced technology in broadband wireless communication. Ƭhe channel estimation techniques like Leaşt Square Estimation (LSE) algorithm is used to estimate the channel and the performancе of MIMO-OFDM system is еvaluated on the basis of Bit Error Ratе (BER) and MеanSquarе Error (MSE) by using MATLAB simulation. Further enhancement can be achieved by applying optimization algorithms, in this paper to find the optimum solution Partic1e Swɑrm Optimization Algorithm (PSO) is uti1ized when the pilots are placed randomly. Simulation outcome show that PSO algorithm outperforms the LSE when random pilots are used for MIMO-OFDM systems.

scholarly journals The Content Analysis of Social Media Shares in Turkish Related to COVID-19

2021 ◽  
Vol 11 (3) ◽  
pp. 113-137
Author(s):  
M. Fevzi Esen
Keyword(s):  
Social Media ◽  
Content Analysis ◽  
Information Source ◽  
Latent Semantic Indexing ◽  
Decision Makers ◽  
Semantic Indexing ◽  
Social Media Networks ◽  
Network Analyses ◽  
Media Platform ◽  
Short Time

A remarkable increase has currently been happening in social media platform content related to COVID-19. Users have created large volumes of content on various topics over a short time, interacting with people in real-time. This also has transformed social media into an indispensable information source for any crisis. This study aims to explore the information content on COVID-19 disseminated through social media and to discover prominent topics in shares on COVID-19. In this regard, we have retrieved 17,542 tweets shared in Turkish. A content analysis of social media shares has been carried out, with latent semantic indexing and network analyses being performed to detect the relationships and interactions among shares. As a result, the most shared topics have been concluded to be on yasak [lockdown], tedbir [precaution], karantina [quarantine], and vaka [case], with communication being frequently passed using this semantic string and information exchanges being faster within the network. In addition, shares related to hygiene, masks, and distancing were determined to have occurred less than shares related to precautions, rules, cases, and lockdowns. The number of likes and retweets for content with social propaganda such as #evdekal [stayathome], #evdehayatvar [lifeathome], and #birliktebaşaracağız [togetherwesucceed] were low and not found in a semantic string. This suggests social propaganda through social media to have had a limited impact on epidemic management. In conclusion, identifying the prominent issues in social media posts and the characteristics of social media networks will help decision-makers determine appropriate policies for controlling and preventing the pandemic’s spread.

scholarly journals Application of Artificial Intelligence to Evaluate the Fresh Properties of Self-Consolidating Concrete

Materials ◽  
2021 ◽  
Vol 14 (17) ◽  
pp. 4885
Author(s):  
Yuping Feng ◽  
Masoud Mohammadi ◽  
Lifeng Wang ◽  
Maria Rashidi ◽  
Peyman Mehrabi
Keyword(s):  
Fuzzy Inference ◽  
Information Source ◽  
Pearson Correlation ◽  
Optimization Algorithms ◽  
Pso Algorithm ◽  
Metaheuristic Algorithms ◽  
Ring Test ◽  
Inference System ◽  
Self Consolidating Concrete ◽  
Non Destructive

This paper numerically investigates the required superplasticizer (SP) demand for self-consolidating concrete (SCC) as a valuable information source to obtain a durable SCC. In this regard, an adaptive neuro-fuzzy inference system (ANFIS) is integrated with three metaheuristic algorithms to evaluate a dataset from non-destructive tests. Hence, five different non-destructive testing methods, including J-ring test, V-funnel test, U-box test, 3 min slump value and 50 min slump (T50) value were performed. Then, three metaheuristic algorithms, namely particle swarm optimization (PSO), ant colony optimization (ACO) and differential evolution optimization (DEO), were considered to predict the SP demand of SCC mixtures. To compare the optimization algorithms, ANFIS parameters were kept constant (clusters = 10, train samples = 70% and test samples = 30%). The metaheuristic parameters were adjusted, and each algorithm was tuned to attain the best performance. In general, it was found that the ANFIS method is a good base to be combined with other optimization algorithms. The results indicated that hybrid algorithms (ANFIS-PSO, ANFIS-DEO and ANFIS-ACO) can be used as reliable prediction methods and considered as an alternative for experimental techniques. In order to perform a reliable analogy of the developed algorithms, three evaluation criteria were employed, including root mean square error (RMSE), Pearson correlation coefficient (r) and determination regression coefficient (R2). As a result, the ANFIS-PSO algorithm represented the most accurate prediction of SP demand with RMSE = 0.0633, r = 0.9387 and R2 = 0.9871 in the testing phase.

scholarly journals A Survey on Meta-heuristic Algorithms for Global Optimization Problems

2020 ◽  
pp. 48-60
Author(s):  
Abdel Nasser H. Zaied ◽  
Mahmoud Ismail ◽  
Salwa El-Sayed ◽  
◽  
◽  
...  
Keyword(s):  
Global Optimization ◽  
Real World ◽  
Heuristic Algorithms ◽  
Optimization Problems ◽  
Optimization Algorithms ◽  
Traditional Methods ◽  
Complex Problems ◽  
First Choice ◽  
Important Field ◽  
Real World Problems

Optimization is a more important field of research. With increasing the complexity of real-world problems, the more efficient and reliable optimization algorithms vital. Traditional methods are unable to solve these problems so, the first choice for solving these problems becomes meta-heuristic algorithms. Meta-heuristic algorithms proved their ability to solve more complex problems and giving more satisfying results. In this paper, we introduce the more popular meta-heuristic algorithms and their applications in addition to providing the more recent references for these algorithms.

scholarly journals Speed Proportional Integrative Derivative Controller: Optimization Functions in Metaheuristic Algorithms

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Luis Fernando de Mingo López ◽  
Francisco Serradilla García ◽  
José Eugenio Naranjo Hernández ◽  
Nuria Gómez Blas
Keyword(s):  
Pid Controller ◽  
Fitness Function ◽  
Optimization Algorithms ◽  
Metaheuristic Algorithms ◽  
Mathematical Background ◽  
Speed Controller ◽  
Search Optimization ◽  
Metaheuristic Search ◽  
Self Driving Cars ◽  
The Right

Recent advancements in computer science include some optimization models that have been developed and used in real applications. Some metaheuristic search/optimization algorithms have been tested to obtain optimal solutions to speed controller applications in self-driving cars. Some metaheuristic algorithms are based on social behaviour, resulting in several search models, functions, and parameters, and thus algorithm-specific strengths and weaknesses. The present paper proposes a fitness function on the basis of the mathematical description of proportional integrative derivate controllers showing that mean square error is not always the best measure when looking for a solution to the problem. The fitness developed in this paper contains features and equations from the mathematical background of proportional integrative derivative controllers to calculate the best performance of the system. Such results are applied to quantitatively evaluate the performance of twenty-one optimization algorithms. Furthermore, improved versions of the fitness function are considered, in order to investigate which aspects are enhanced by applying the optimization algorithms. Results show that the right fitness function is a key point to get a good performance, regardless of the chosen algorithm. The aim of this paper is to present a novel objective function to carry out optimizations of the gains of a PID controller, using several computational intelligence techniques to perform the optimizations. The result of these optimizations will demonstrate the improved efficiency of the selected control schema.

scholarly journals A Thematic-Analytical Review of Knowledge Production Culture in Architectural Design

2020 ◽  
Author(s):  
Alireza Kharazmi-Nezhad ◽  
Nesip Ömer Erem
Keyword(s):  
Content Analysis ◽  
Production Process ◽  
Design Process ◽  
Knowledge Production ◽  
Architectural Design ◽  
Relevant Literature ◽  
Computer Application ◽  
Design Studies ◽  
Young Culture ◽  
Analytical Review

Architectural design, whether as a knowledge production process or as a ‘means’ for producing knowledge, has been the hot topic of theoretical debates since the late 1990s. Despite the developments, it requires more clarity as a young culture in the discipline. This research aims at deciphering the theoretical body to identify and bring the central themes into sight and provide a legible interpretation of knowledge production in architectural design. To this end, a unique methodology, adopted form content analysis, has been utilized. In this paper, a piece of the relevant literature was analysed by a computer application namely NVivo. The analysis has revealed a set of words from which the central themes are extracted. Out of thirty emphatic words, ten central themes are generated. According to the findings, ‘design and research’, ‘design process and methods’, and ‘newness and novelty’ appeared to be the key themes when knowledge production in architecture matters. The remaining seven themes are mainly included in the key themes. The findings show that knowledge production in architectural design is much more influenced by the field of design studies rather than architecture. This study remarks that the objective and generic aspect of architecture is investigated for knowledge production, however, taking architecture-specific dimensions into account could bring new insights into the discipline.Az építészeti tervezés a tudástermelés folyamataként és „eszközeként” is az elméleti viták központi témája az 1990-es évek vége óta. Bár még fejlődésben van, a tudomány fiatal területeként szükség van arra, hogy fogalmait egyértelműbbé tegyék. E kutatás célja egy elméleti törzsanyag meghatározása, hogy a tudástermelés területe jól körülhatárolható legyen, célkitűzései láthatóvá, és fogalma értelmezhetővé váljon az építészeti tervezésben is. Ennek érdekében egyedülálló módszertan, formai tartalomelemzés alkalmazására került sor. A tanulmányban a vonatkozó szakirodalom egy részét az NVivo elnevezésű számítógépes alkalmazás segítségével elemeztük. Az elemzés gyakran ismételt szóhalmazokat gyűjtött, majd ezek alapján kivonatolta a szövegekben leggyakrabban előforduló témákat. A program harminc hangsúlyos szóból tíz központi témát generált. Az építészetre vonatkozó tudástermelés vizsgálata során a leggyakoribb találatok a „tervezés és kutatás”, a „tervezési folyamat és módszerek”, valamint az „újdonság és újszerűség” voltak. A többi hét témát nagyrészt magukba foglalták ezek a kulcstémák. A további eredmények azt mutatják, hogy az építészeti tervezésben megjelenő tudástermelésre nagyobb mértékben hatnak a tervezéselméleti stúdiumok, mint az építészeti gyakorlat. Noha jelen tanulmányunk az építészet objektív és általános aspektusát vizsgálja a tudástermelés szempontjából, e tudományágban később új fejezetet nyithatnak a kifejezetten építészeti szempontú megközelítések is.

Sign in / Sign up

Export Citation Format

Share Document