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Wyświetlanie 1-15 z 101
Tytuł:
Towards a distributed solution to multi-robot task allocation problem with energetic and spatiotemporal constraints
Autorzy:
Zitouni, Farouq
Harous, Saad
Maamri, Ramdane
Powiązania:
https://bibliotekanauki.pl/articles/305365.pdf
Data publikacji:
2020
Wydawca:
Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
Tematy:
multi-robot systems
multi-robot task allocation
energetic constraints
spatial constraints
temporal constraints
objective function
parallel distributed guided genetic algorithms
Opis:
This paper tackles the Multi-Robot Task Allocation problem. It consists of two distinct sets: a set of tasks (requiring resources), and a set of robots (offering resources). Then, the tasks are allocated to robots while optimizing a certain objective function subject to some constraints; e.g., allocating the maximum number of tasks, minimizing the distances traveled by the robots, etc. Previous works mainly optimized the temporal and spatial constraints, but no work focused on energetic constraints. Our main contribution is the introduction of energetic constraints on multi-robot task allocation problems. In addition, we propose an allocation method based on parallel distributed guided genetic algorithms and compare it to two state-of-the-art algorithms. The performed simulations and obtained results show the effectiveness and scalability of our solution, even in the case of a large number of robots and tasks. We believe that our contribution is applicable in many contemporary areas of research such as smart cities and related topics.
Źródło:
Computer Science; 2020, 21 (1); 3-24
1508-2806
2300-7036
Pojawia się w:
Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Multi-Objective Optimization of Traffic Signal Timing Using Non-Dominated Sorting Artificial Bee Colony Algorithm for Unsaturated Intersections
Autorzy:
Zhao, H.
He, R.
Su, J.
Powiązania:
https://bibliotekanauki.pl/articles/223879.pdf
Data publikacji:
2018
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
unsaturated intersection
multi-objective optimization
signal timing
artificial bee colony algorithm
vehicle delay
vehicle stops
Opis:
Vehicle delay and stops at intersections are considered targets for optimizing signal timing for an isolated intersection to overcome the limitations of the linear combination and single objective optimization method. A multi-objective optimization model of a fixed-time signal control parameter of unsaturated intersections is proposed under the constraint of the saturation level of approach and signal time range. The signal cycle and green time length of each phase were considered decision variables, and a non-dominated sorting artificial bee colony (ABC) algorithm was used to solve the multi-objective optimization model. A typical intersection in Lanzhou City was used for the case study. Experimental results showed that a single-objective optimization method degrades other objectives when the optimized objective reaches an optimal value. Moreover, a reasonable balance of vehicle delay and stops must be achieved to flexibly adjust the signal cycle in a reasonable range. The convergence is better in the non-dominated sorting ABC algorithm than in non-dominated sorting genetic algorithm II, Webster timing, and weighted combination methods. The proposed algorithm can solve the Pareto front of a multi-objective problem, thereby improving the vehicle delay and stops simultaneously.
Źródło:
Archives of Transport; 2018, 46, 2; 85-96
0866-9546
2300-8830
Pojawia się w:
Archives of Transport
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A novel multi-objective discrete particle swarm optimization with elitist perturbation for reconfiguration of ship power system
Autorzy:
Zhang, L.
Sun, J.
Guo, C.
Powiązania:
https://bibliotekanauki.pl/articles/260215.pdf
Data publikacji:
2017
Wydawca:
Politechnika Gdańska. Wydział Inżynierii Mechanicznej i Okrętownictwa
Tematy:
shipboard power system
reconfiguration
multi-objective
discrete PSO
elitist perturbation
Opis:
A novel multi-objective discrete particle swarm optimization with elitist perturbation strategy (EPSMODPSO) is proposed and applied to solve the reconfiguration problem of shipboard power system(SPS). The new algorithm uses the velocity to decide each particle to move one step toward positive or negative direction to update the position. An elitist perturbation strategy is proposed to improve the local search ability of the algorithm. Reconfiguration model of SPS is established with multiple objectives, and an inherent homogeneity index is adopted as the auxiliary estimating index. Test results of examples show that the proposed EPSMODPSO performs excellent in terms of diversity and convergence of the obtained Pareto optimal front. It is competent to solve network reconfiguration of shipboard power system and other multi-objective discrete optimization problems.
Źródło:
Polish Maritime Research; 2017, S 3; 79-85
1233-2585
Pojawia się w:
Polish Maritime Research
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Investigating multi-objective time, cost, and risk problems using the Grey Wolf Optimization algorithm
Autorzy:
Yilmaz, Mehmet
Dede, Tayfun
Grzywiński, Maksym
Powiązania:
https://bibliotekanauki.pl/articles/31342511.pdf
Data publikacji:
2023
Wydawca:
Politechnika Częstochowska
Tematy:
multi-objective optimization
grey wolf optimization algorithm
time-cost-risk
optymalizacja wielocelowa
algorytm optymalizacji szarego wilka
czas-koszt-ryzyko
Opis:
Safety plays a crucial role in construction projects. Safety risks encompass potential hazards such as work accidents, injuries, and security. Consequently, it is important to effectively manage these risks with equal emphasis on time and cost considerations during the project planning phase. Within the scope of this research, the grid and archive-based Grey Wolf Optimizer (GWO) algorithm was employed to investigate multi-objective time-cost-risk problems. By employing the GWO, multiple Pareto solutions were provided to the decisionmaker, facilitating improved decision-making. It was determined that the GWO algorithm yields better results in time-cost-risk problems compared to the Particle Swarm Optimization (PSO) and Differential Evolution (DE) algorithms.
Źródło:
Budownictwo o Zoptymalizowanym Potencjale Energetycznym; 2023, 12; 79-86
2299-8535
2544-963X
Pojawia się w:
Budownictwo o Zoptymalizowanym Potencjale Energetycznym
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Carpooling Scheme Selection for Taxi Carpooling Passengers: a Multi-Objective Model and Optimisation Algorithm
Autorzy:
Xiao, Q.
He, R.-C.
Powiązania:
https://bibliotekanauki.pl/articles/223987.pdf
Data publikacji:
2017
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
traffic engineering
taxi carpooling
multi-objective optimisation
information entropy
inżynieria ruchu
system carpooling
wspólne dojazdy
infrastruktura transportowa
optymalizacja
Opis:
Carpooling has been long deemed a promising approach to better utilizing existing transportation infrastructure, the carpooling system can alleviate the problems of traffic congestion and environmental pollution effectively in big cities. However, algorithmic and technical barriers inhibit the development of taxi carpooling, and it is still not the preferred mode of commute. In order to improve carpooling efficiency in urban, a taxi carpooling scheme based on multi-objective model and optimisation algorithm is presented. In this paper, urban traffic road network nodes were constructed from the perspective of passenger carpooling. A multi-objective taxi carpooling scheme selection model was built based on an analysis of the main influences of carpooling schemes on passengers. This model aimed to minimise get-on-and-get-off distance, carpooling waiting time and arriving at the destination. Furthermore, a two-phase algorithm was used to solve this model. A rapid searching algorithm for feasible routes was established, and the weight vector was assigned by introducing information entropy to obtain satisfying routes. The algorithm is applied to the urban road, the Simulation experimental result indicates that the optimisation method presented in this study is effective in taxi carpooling passengers.
Źródło:
Archives of Transport; 2017, 42, 2; 85-92
0866-9546
2300-8830
Pojawia się w:
Archives of Transport
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Tuning of a Fuzzy System for Controlling Searching Process In Multi Objective Scheduling Immune Algorithm
Autorzy:
Wosik, I.
Skołud, B.
Powiązania:
https://bibliotekanauki.pl/articles/971215.pdf
Data publikacji:
2009
Wydawca:
Wrocławska Rada Federacji Stowarzyszeń Naukowo-Technicznych
Tematy:
Immune Algorithm
multi objective optimization
fuzzy system
Opis:
In the paper the Multi Objective Immune Algorithm (MOIA) for an open job shop scheduling problem (OJSP) is proposed. The OJSP belongs to most both time consuming and most complicated problems in scope of searching space. In the paper schedules are evaluated by using three criteria: makespan, flowtime and total tardiness. MOIA proposes a schedule, which is best one, selected from a set of achieved solutions. An affinity threshold is a parameter that controls equilibrium between searching space and solutions diversity in MOIA. The affinity threshold is defined by using fuzzy logic system. In the paper fuzzy system is tuned by selecting shape, size of fuzzy sets, and fuzzy decisions of an affinity threshold. If the fuzzy system is used then neither the knowledge about the affinity threshold nor influence over searching processes is not required from a decision-maker. The application of the fuzzy system makes the process of decision-making user friendly. In the paper efficiency of MOIA before and after the fuzzy system tuning is compared and computational results are presented.
Źródło:
Journal of Machine Engineering; 2009, 9, 1; 130-143
1895-7595
2391-8071
Pojawia się w:
Journal of Machine Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
The scalarization approach for multi-objective optimization of network resource allocation in distributed systems
Autorzy:
Wesołowski, Z.
Powiązania:
https://bibliotekanauki.pl/articles/92817.pdf
Data publikacji:
2016
Wydawca:
Uniwersytet Przyrodniczo-Humanistyczny w Siedlcach
Tematy:
distributed system
resource allocation
multi-objective optimization
Opis:
The paper presents a multi-objective optimization framework to the network resource allocation problem, where the aim is to maximize the bitrates of data generated by all agents executed in a distributed system environment. In the proposed approach, the utility functions of agents may have different forms, which allows a more realistic modeling of phenomena occurring in computer networks. A scalarizing approach has been applied to solve the optimization problem.
Źródło:
Studia Informatica : systems and information technology; 2016, 1-2(20); 39-52
1731-2264
Pojawia się w:
Studia Informatica : systems and information technology
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Methods of universities investment potential improvement
Autorzy:
Vergun, Mykhailo O.
Powiązania:
https://bibliotekanauki.pl/articles/2157547.pdf
Data publikacji:
2014
Wydawca:
Instytut Studiów Międzynarodowych i Edukacji Humanum
Tematy:
higher education establishment
social and economic conditions of market economy
investment potential
factors of the development
multi-objective optimization
fixed assets
sources of financing
Opis:
The current article considers the issues of increasing the efficiency of processes of implementation of the investment potential of universities by optimizing sources of financing, taking into account the features of modern social and economic situation in Ukraine.
Źródło:
Społeczeństwo i Edukacja. Międzynarodowe Studia Humanistyczne; 2014, 3(15); 49-54
1898-0171
Pojawia się w:
Społeczeństwo i Edukacja. Międzynarodowe Studia Humanistyczne
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Milk runs model with overtime: application to cluster supply chain
Autorzy:
Tomczak, M.
Bucoń, R.
Powiązania:
https://bibliotekanauki.pl/articles/390975.pdf
Data publikacji:
2015
Wydawca:
Politechnika Lubelska. Wydawnictwo Politechniki Lubelskiej
Tematy:
cluster supply chain
mathematical programming
multi-objective optimization
small and medium enterprises
Opis:
Paper identifies obstacles limiting functioning and development of small and medium construction enterprises. It also includes a description of cluster supply chain (CSC) idea as a suggested solution to some of the problems resulting from the small scale of company activities. One of more important issues of every distribution centre, i.e. portions of deliveries smaller than truck capacity for particular consumers, is also discussed. This problem was formulated for the first time in dairy industry, therefore, it was called milk runs. Moreover, the authors of this paper presented the outcome analysis of survey carried out among construction engineers and managers. This study aimed at determining organizational principles for logistic centre working with CSC framework. The mathematical model depicting milk runs deliveries with overtime consideration, done for many construction sites within a distribution centre is presented hereunder. This model may be potentially used to optimize distribution centres working within cluster supply chain framework.
Źródło:
Budownictwo i Architektura; 2015, 14, 4; 139-147
1899-0665
Pojawia się w:
Budownictwo i Architektura
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Multi-objective coordination optimisation method for DGs and EVs in distribution networks
Autorzy:
Tang, Huiling
Wu, Jiekang
Powiązania:
https://bibliotekanauki.pl/articles/141087.pdf
Data publikacji:
2019
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
charging and discharging of electric vehicles
distribution networks
distributed generation
multi-objective coordination optimisation
SAPSO
Opis:
The loss of power and voltage can affect distribution networks that have a significant number of distributed power resources and electric vehicles. The present study focuses on a hybrid method to model multi-objective coordination optimisation problems for distributed power generation and charging and discharging of electric vehicles in a distribution system. An improved simulated annealing based particle swarm optimisation (SAPSO) algorithm is employed to solve the proposed multi-objective optimisation problem with two objective functions including the minimal power loss index and minimal voltage deviation index. The proposed method is simulated on IEEE 33-node distribution systems and IEEE-118 nodes large scale distribution systems to demonstrate the performance and effectiveness of the technique. The simulation results indicate that the power loss and node voltage deviation are significantly reduced via the coordination optimisation of the power of distributed generations and charging and discharging power of electric vehicles.With the methodology supposed in this paper, thousands of EVs can be accessed to the distribution network in a slow charging mode.
Źródło:
Archives of Electrical Engineering; 2019, 68, 1; 15-32
1427-4221
2300-2506
Pojawia się w:
Archives of Electrical Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Framework of an evolutionary multi-objective optimisation method for planning a safe trajectory for a marine autonomous surface ship
Autorzy:
Szłapczyński, Rafał
Ghaemi, Hossein
Powiązania:
https://bibliotekanauki.pl/articles/259121.pdf
Data publikacji:
2019
Wydawca:
Politechnika Gdańska. Wydział Inżynierii Mechanicznej i Okrętownictwa
Tematy:
maritime autonomous surface ships
evolutionary multi-objective optimisation
ship manoeuvres
fuel consumption
ship collision avoidance
Opis:
This paper represents the first stage of research into a multi-objective method of planning safe trajectories for marine autonomous surface ships (MASSs) involved in encounter situations. Our method applies an evolutionary multiobjective optimisation (EMO) approach to pursue three objectives: minimisation of the risk of collision, minimisation of fuel consumption due to collision avoidance manoeuvres, and minimisation of the extra time spent on collision avoidance manoeuvres. Until now, a fully multi-objective optimisation has not been applied to the real-time problem of planning safe trajectories; instead, this optimisation problem has usually been reduced to a single aggregated cost function covering all objectives. The aim is to develop a method of planning safe trajectories for MASSs that is able to simultaneously pursue the three abovementioned objectives, make decisions in real time and without interaction with a human operator, handle basic types of encounters (in open or restricted waters, and in good or restricted visibility) and guarantee compliance with the International Regulations for Preventing Collisions at Sea. It should also be mentioned that optimisation of the system based on each criterion may occur at the cost of the others, so a reasonable balance is applied here by means of a configurable trade-off. This is done throughout the EMO process by means of modified Pareto dominance rules and by using a multi-criteria decision-making phase to filter the output Pareto set and choose the final solution.
Źródło:
Polish Maritime Research; 2019, 4; 69-79
1233-2585
Pojawia się w:
Polish Maritime Research
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Multi-objective optimal reactive power dispatch to maximize power system social welfare in the presence of generalized unified power flow controller
Autorzy:
Suresh, C. V.
Sivanguraju, S.
Powiązania:
https://bibliotekanauki.pl/articles/141441.pdf
Data publikacji:
2015
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
generalized unified power flow controller
optimal reactive power dispatch
social welfare
multi-objective optimization
Opis:
In this paper a novel non-linear optimization problem is formulated to maximize the social welfare in restructured environment with generalized unified power flow controller (GUPFC). This paper presents a methodology to optimally allocate the reactive power by minimizing voltage deviation at load buses and total transmission power losses so as to maximize the social welfare. The conventional active power generation cost function is modified by combining costs of reactive power generated by the generators, shunt capacitors and total power losses to it. The formulated objectives are optimized individually and simultaneously as multi-objective optimization problem, while satisfying equality, in-equality, practical and device operational constraints. A new optimization method, based on two stage initialization and random distribution processes is proposed to test the effectiveness of the proposed approach on IEEE-30 bus system, and the detailed analysis is carried out.
Źródło:
Archives of Electrical Engineering; 2015, 64, 3; 405-426
1427-4221
2300-2506
Pojawia się w:
Archives of Electrical Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Multi-objective optimization with adjusted PSO method on example of cutting process of hardened 18CrMo4 steel
Optymalizacja wielokryterialna skorygowaną metodą PSO na przykładzie procesu skrawania stali 18CrMo4 w stanie zahartowanym
Autorzy:
Stryczek, R.
Pytlak, B.
Powiązania:
https://bibliotekanauki.pl/articles/1366141.pdf
Data publikacji:
2014
Wydawca:
Polska Akademia Nauk. Polskie Naukowo-Techniczne Towarzystwo Eksploatacyjne PAN
Tematy:
toczenie na twardo
metoda optymalizacji wielocząsteczkowej (PSO)
obliczenia ewolucyjne
optymalizacja wielokryterialna
entropia
hard turning
particle swarm optimization (PSO) method
evolutionary computations
multi-objective optimization
entropy
Opis:
W pracy zaproponowano zmodyfikowaną metodę optymalizacji wielocząsteczkowej (PSO) dla problemów optymalizacji wielokryterialnej z dyskretną przestrzenią decyzyjną. W metodzie PSO zmieniono sposób określania momentu bezwładności, współczynnika uczenia oraz współczynnika społecznego. Dodatkowo wprowadzono elitaryzm oraz innowacyjny mechanizm hamowania cząstek chroniący je przed przekraczaniem dopuszczalnych granic przestrzeni decyzyjnej. Zaproponowane podejście zostało zweryfikowane na szeregu aktualnych funkcjach testowych oraz problemie optymalizacji procesu skrawania stali 18CrMo4 w stanie zahartowanym, gdzie porównano je z wynikami uzyskanymi za pomocą algorytmów genetycznych (GA). Uzyskane wyniki wskazują, że zaproponowane podejście jest względnie szybkie i wysoce konkurencyjne w stosunku do innych metod optymalizacji. Autorzy uzyskali bardzo różnorodne, zbieżne i w pełnym zakresie przebiegi frontu Pareto w przestrzeni kryteriów. W celu oceny jakości wygenerowanego zbioru Pareto dla każdego z prezentowanych przykładów wyznaczono ocenę opartą na pomiarze entropii oraz wskaźnika jakości IGD.
In this paper a Modified Particle Swarm Optimization (PSO) method for multi-objective (MO) problems with a discrete decision space is proposed. In the PSO method the procedure to determine inertia weight, learning factor and social factor is modified. In addition, both an elitism strategy and innovative deceleration mechanism preventing the particles from going beyond the limits of decision space are introduced. The proposed approach has been applied to a series of currently used test functions as well as to optimization problems connected with finish hard turning operation, where the obtained results have been compared with those obtained by means of Genetic Algorithms (GA). The results indicate that the proposed approach is relatively quick, and thus it is highly competitive with other optimization methods. The authors have obtained a very good diversity, convergence and a maximum range of the Pareto front in the criteria space. In order to assess the quality of the generated Pareto set for each of presented examples, a rating has been determined based on the entropy measurement and inverted generational distance (IGD).
Źródło:
Eksploatacja i Niezawodność; 2014, 16, 2; 236-245
1507-2711
Pojawia się w:
Eksploatacja i Niezawodność
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Evolutionary multi–objective weather routing of sailboats
Autorzy:
Sobecka, Ewa
Szłapczyński, Rafał
Życzkowski, Marcin
Powiązania:
https://bibliotekanauki.pl/articles/1585076.pdf
Data publikacji:
2020
Wydawca:
Politechnika Gdańska. Wydział Inżynierii Mechanicznej i Okrętownictwa
Tematy:
sailing vessels
weather routing
evolutionary multi-objective optimization
weather forecasts
navigation
Opis:
The paper presents a multi-objective method, which optimises the route of a sailboat. The presented method makes use of an evolutionary multi-objective (EMO) algorithm, which performs the optimisation according to three objective functions: total passage time, a sum of all course alterations made during the voyage and the average angle of heel. The last two of the objective functions reflect the navigator’s and passenger’s comfort, which may decrease with multiple turns or when experiencing an excessive heel angle for a long time. The optimisation process takes into account static bathymetry-related constraints as well as dynamic constraints related to the sailboat’s safety in changing wind and wave conditions. The method makes use of all of the above and finally returns an approximated Pareto set containing non-dominated solutions to the optimisation problem. The developed method has been implemented as a simulation application. The paper includes selected simulation results followed by their discussion.
Źródło:
Polish Maritime Research; 2020, 3; 130-139
1233-2585
Pojawia się w:
Polish Maritime Research
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Generating a set of compromise solutions of a multi objective linear programming problem through game theory
Autorzy:
Sivri, Mustafa
Kocken, Hale Gonce
Albayrak, Inci
Akin, Sema
Powiązania:
https://bibliotekanauki.pl/articles/406253.pdf
Data publikacji:
2019
Wydawca:
Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
Tematy:
multi-objective programming problem
game theory
compromise solution
Opis:
Most of real-life problems, including design, optimization, scheduling and control, etc., are inherently characterized by multiple conflicting objectives, and thus multi-objective linear programming (MOLP) problems are frequently encountered in the literature. One of the biggest difficulties in solving MOLP problems lies in the trade-off among objectives. Since the optimal solution of one objective may lead other objective(s) to bad results, all objectives must be optimized simultaneously. Additionally, the obtained solution will not satisfy all the objectives in the same satisfaction degree. Thus, it will be useful to generate a set of compromise solutions in order to present it to the decision maker (DM). With this motivation, after determining a modified payoff matrix for MOLP, all possible ratios are formed between all rows. These ratio matrices are considered a two person zero-sum game and solved by linear programming (LP) approach. Taking into consideration the results of the related game, the original MOLP problem is converted to a single objective LP problem. Since there exist numerous ratio matrices, a set of compromise solutions is obtained for MOLP problem. Numerical examples are used to demonstrate this approach.
Źródło:
Operations Research and Decisions; 2019, 29, 2; 77-88
2081-8858
2391-6060
Pojawia się w:
Operations Research and Decisions
Dostawca treści:
Biblioteka Nauki
Artykuł
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