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1
Content available Logistic staff managment - ant algorithm for the optimal team creation
Schiff Krzysztof
Research in Logistics & Production
|
2019
|
Vol. 9, No. 1
49--59
EN
During daily logistic management managers often met difficult decision optimization problem concerning company staff. Such problems often rely on matching workers between them and team leader or matching worker to a place and a time slot and often they, menagers want to optimise their resources in order to receive such matches as maximum as possible as regars a cardinality number of a such set. These optimisation problem are often NP-difficults and to solve them menagers need special software tools. To aid managers in such situation artificial methods are used. Between artificials methods is a one called the ant colony optimisation algorithm and why in this article an ant colony optimization algorithm for the maximum cardinality 3-dimensional matching problem is described. The problem is modeled by means of 2-dimensional arrays. The elaborated ant algorithm was compared with another existing ant algorithm and tested for different values of ant algorithm parameters. Results of these tests were presented and discussed. The elaborated algorithm shows its superiority.
2
Content available An ant-based filtering random-finite-set approach to simultaneous localization and mapping
Li D., Zhu J., Xu B., Lu M., Li M.
International Journal of Applied Mathematics and Computer Science
|
2018
|
Vol. 28, no. 3
505--519
EN
Inspired by ant foraging, as well as modeling of the feature map and measurements as random finite sets, a novel formulation in an ant colony framework is proposed to jointly estimate the map and the vehicle trajectory so as to solve a feature-based simultaneous localization and mapping (SLAM) problem. This so-called ant-PHD-SLAM algorithm allows decomposing the recursion for the joint map-trajectory posterior density into a jointly propagated posterior density of the vehicle trajectory and the posterior density of the feature map conditioned on the vehicle trajectory. More specifically, an ant-PHD filter is proposed to jointly estimate the number of map features and their locations, namely, using the powerful search ability and collective cooperation of ants to complete the PHD-SLAM filter time prediction and data update process. Meanwhile, a novel fast moving ant estimator (F-MAE) is utilized to estimate the maneuvering vehicle trajectory. Evaluation and comparison using several numerical examples show a performance improvement over recently reported approaches. Moreover, the experimental results based on the robot operation system (ROS) platform validate the consistency with the results obtained from numerical simulations.
3
Content available Ant colony optimization applied to the problem of choosing the best combination among m combinations of shortest paths in transparent optical networks
Brasileiro Í, Santos I., Soares A., Rabêlo R., Mazullo F.
Journal of Artificial Intelligence and Soft Computing Research
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2016
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Vol. 6, No. 4
231--242
EN
This paper presents an attempt to solve the problem of choosing the best combination among the M combinations of shortest paths in optical translucent networks. Fixed routing algorithms demands a single route to each pair of nodes. The existence of multiple shortest paths to some pairs of nodes originates the problem of choose the shortest path which fits better the network requests. The algorithm proposed in this paper is an adaptation of Ant Colony Optimization (ACO) metaheuristic and attempt to define the set of routes that fits in an optimized way the network conditions, resulting in reduced number of blocked requests and better adjusted justice in route distribution. A performance evaluation is conducted in real topologies by simulations, and the proposed algorithm shows better performance between the compared algorithms.
4
Content available remote Real ant colony optimization as a tool for multi-criteria problems
Nowak I., Nowak G.
Computer Assisted Methods in Engineering and Science
|
2015
|
Vol. 22, no. 3
255--265
EN
This paper presents a population-based heuristic method – a real ant colony optimization (RACO) as a tool for multi-criteria optimization problems. The idea of multi-criteria optimization is discussed and the necessary modifications of RACO are proposed. These modifications made possible to use the method to simultaneously search many Pareto-optimal solutions. The method was numerically tested in problems of benchmark-type and used for solving simple engineering problems. This article presents and discusses all results obtained in tests, and two different approaches to multi-criteria optimization are additionally compared (search then decision and decision then search).
5
Algorytm mrówkowy w optymalizacji dyskretnych problemów nieliniowych
Krenich S.
Logistyka
|
2014
|
nr 6
6032-6040
PL
Artykuł prezentuje zastosowanie algorytmu mrówkowego w optymalizacji problemów o dyskretnym i nieliniowym charakterze. Algorytm mrówkowy zaliczany jest do grupy algorytmów rojowych, które są inspirowane zachowaniem stad lub rojów zwierząt, ptaków czy owadów podczas poszukiwania pożywienia czy przemieszczania się. Algorytmy te stosowane są głównie do rozwiązywania problemów opisanych za pomocą grafów i sieci. W niniejszej pracy przedstawiono modyfikację klasycznego algorytmu mrówkowego i jego przystosowanie do rozwiązywania zadań optymalizacji jednokryterialnej konstrukcji z ograniczeniami, które nie są modelowane jako grafy z wyraźnie zaznaczonymi węzłami i krawędziami przejść o określonym ściśle koszcie lub wartości drogi. Wprowadzono modyfikację w wyznaczaniu prawdopodobieństwa wyboru tzw. krawędzi przejścia oraz w obliczaniu wartości feromonu na tych krawędziach. Wartości te zależą nie tylko od liczby przejść sztucznych mrówek, ale także dodatkowo od dynamicznie ustalanej wartości pozostawianego przez mrówki feromonu. Eksperymenty przeprowadzono na dwóch przykładach dyskretnej optymalizacji sprzęgła wielopłytkowego oraz układu koncentrycznych sprężyn poddanych zmiennemu obciążeniu z wykorzystaniem zmodyfikowanego algorytmu mrówkowego oraz dodatkowo w celu porównania z wykorzystaniem algorytmu ewolucyjnego i losowego. Wyniki wskazują, iż algorytm mrówkowy może być efektywnym narzędziem w programowaniu dyskretnym.
EN
The paper presents an approach to design optimization for discrete and nonlinear problems using ant colony based algorithm. This algorithm belongs to the group of swarm algorithms inspired by behavior of birds, animals and bugs during their life or movement. Generally it is used for solving tasks which are modeled as grid or network problems. In the work a modification of the classical ant colony algorithm and its adaptation for problems that are not modeled as a network task with marked nodes and edges is described. New dependencies for dynamic calculating of pheromone on the edges and for probability of their choosing are introduced. Experiments were carried out for two examples of discrete optimization. The first one deals with the coupling system and the second one solves the set of concentric springs. Additionally, in order to compare generated optimal solutions, an evolutionary algorithm and a random search method are used. The obtained results indicate that the ant colony based algorithm can be an effective tool for discrete programming.
6
Content available remote Distribution Network Reconfiguration for Optimal Operation of Distributed Generation with Ant Colony Algorithm
Kasaei M. J.
Przegląd Elektrotechniczny
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2012
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R. 88, nr 12a
255-258
EN
This paper introduces one of applications of the Ant colony algorithm to solve the optimal network reconfiguration problem with Distributed Generation (DG) for power loss reduction and voltage profile improvement. DGs, such as fuel cells and solar cells, etc., are going to be installed in the demand side of power networks for reducing power losses, network reinforcement, improving network efficiency and reliability. Network reconfiguration is performed by altering the topological structure of distribution feeders. By reconfiguring the network, voltage stability can be maximized for a particular set of loads in distribution networks. The performance of the proposed method was investigated on two distribution networks consisting of 33 and 10 buses.
PL
W artykule przedstawiono algorytm optymalnej rekonfiguracji sieci dystrybucji energii, zawierającej rozproszone generatory energii, z wykorzystaniem algorytmu mrówkowego. Metoda wpływa na zmniejszenie strat mocy oraz wahań napięcia sieci. Weryfikację przeprowadzono na dwóch sieciach przesyłowych, zawierających 33 i 10 linii.
7
Content available An improved ant colony optimization algorithm and its application to text-independent speaker verification system
Aghdam M. H.
Journal of Artificial Intelligence and Soft Computing Research
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2012
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Vol. 2, No. 4
301--315
EN
With the growing trend toward remote security verification procedures for telephone banking, biometric security measures and similar applications, automatic speaker verification (ASV) has received a lot of attention in recent years. The complexity of ASV system and its verification time depends on the number of feature vectors, their dimensionality, the complexity of the speaker models and the number of speakers. In this paper, we concentrate on optimizing dimensionality of feature space by selecting relevant features. At present there are several methods for feature selection in ASV systems. To improve performance of ASV system we present another method that is based on ant colony optimization (ACO) algorithm. After feature selection phase, feature vectors are applied to a Gaussian mixture model universal background model (GMM-UBM) which is a text-independent speaker verification model. The performance of proposed algorithm is compared to the performance of genetic algorithm on the task of feature selection in TIMIT corpora. The results of experiments indicate that with the optimized feature set, the performance of the ASV system is improved. Moreover, the speed of verification is significantly increased since by use of ACO, number of features is reduced over 80% which consequently decrease the complexity of our ASV system.
8
Content available remote BA-TORA: a Multipath Routing Protocol for MANETs by Inspiration from Bee and Ant Colonies
Jamali S., Jahanbakhsh S.
Przegląd Elektrotechniczny
|
2011
|
R. 87, nr 7
183-187
EN
A mobile ad hoc network (MANET) consists of a set of mobile nodes which communicate over radio. One of the major challenging issues in this kind of networks is to develop an efficient routing protocol. Since MANET nodes have restricted battery capacity, an energy-aware routing protocol can play an important role in its performance. On the other hand, in recent years nature has been emerged as source of inspiration to successfully solve of many scientific problems. Hence in this paper we present BA-TORA, a TORA-based reactive multipath energy-aware routing protocol that has been inspired from bee and ant colonies. Simulation results show that BA-TORA outperforms TORA in terms of number of delivered packets, life time of network and life time of system.
PL
Sieci mobilne i ad-hoc MANET składają się z wielu ruchomych węzłów połączonych droga radiową. Dlatego bardzo ważna rolę odgrywa zastosowanie skutecznego protokołu transmisji. W sieciach MANET mogą być ograniczone pojemności baterii zasilających. W artykule zaprezentowano nowy protokół bazujący na protokole TORA inspirowany koloniami mrówek lub pszczół. Symulacje potwierdziły skuteczność protokołu opisywanego liczba przesłanych pakietów i czasem przesyłania.
9
Content available Metody sztucznej inteligencji w syntezie systemów typu kompleks zasobów i operacji
Drabowski M., Wantuch E.
Automatyka / Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie
|
2011
|
T. 15, z. 2
127-138
PL
Celem wysoko-poziomowej syntezy złożonych systemów przetwarzania, a także wytwarzania (systemów typu kompleks zasobów i operacji) jest znalezienie rozwiązania optymalnego, które dla przyjętych kryteriów optymalnosei będzie spełniało wymagania i ograniczenia narzucone przez zadaną specyfikację projektowanego systemu. Ponieważ problemy syntezy i ich optymalizacje są obliczeniowo NP-zupełne, zastosowano do ich rozwiązania wybrane metody sztucznej inteligencji i niektóre wyniki obliczeń tych metod są prezentowane w niniejszej pracy.
EN
The goal of this synthesis is to find an optimum solution satisfying the requirements and constraints enforced by the given specification of the system. The partition of the functions between hardware and software is the basic problem of synthesis. Such partition is significant, because every computer system must be realized as result of hardware implementation for its certain tasks. Due to the fact that synthesis problems and their optimizations are NP-complete we suggest meta-heuristic approaches.
10
Content available remote Ant Colony Optimization for Electrical Power System Expansion-Scheduling
Hadjeri S., Zeblah A.
Przegląd Elektrotechniczny
|
2008
|
R. 84, nr 7
36-42
EN
This paper uses an ant colony meta-heuristic optimization method to solve the multi-stage expansion problem for multi-state series-parallel systems. The study horizon is divided into several periods. At each period the demand distribution is forecasted in the form of a cumulative demand curve. A multiple-choice of additional components among a list of available product can be chosen and included into any subsystem component at any stage to improve the system performance. The components are characterized by their cost, performance (capacity) and availability. The objective is to minimize the whole investment-costs over the study period while satisfying availability or performance constraints. A universal generating function technique is applied to evaluate system availability. The ant colony approach is required to identify the optimal combination of adding components with different parameters to be allocated in parallel at each stage.
PL
W artykule omówiono metodę optymalizacji wykorzystującą algorytmy mrówkowe. Rozwiązywano problem wielopoziomowej rozbudowy szeregowo-równoległego system zasilania. Horyzont czasowy analizy został podzielony na mniejsze okresy. W każdym okresie potrzeby są prognozowane w postaci kumulacyjnej krzywej potrzeb. Różny wybór dodatkowych składowych systemu był możliwy na każdym etapie analizy. Te składowe były charakteryzowane przez koszt, możliwości i parametry. Celem była minimalizacja całkowitych kosztów inwestycji przy wymuszonych parametrach. Algorytm mrówkowy został wykorzystany do optymalizacji systemu na każdym etapie dodawania nowego elementu.
11
Content available Coherent synthesis of heterogeneous system - an ant colony optimization approach
Drabowski M.
Studia Informatica : systems and information technology
|
2007
|
Vol. 2(9)
9--18
EN
The paper presents an innovative approach to solving the problems of computer system synthesis based on ant colony optimization method. We describe algorithm realizations aimed to optimize resource, selection and task scheduling, as well as the adaptation of those algorithms for coherent synthesis realization. We then present selected analytical experiments proving the correctness of the coherent synthesis concept and indicate its practical motivations.
12
Content available remote Efficiency of selected meta-heuristics applied to the TSP problem: a simulation study
Kwaśnicka H.
TASK Quarterly : scientific bulletin of Academic Computer Centre in Gdansk
|
2003
|
Vol. 7, No 1
73-91
EN
The paper presents a simulation study of the usefulness of a numberof meta-heuristicsused as optimisation methods forTSPproblems. The five considered approaches are outlined: GeneticAlgorithm, Simulated Annealing, Ant Colony System, Tabu Search and Hopfield Neural Network.Using a purpose-developed computer program, efficiency of the meta-heuriticshas been studied andcompared. Results obtained from about 40000 simulation runs are briefly presented and discussed.
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