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1

Modern method based on artificial intelligence for safe control in the marine environment

Mohamed-Seghir Gdynia Maritime University, Gdynia, Poland

TransNav : International Journal on Marine Navigation and Safety of Sea Transportation

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2023

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Vol. 17 No. 2

283--288

EN

The article presents an approach to formulating a ship control process model in order to solve the problem of determining a safe ship trajectory in collision situations. Fuzzy process properties are included in the model to bring it closer to reality, as in many situations the navigator makes a subjective decision. A special neural network was used to solve the presented problem. This artificial neural network is characterized by minimum and maximum operations when set. In order to confirm the correctness of the operation of the proposed algorithm, the results of the simulations obtained were presented and an discussion was conducted.

2

Exact approaches to late work scheduling on unrelated machines

Liu Xinbo, Wang Wen, Chen Xin, Sterna Malgorzata, Blazewicz Jacek

International Journal of Applied Mathematics and Computer Science

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2023

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Vol. 33, no. 2

285--295

EN

We consider the scheduling problem on unrelated parallel machines in order to minimize the total late work. Since the problem is NP-hard, we propose a mathematical model and two dedicated exact approaches for solving it, based on the branching and bounding strategy and on enumerating combined with a dynamic programming algorithm. The time efficiencies of all three approaches are evaluated through computational experiments.

3

A boundary value problem for a non-linear difference equation

Lefebvre Mario

Archives of Control Sciences

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2023

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Vol. 33, No. 4

829--837

EN

A boundary value problem for a non-linear difference equation of order three is considered. We show that this equation can be interpreted as the equation satisfied by the value function in a stochastic optimal control problem. We thus obtain an expression for the solution of the non-linear difference equation that can be used to find an explicit solution to this equation. An example is presented.

4

Approximate method for redundancy allocation problem in multi-state series-parallel system

Zhang Hanxiao, Li Yan-Fu

Safety and Reliability of Systems and Processes

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2022

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Summer Safety and Reliability Seminar 2022

215--224

EN

Redundancy allocation problem (RAP) is one of the most important model of reliability optimization problems. In literature, there exist two typical formulations for RAP, namely 1) maximization of the system reliability under the resource constraints and 2) minimization of the system cost under system reliability and resource constraints. We propose an approximate method to solve MSSPS RAP under homogeneous and heterogeneous conditions under an absolute error. Numerical experiments are conducted on five published benchmarks and a new randomly generated instance with a larger number of subsystems. The approximated solutions exhibit good quality throughout the experiments.

5

Novel artificial intelligence-dynamic programming on infrared thermometer based on internet of things (IoT)

Boonsong Wasana

Przegląd Elektrotechniczny

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2022

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R. 98, nr 5

76--79

EN

According to the COVID-19 epidemic, the world has completely changed to new norm life. However, until 2022, people are still facing COVID-19 and its spreading and fast infection to the human body. Healthcare workers are on the front lines and are at higher risk of contracting COVID-19 than other occupations because they must be in close contact with the patient who risks virus diseases. The paper proposes the novel artificial intelligence (AI)-dynamic programming algorithm on infrared Thermometer based on the Internet of things (IoT) to support the medical personnel. The proposed novel thermometer is divided into three main sections, which are 1) Temperature sensing device, 2) Embedded dynamic programming algorithm, and 3) IoT communication platform. The innovation was designed using dynamic programming algorithm embedment, reducing complex and repetitive processing errors and fast computation. Moreover, it was tested according to the research methodology way. The temperatures were collected within the controlled condition test of time, environment condition, and same body organ of volunteer according to the various distances. The experimental results came out with three classified zones: best, moderate, and ineffective spaces. In addition, the discussions were also included about the complication factors about sensor's accuracy detection, such as angle detection, target distance, and focusing of wireless infrared Thermometer.

PL

Według epidemii COVID-19 świat całkowicie zmienił się w nowe, normalne życie. Jednak do 2022 r. ludzie nadal stoją w obliczu COVID-19 oraz jego rozprzestrzeniania się i szybkiej infekcji w ludzkim ciele. Pracownicy służby zdrowia znajdują się na pierwszej linii frontu i są bardziej narażeni na zarażenie się COVID-19 niż w innych zawodach, ponieważ muszą być w bliskim kontakcie z pacjentem zagrożonym chorobami wirusowymi. W artykule zaproponowano nowatorski algorytm sztucznej inteligencji (AI)-dynamicznego programowania termometru na podczerwień w oparciu o Internet rzeczy (IoT) w celu wsparcia personelu medycznego. Proponowany nowatorski termometr jest podzielony na trzy główne sekcje, którymi są 1) urządzenie do pomiaru temperatury, 2) wbudowany algorytm programowania dynamicznego oraz 3) platforma komunikacyjna IoT. Innowacja została zaprojektowana z wykorzystaniem dynamicznego osadzenia algorytmu programowania, redukującego złożone i powtarzalne błędy przetwarzania oraz szybkie obliczenia. Ponadto został przetestowany zgodnie z metodologią badawczą. Temperatury zbierano w ramach kontrolowanego testu warunków czasu, warunków środowiska i tego samego organu ciała ochotnika w zależności od różnych odległości. Wyniki eksperymentalne przyniosły trzy sklasyfikowane strefy: najlepsze, umiarkowane i nieefektywne przestrzenie. Ponadto dyskutowano również na temat czynników komplikacji związanych z wykrywaniem dokładności czujnika, takich jak wykrywanie kąta, odległość celu i ogniskowanie bezprzewodowego termometru na podczerwień.

6

Sustainable supply chains modeling

Pupavac Drago

LogForum

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2022

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Vol. 18, no. 4

471--480

EN

Background: Although existing studies have highlighted the importance of modeling sustainable supply chains, there is a scarcity of research that integrates environmental, social, and economic dimensions simultaneously. Accordingly, this paper aims to explore the possibilities of creating and modeling sustainable supply chains in the trefoil of economic, environmental, and social sustainability. Methods: For creating and modeling optimal sustainable supply chains, we used the mathematical method of dynamic programming. The method of dynamic programming was chosen for the reason that dynamic programming represents a set of special mathematical methods that serve to optimize multi-stage or multi-phase processes. Results: Minimum costs of the supply chain in the given example are achieved when the problem is solved from an economic perspective or from the perspective of total costs. Solving the problem from an ecological or social perspective increases the costs of the supply chain compared to optimal solutions, by 16.05% if the problem is solved from an ecological perspective and by 14.31% if the problem is solved from a social perspective. Conclusions: Contemporary sustainable supply chains are forced to include in their logistics network only those participants who can satisfy the principles of integral sustainability, i.e. respecting the economic, ecological and social dimensions.

7

The dynamic programming model for optimal allocation of laden shipping containers to Nigerian seaports

Amuji Harrison O., Onwuegbuchunam Donatus E., Aponjolosun Moses O., Okeke Kenneth O., Mbachu Justice C., Ojutalayo John F.

Journal of Sustainable Development of Transport and Logistics

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2022

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Vol. 7, No. 2

69--79

EN

In highly competitive shipping market environment, container network operators-Freight forwarders, shipping companies etc. are concerned about design, development and deployment of optimized allocation model to achieve cost savings through improved container storage yard operations, crane productivity, outbound container allocation/distribution to seaport terminals and hence reduction in ships’ waiting times. In this paper, we developed two models, the Dynamic programming model and optimal allocation policy (model), for the optimal allocation of units of outbound laden cargo containers of sizes: 20ft and 40ft to six (6) major seaports in Nigeria. The distributions of the laden containers were allocated as follows: Port-Harcourt, Tincan Island, Onne, and Calabar seaports were allocated with 1,064 units of stuffed containers each. Apapa seaport was allocated with 2,128 units of laden containers, and zero allocation was made to Warri seaport. These results were arrived at through the implementation of the optimal allocation policy. The zero units allocation made to Warri seaport could be attributed to poor shipper patronage and hence the low frequency of ship visits. Apapa seaport was allocated double the number of containers moved to the remaining ports because it attracted more shipper patronage and hence more ship visits. Hence, freight forwarding companies will be assured of cargo spaces and make more profit by allocating more containers. Policy implications of the developed models were discussed.

8

Computing power indices for weighted voting games via dynamic programming

Staudacher Jochen, Kóczy László Á., Stach Izabella, Filipp Jan, Kramer Marcus, Noffke Till, Olsson Linuss, Pichler Jonas, Singer Tobias

Operations Research and Decisions

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2021

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Vol. 31, No. 2

123--145

EN

We study the efficient computation of power indices for weighted voting games using the paradigm of dynamic programming. We survey the state-of-the-art algorithms for computing the Banzhaf and Shapley–Shubik indices and point out how these approaches carry over to related power indices. Within a unified framework, we present new efficient algorithms for the Public Good index and a recently proposed power index based on minimal winning coalitions of the smallest size, as well as a very first method for computing the Johnston indices for weighted voting games efficiently. We introduce a software package providing fast C++ implementations of all the power indices mentioned in this article, discuss computing times, as well as storage requirements.

9

Optimal transmission expansion planning considering distributed generations by using non-dominated sorting genetic algorithm-II (NSGAII)

Kamarposhti Mehrdad Ahmadi, Kabalci Ersan

Journal of Power Technologies

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2021

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Vol. 101, nr 1

70--77

EN

Reconstructing power systems has changed the traditional planning of power systems and has raised new challenges in Transmission Expansion Planning (TEP). Because of these reason, new methods and criteria have been formed for planning transmission in reconstructed environments. Thus, a dynamic programming was used for transmission efficiency based on multi-objective optimization in this research. In this model, investment cost, cost of density and dependability have been considered three objectives of optimization. In this paper, NSGAII multi-objective genetic algorithm was used to solve this non-convex and mixed integer problem. A fuzzy decision method has been used to choose the final optimal answer from the Pareto solutions obtained from NSGAII. Moreover, to confirm the efficiency of NSGAII multi-objective genetic algorithm in solving TEP problem, this algorithm was implemented in an IEEE 24 bus system and the gained results were compared with previous works in this field.

10

Optimization of rule-based energy management strategies for hybrid vehicles using dynamic programming

Zhu Di, Pritchard Ewan, Dadam Sumanth Reddy, Kumar Vivek, Xu Yang

Combustion Engines

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2021

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R. 60, nr 1

3--10

EN

Reducing energy consumption is a key focus for hybrid electric vehicle (HEV) development. The popular vehicle dynamic model used in many energy management optimization studies does not capture the vehicle dynamics that the in-vehicle measurement system does. However, feedback from the measurement system is what the vehicle controller actually uses to manage energy consumption. Therefore, the optimization solely using the model does not represent what the vehicle controller sees in the vehicle. This paper reports the utility factor-weighted energy consumption using a rule-based strategy under a real-world representative drive cycle. In addition, the vehicle test data was used to perform the optimization approach. By comparing results from both rule-based and optimization-based strategies, the areas for further improving rule-based strategy are discussed. Furthermore, recent development of OBD raises a concern about the increase of energy consumption. This paper investigates the energy consumption increase with extensive OBD usage.

11

On the weightedk-path vertex cover on interval graphs

Zygadło Jakub

Schedae Informaticae

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2020

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Vol. 29

9--21

EN

We consider a version of the k-path vertex cover problem that asks for the minimum weight subset C of vertices of a graph G such that every path on k vertices in G has at least one vertex in common with C. We present two dynamic algorithms solving this problem on interval graphs. The first one works on general interval graphs but is in practice limited to small values of k. The second algorithm computes minimum weight vertex cover for arbitrary k on proper interval graph G = (V,E) in time O(|V|^2|E|).

12

The load torque influence on time-optimal position control process

Andrzejewski Andrzej

Przegląd Elektrotechniczny

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2020

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R. 96, nr 1

142--145

EN

The contribution of the paper is the theoretical development and obtaining the time-optimal position control process in conditions of heavy loading of the servo motor as a result of simulation tests. The influence of passive load torque and active load torque on the position controller output signal generation in its active state is described mathematically.

PL

Wkładem pracy jest opracowanie teoretyczne oraz uzyskanie optymalno-czasowego procesu regulacji położenia w warunkach silnego obciążenia silnika serwo w wyniku badań symulacyjnych. Opisano matematycznie wpływ pasywnego momentu obciążenia oraz aktywnego momentu obciążenia na sposób generowania sygnału wyjściowego regulatora położenia w jego stanie aktywnym.

13

Map Matching Algorithm Based on Dynamic Programming Approach

Yumaganov Alexander, Agafonov Anton, Myasnikov Vladislav

Annals of Computer Science and Information Systems

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2020

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Vol. 21

563--566

EN

GPS sensors embedded in almost all mobile devices and vehicles generate a large amount of data that can be used in both practical applications and transportation research. Despite the high accuracy of location measurements in 3-5 meters on average, this data can not be used for practical use without preprocessing. The preprocessing step that is needed to identify the correct path as a sequence of road segments by a series of location measurements and road network data is called map matching. In this paper, we consider the offline map matching problem in which the whole trajectory is processed after it has been collected. We propose a map matching algorithm based on a dynamic programming approach. The experimental studies on the dataset collected in Samara, Russia, showed that the proposed algorithm outperforms other comparable algorithms in terms of accuracy.

14

Time-optimal position control of DC motor servo drive

Andrzejewski Andrzej

Przegląd Elektrotechniczny

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2019

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R. 95, nr 12

85--88

EN

Time optimal position control method is obtained differently on the basis of position, speed and motor current responses to DC motor voltage steps by applying dynamic programming method. As the result, the position overshoot and chattering is completely eliminated.

PL

Metodę optymalno-czasowej regulacji położenia uzyskano inaczej czyli na podstawie odpowiedzi położenia, prędkości oraz prądu silnika DC po skokowej zmianie napięcia DC zasilającego silnik prądu stałego oraz stosując metodę programowania dynamicznego. W rezultacie całkowicie wyeliminowano przeregulowanie położenia oraz zjawisko zwane „chattering”.

15

Expansion-based QBF Solving on Tree Decompositions

Charwat Günther, Woltran Stefan

Fundamenta Informaticae

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2019

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Vol. 167, nr 1-2

59--92

EN

In recent years various approaches for quantified Boolean formula (QBF) solving have been developed, including methods based on expansion, skolemization and search. Here, we present a novel expansion-based solving technique that is motivated by concepts from the area of parameterized complexity. Our approach relies on dynamic programming over the tree decomposition of QBFs in prenex conjunctive normal form (PCNF). Hereby, binary decision diagrams (BDDs) are used for compactly storing partial solutions. Towards efficiency in practice, we integrate dependency schemes and develop dedicated heuristic strategies. Our experimental evaluation reveals that our implementation is competitive to state-of-the-art solvers on instances with one quantifier alternation. Furthermore, it performs particularly well on instances up to a treewidth of approximately 80, even for more quantifier alternations. Results indicate that our approach is orthogonal to existing techniques, with a large number of uniquely solved instances.

16

Comparison of Heuristics for Optimization of Association Rules

Alsolami Fawaz, Amin Talha, Moshkov Mikhail, Zielosko Beata, Żabiński Krzysztof

Fundamenta Informaticae

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2019

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Vol. 166, nr 1

1--14

EN

In this paper, seven greedy heuristics for construction of association rules are compared from the point of view of the length and coverage of constructed rules. The obtained rules are compared also with optimal ones constructed by dynamic programming algorithms. The average relative difference between length of rules constructed by the best heuristic and minimum length of rules is at most 4%. The same situation is with coverage.

17

Memoization method for storing of minimum-weight triangulation of a convex polygon

Selimi Aybeyan, Krrabaj Samedin, Saracevic Muzafer, Pepić Selver

Computer Science

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2019

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Vol. 20 (2)

195--211

EN

This study presents a practical view of dynamic programming, specifically in the context of the application of finding the optimal solutions for the polygon triangulation problem. The problem of the optimal triangulation of polygon is considered to be as a recursive substructure. The basic idea of the constructed method lies in finding to an adequate way for a rapid generation of optimal triangulations and storing - them in as small as possible memory space. The upgraded method is based on a memoization technique, and its emphasis is in storing the results of the calculated values and returning the cached result when the same values again occur. The significance of the method is in the generation of the optimal triangulation for a large number of n. All the calculated weights in the triangulation process are stored and performed in the same table. Results processing and implementation of the method was carried out in the Java environment and the experimental results were compared with the square matrix and Hurtado-Noy method.

18

The LQG homing problem for a Wiener process with random infinitesimal parameters

Lefebvre Mario, Moutassim Abderrazak

Archives of Control Sciences

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2019

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Vol. 29, No. 3

413--422

EN

The problem of optimally controlling a Wiener process until it leaves an interval (a, b) for the first time is considered in the case when the infinitesimal parameters of the process are random. When a = -∞, the exact optimal control is derived by solving the appropriate system of differential equations, whereas a very precise approximate solution in the form of a polynomial is obtained in the two-barrier case.

19

Parallel cache-efficient code for computing the McCaskill partition functions

Palkowski Marek, Bielecki Wlodzimierz

Annals of Computer Science and Information Systems

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2019

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Vol. 18

207--210

EN

We present parallel tiled optimized McCaskill's partition functions computation code. That CPU and memory intensive dynamic programming task is within computational biology. To optimize code, we use the authorial source-to-source TRACO compiler and compare obtained code performance with that generated with the state-of-the-art PluTo compiler based on the affine transformations framework (ATF). For the considered task, PluTo is able to generate only serial highly cache efficient code without any parallelism. A TRACO tiling and parallelizing strategy uses the transitive closure of a dependence graph to avoid affine function calculation. First, for each loop nest statement, rectangular tiles are formed. Then those tiles are corrected to be valid under lexicographical order if necessary. A correction is carried out by means of applying transitive closure. The validity of tiles guarantees that the inter-tile dependence graph is acyclic. So, a valid schedule for target tiles can be derived and applied to generate parallel tiled code. For this purpose, the ISL scheduler is used. An experimental study carried out on a multi-core computer demonstrates considerable speed-up of generated code for the larger number of threads. Generated parallel tiled code overcomes that generated with the PluTo compiler.

20

Reference Abstract Domains and Applications to String Analysis

Amadini R., Gange G., Gauthier F., Jordan A., Schachte P., Søndergaard H., Stuckey P. J., Zhang C.

Fundamenta Informaticae

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2018

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Vol. 158, nr 4

297--326

EN

Abstract interpretation is a well established theory that supports reasoning about the run-time behaviour of programs. It achieves tractable reasoning by considering abstractions of run-time states, rather than the states themselves. The chosen set of abstractions is referred to as the abstract domain. We develop a novel framework for combining (a possibly large number of) abstract domains. It achieves the effect of the so-called reduced product without requiring a quadratic number of functions to translate information among abstract domains. A central notion is a reference domain, a medium for information exchange. Our approach suggests a novel and simpler way to manage the integration of large numbers of abstract domains. We instantiate our framework in the context of string analysis. Browser-embedded dynamic programming languages such as JavaScript and PHP encourage the use of strings as a universal data type for both code and data values. The ensuing vulnerabilities have made string analysis a focus of much recent research. String analysis tends to combine many elementary string abstract domains, each designed to capture a specific aspect of strings. For this instance the set of regular languages, while too expensive to use directly for analysis, provides an attractive reference domain, enabling the efficient simulation of reduced products of multiple string abstract domains.