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EN
This study describes a pickup and delivery vehicle routing problem, considering time windows in reality. The problem of tractor truck routes is formulated by a mixed integer programming model. Besides this, three algorithms - a guided local search, a tabu search, and simulated annealing - are proposed as solutions. The aims of our study are to optimize the number of internal tractor trucks used, and create optimal routes in order to minimize total logistics costs, including the fixed and variable costs of an internal vehicle group and the renting cost of external vehicles. Besides, our study also evaluates both the quality of solutions and the time to find optimal solutions to select the best suitable algorithm for the real problem mentioned above. A novel mathematical model is formulated by OR tools for Python. Compared to the current solution, our results reduced total costs by 18%, increased the proportion of orders completed by internal vehicles (84%), and the proportion of orders delivered on time (100%). Our study provides a mathematical model with time constraints and large job volumes for a complex distribution network in reality. The proposed mathematical model provides effective solutions for making decisions at logistics companies. Furthermore, our study emphasizes that simulated annealing is a more suitable algorithm than the two others for this vehicle routing problem.
EN
A scheduling problem in considered on unrelated machines with the goal of total late work minimization, in which the late work of a job means the late units executed after its due date. Due to the NP-hardness of the problem, we propose two meta-heuristic algorithms to solve it, namely, a tabu search (TS) and a genetic algorithm (GA), both of which are equipped with the techniques of initialization, iteration, as well as termination. The performances of the designed algorithms are verified through computational experiments, where we show that the GA can produce better solutions but with a higher time consumption. Moreover, we also analyze the influence of problem parameters on the performances of these metaheuristics.
3
Content available Tabu Search Against Permutation Based Stream Ciphers
EN
Encryption is one of the most effective methods of securing data confidentiality, whether stored on hard drives or transferred (e.g. by e-mail or phone call). In this paper a new state recovery attack with tabu search is introduced. Based on research and theoretical approximation it is shown that the internal state can be recovered after checking 2⁵² internal states for RC4 and 2¹⁸⁰ for VMPC.
4
Content available Tabu search for the RNA partial degradation problem
EN
In recent years, a growing interest has been observed in research on RNA (ribonucleic acid), primarily due to the discovery of the role of RNA molecules in biological systems. They not only serve as templates in protein synthesis or as adapters in the translation process, but also influence and are involved in the regulation of gene expression. The RNA degradation process is now heavily studied as a potential source of such riboregulators. In this paper, we consider the so-called RNA partial degradation problem (RNA PDP). By solving this combinatorial problem, one can reconstruct a given RNA molecule, having as input the results of the biochemical analysis of its degradation, which possibly contain errors (false negatives or false positives). From the computational point of view the RNA PDP is strongly NP-hard. Hence, there is a need for developing algorithms that construct good suboptimal solutions. We propose a heuristic approach, in which two tabu search algorithms cooperate, in order to reconstruct an RNA molecule. Computational tests clearly demonstrate that the proposed approach fits well the biological problem and allows to achieve near-optimal results. The algorithm is freely available at http://www.cs.put.poznan.pl/arybarczyk/tabusearch.php.
EN
In recent years elastic optical networks have been perceived as a prospective choice for future optical networks due to better adjustment and utilization of optical resources than is the case with traditional wavelength division multiplexing networks. In the paper we investigate the elastic architecture as the communication network for distributed data centers. We address the problems of optimization of routing and spectrum assignment for large-scale computing systems based on an elastic optical architecture; particularly, we concentrate on anycast user to data center traffic optimization. We assume that computational resources of data centers are limited. For this offline problems we formulate the integer linear programming model and propose a few heuristics, including a meta-heuristic algorithm based on a tabu search method. We report computational results, presenting the quality of approximate solutions and efficiency of the proposed heuristics, and we also analyze and compare some data center allocation scenarios.
EN
Minimum Latency Problem (MLP) is a class of NP-hard combinatorial optimization problems which has many practical applications. In this paper, we investigate the global structure of the MLP solution space to propose a suitable meta-heuristic algorithm for the problem, which combines Tabu search (TS) and Variable Neighborhood Search (VNS). In the proposed algorithm, TS is used to prevent the search from getting trapped into cycles, and guide VNS to escape local optima. In a cooperative way, VNS is employed to generate diverse neighborhoods for TS. We also introduce a novel neighborhoods’ structure for VNS and present a constant time operation for calculating the latency cost of each neighboring solution. Extensive numerical experiments and comparisons with the state of the art meta-heuristic algorithms in the literature show that the proposed algorithm is highly competitive, providing the new best solutions for several instances.
EN
We consider a stochastic variant of the single machine total weighted tardiness problem jobs parameters are independent random variables with normal or Erlang distributions. Since even deterministic problem is NP-hard, it is difficult to find global optimum for large instances in the reasonable run time. Therefore, we propose tabu search metaheuristics in this work. Computational experiments show that solutions obtained by the stochastic version of metaheuristics are more stable (i.e. resistant to data disturbance) than solutions generated by classic, deterministic version of the algorithm.
PL
W artykule przedstawiono obecnie stosowane metody szeregowania zadań i harmonogramowania w budownictwie. Zaprezentowano przykładowe zadanie budowlane o charakterze deterministycznym, z którym borykać się może firma wykonawcza, podano jego rozwiązanie za pomocą algorytmu genetycznego i przeszukiwania tabu. Dokonano analizy i porównania uzyskanych wyników.
EN
The paper contains literature study for task sequencing methods and schedule optimization in construction. The author presents sample, determinative construction company problem. The sample problem is solved with the use of genetic algorithm and tabu search. Results are compared and analyzed.
EN
A comprehensive case study of manufacturing scheduling solutions development is given. It includes highly generalized scheduling problem as well as a few scheduling modes, methods and problem models. The considered problem combines flexible job shop structure, lot streaming with variable sublots, transport times, setup times, and machine calendars. Tabu search metaheuristic and constraint programming methods have been used for the off-line scheduling. Two dynamic scheduling methods have also been implemented, i.e., dispatching rules for the completely reactive scheduling and a multi-agent system for the predictivereactive scheduling. In these implementations three distinct models of the problem have been used, based on: graph representation, optimal constraint satisfaction, and Petri net formalism. Each of these solutions has been verified in computational experiments. The results are compared and some findings about advantages, disadvantages, and suggestions on using the solutions are formulated.
EN
The aim of this paper is to introduce a strategy to find a minimal set of test nodes for diagnostics of complex analog systems with single parametric faults using the support vector machine (SVM) classifier as a fault locator. The results of diagnostics of a video amplifier and a low-pass filter using tabu search along with genetic algorithms (GAs) as node selectors in conjunction with the SVM fault classifier are presented. General principles of the diagnostic procedure are first introduced, and then the proposed approach is discussed in detail. Diagnostic results confirm the usefulness of the method and its computational requirements. Conclusions on its wider applicability are provided as well.
EN
A SO(3) transformer of a three-plate polarizer is adopted to rapidly achieve the transformation of the polarized state. The polarization coding based on Stokes components S2 and S3 is analyzed and demonstrated. Tabu search algorithm is used to accelerate the transformation of the polarized state by utilizing Mueller matrix roots decomposition to decompose the SO(3) matrix, and substituting first order Taylor series approximations for the trigonometric functions in the SO(3) matrix. The results show that bias voltage is less than 120 V in the coding zone. The search speed of our algorithm is faster than the one without first order Taylor series approximations by 4 times.
EN
Computer-aided analysis and preprocessing of spectral data is a prerequisite for any study of molecular structures by Nuclear Magnetic Resonance (NMR) spectroscopy. The data processing stage usually involves a considerable dedication of time and expert knowledge to cope with peak picking, resonance signal assignment and calculation of structure parameters. A significant part of the latter step is performed in an automated way. However, in peak picking and resonance assignment a multistage manual assistance is still essential. The work presented here is focused on the theoretical modeling and analyzing the assignment problem by applying heuristic approaches to the NMR spectra recorded for RNA structures containing irregular regions.
13
Content available remote Using tabu search for feature selection in discriminant analysis
EN
The well known statistical software packages like STATISTICA [11] continue to use classic variable selection methods in stepwise Discriminant Analysis such as the sequential forward/backward ones. Such stepwise procedures suffer from the nesting effect. Moreover, due to the criterion used for evaluation of variable subsets they are designed for descriptive purposes, not for predictive ones. We propose the new solution to the mentioned problems, the feature selection algorithm based on metaheuristic tabu search. After performing some tests it is found that our tabu search-based algorithm obtains significantly better results than stepwise procedures of statistical package.
PL
W znanych szeroko pakietach do obliczeń statystycznych (np. STATISTICA [11]) selekcja zmiennych wejściowych w module krokowej Analizy Dyskryminacyjnej wykonywana jest z wykorzystaniem klasycznych metod sekwencyjnych w przód/w tył, których wadą jest efekt zagnieżdżania. Również kryterium ewaluacyjne w tychże metodach jest dostosowane do celów deskryptywnych, a nie predyktywnych. Artykuł proponuje nowe rozwiązania wspomnianych problemów – algorytm selekcji z wykorzystaniem metaheurystyki przeszukiwania z tabu. Wykonane, wstępne testy wykazały znacznie lepszą sprawność klasyfikacji w porównaniu z metodami krokowymi.
EN
Distributed Sensor Networks (DSNs) have attracted significant attention over the past few years. A growing list of many applications can employ DSNs for increased effectiveness especially in hostile and remote are as. In all application salargen umber of sensors are expected and requiring careful architecture and management of the net work. Grouping nodes in toclusters has been the most popular approach for support scalability in DSN. This paper proposes acluster based optimization of routing in DSN by employing a Bayesi an network (BN) with Tabu search (TS) approach. BN based approach is used to select efficient cluster head sand construction of BN for the proposed scheme. This approach in corporates energy level of each node, band width and link efficiency. The optimization of routing is considered as a design issue in DSN due to lack of energy consumption, delay and maximum time required for data transmission between source nodes (cluster heads) to sink node. In this work optimization of routing takes place through cluster head nodes by using TS. Simulations have been conducted to compare the performance of the proposed approach with LEACH protocol. The objective of the proposed work is to improve the performance of network in terms of energy consumption, through put, packet delivery ratio, and time efficiency of optimization of routing. The results hows that the proposed approach perform better than LEACH protocol that utilizes minimum energy, latency for cluster formation and reduce over head of the protocol.
EN
Automated Incident Detection (AID) is an important part of Advanced Traffic Management and Information Systems (ATMISs). An automated incident detection system can effectively provide information on an incident, which can help initiate the required measure to reduce the influence of the incident. To accurately detect incidents in expressways, a Support Vector Machine (SVM) is used in this paper. Since the selection of optimal parameters for the SVM can improve prediction accuracy, the tabu search algorithm is employed to optimize the SVM parameters. The proposed model is evaluated with data for two freeways in China. The results show that the tabu search algorithm can effectively provide better parameter values for the SVM, and SVM models outperform Artificial Neural Networks (ANNs) in freeway incident detection.
EN
To maintain patients at home as most as possible, healthcare services are nowadays quite diversified. We present the case of a public medical clinic offering activities, mostly to the elderly, at a daycare center. Users are brought into the daycare center by bus or by taxi. The global problem consists in defining routes to pick up users while assigning them to time slots in the week. At first sight this problem could be viewed as an asymmetric multiple vehicle routing problem. However many additional constraints must be considered. In this paper, we propose a metaheuristic including two phases to solve the problem. In the first phase, the initial solution is determined using one of two proposed constructed algorithms and is improved using tabu search in the second phase. These algorithms are tested on 10 problem instances. Experimental results are presented.
PL
W pracy rozpatrujemy problem harmonogramowania przedsięwzięć budowlanych realizowanych w systemie potokowym. Są to bardzo ważne zagadnienia praktyki budowlanej, mające znaczący i bezpośredni wpływ na ostateczne koszty realizacji. Przedstawiamy założenia do harmonogramowania robót, algorytm jego rozwiązywania opartego na metodzie przeszukiwania z tabu (ang. tabu search) oraz jego modyfikację dla przypadku, gdy niepewne są czasy wykonywania prac. Porównujemy stabilność rozwiązań w przypadku, gdy niepewne dane są reprezentowane przez zmienne losowe o rozkładzie normalnym lub liczby rozmyte w trzypunktowej reprezentacji.
EN
This paper deals with some problems of synchronizing construction activities differing in their execution times. The methodology of calculating the times of execution of the activities, ensuring that there will be no collisions between them, is presented. The methodology is illustrated with numerical examples showing the successive steps of the algorithm and it is applied to complex works modelled as the flow shop problem. The tabu search algorithm is adapted to solve the problem.
18
Content available remote Methods of using the Quadratic Assignment Problem solution
EN
Background: Quadratic assignment problem (QAP) is one of the most interesting of combinatorial optimization. Was presented by Koopman and Beckamanna in 1957, as a mathematical model of the location of indivisible tasks. This problem belongs to the class NP-hard issues. This forces the application to the solution already approximate methods for tasks with a small size (over 30). Even though it is much harder than other combinatorial optimization problems, it enjoys wide interest because it models the important class of decision problems. Material and methods: The discussion was an artificial intelligence tool that allowed to solve the problem QAP, among others are: genetic algorithms, Tabu Search, Branch and Bound. Results and conclusions: QAP did not arise directly as a model for certain actions, but he found its application in many areas. Examples of applications of the problem is: arrangement of buildings on the campus of the university, layout design of electronic components in systems with large scale integration (VLSI), design a hospital, arrangement of keys on the keyboard.
PL
Wstęp: Kwadratowy Problem Przydziału (QAP) jest jednym z najciekawszych zagadnień optymalizacji kombinatorycznej. Został przedstawiony przez Koopmana i Beckamanna w roku 1957, jako matematyczny model lokalizacji niepodzielnych zadań. Problem ten należy do klasy zagadnień NP.-trudnych. Wymusza to stosowanie do jego rozwiązania metod przybliżonych już dla zadań o niewielkim rozmiarze (powyżej 30). Mimo że jest ono znacznie trudniejsze niż inne zagadnienia optymalizacji kombinatorycznej, to cieszy się powszechnym zainteresowaniem, ponieważ modeluje ważną klasę problemów decyzyjnych. Metody: Dyskusji poddano narzędzia sztucznej inteligencji, które pozwoliły rozwiązać problem QAP, między innymi są to: algorytmy genetyczne, Tabu Search, Branch and Bound Wyniki i wnioski: Sam problem bezpośrednio nie powstał jako model pewnych działań, jednak znalazł on swoje zastosowanie w wielu dziedzinach. Przykładowymi zastosowaniami problemu jest: rozmieszczenie budynków na kampusie uczelnianym, projektowanie rozmieszczenia elementów elektronicznych w układach o wielkiej skali integracji (VLSI), projekt szpitala, rozmieszczenie klawiszy na klawiaturze.
EN
This paper concerns Directed Acyclic Graph task scheduling on parallel executors. The problem is solved using two new implementations of Tabu Search and genetic algorithm presented in the paper. A new approach to solution coding is also introduced and implemented in both metaheuristics algorithms. Results given by the algorithms are compared to those generated by greedy LPT and SS-FF algorithms; and HAR algorithm. The analysis of the obtained results of multistage simulation experiments confirms the conclusion that the proposed and implemented algorithms are characterized by very good performance and characteristics.
EN
The problem considered in this paper consists of planning and routing rail-truck intermodal shipments from a set of suppliers to a set of clients. The delivered quantities have to follow a truck-rail-truck intermodal path. There are three constraints to satisfy: the satisfaction of the demand is mandatory, each request should be delivered by its due date, and the capacity of a train cannot be exceeded. The objective function to minimize is a weighted summation of the cost and the risk. The former component concerns the fixed and variable transportation costs associated with trucks and trains, while the latter associated with dangerous goods is non-linear for trains. We propose a graph model to represent this problem and a tabu search metaheuristic to tackle it. Numerical experiments on realistic data are provided and discussed.
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