Browsing by Subject "Tabu search"

Now showing 1 - 10 of 10

Open Access
Computation of the resonant frequency of electrically thin and thick rectangular microstrip antennas with the use of fuzzy inference systems
(John Wiley & Sons, 2000) Özer, Ş.; Güney, K.; Kaplan, A.
A new method for calculating the resonant frequency of electrically thin and thick rectangular microstrip antennas, based on the fuzzy inference systems, is presented. The optimum design parameters of the fuzzy inference systems are determined by using the classical, modified, and improved tabu search algorithms. The calculated resonant frequency results are in very good agreement with the experimental results reported elsewhere.
Open Access
Customer order scheduling problem: a comparative metaheuristics study
(Springer, 2007) Hazır, Ö.; Günalay, Y.; Erel, E.
The customer order scheduling problem (COSP) is defined as to determine the sequence of tasks to satisfy the demand of customers who order several types of products produced on a single machine. A setup is required whenever a product type is launched. The objective of the scheduling problem is to minimize the average customer order flow time. Since the customer order scheduling problem is known to be strongly NP-hard, we solve it using four major metaheuristics and compare the performance of these heuristics, namely, simulated annealing, genetic algorithms, tabu search, and ant colony optimization. These are selected to represent various characteristics of metaheuristics: nature-inspired vs. artificially created, population-based vs. local search, etc. A set of problems is generated to compare the solution quality and computational efforts of these heuristics. Results of the experimentation show that tabu search and ant colony perform better for large problems whereas simulated annealing performs best in small-size problems. Some conclusions are also drawn on the interactions between various problem parameters and the performance of the heuristics.
Open Access
Generating robust and stable schedules in a single machine environment
(IIE, 2004) Gören, Selçuk; Sabuncuoğlu, İhsan
Scheduling is a decision making process that concerns with allocation of limited resources (machines, material handling equipment, operators, tools, etc.) to competing tasks (operations of jobs) over time with the goal of optimizing one or more objectives. The output of this process is time/machine/operation assignments. In the scheduling theory, the objective is generally to optimize one or more regular performance measures such as makespan, flow-time, and tardiness. Recently, two new measures have been also used in scheduling applications: "robustness" and "stability". In this paper, we develop a new surrogate measure to achieve robustness and stability. This measure is embedded in a tabu search algorithm to generate schedules in a single machine environment subject to random machine breakdowns. The results of extensive computational experiments indicate that the proposed method performs better than the average slack method used in the literature.
Open Access
A joint production and transportation planning problem with heterogeneous vehicles
(2014) Toptal, A.; Koc, U.; Sabuncuoglu, I.
We consider a manufacturer's planning problem to schedule order production and transportation to respective destinations. The manufacturer in this setting can use two vehicle types for outbound shipments. The first type is available in unlimited numbers. The availability of the second type, which is less expensive, changes over time. Motivated by some industry practices, we present formulations for three different solution approaches: the myopic solution, the hierarchical solution and the coordinated solution. These approaches vary in how the underlying production and transportation subproblems are solved, that is, sequentially versus jointly or heuristically versus optimally. We provide intractability proofs or polynomial-time exact solution procedures for the sub-problems and their special cases. We also compare the three solution approaches over a numerical study to quantify the savings from integration and explicit consideration of transportation availabilities. Our analytical and numerical results set a foundation and a need for a heuristic to solve the integrated problem. We thus propose a tabu search heuristic, which quickly generates near-optimal solutions.
Open Access
A local search heuristic with self-tuning parameter for permutation flow-shop scheduling problem
(IEEE, 2009) Dengiz, B.; Alabaş-Uslu, Ç.; Sabuncuoğlu, İhsan
In this paper, a new local search metaheuristic is proposed for the permutation flow-shop scheduling problem. In general, metaheuristics are widely used to solve this problem due to its NP-completeness. Although these heuristics are quite effective to solve the problem, they suffer from the need to optimize parameters. The proposed heuristic, named STLS, has a single self-tuning parameter which is calculated and updated dynamically based on both the response surface information of the problem field and the performance measure of the method throughout the search process. Especially, application simplicity of the algorithm is attractive for the users. Results of the experimental study show that STLS generates high quality solutions and outperforms the basic tabu search, simulated annealing, and record-to-record travel algorithms which are well-known local search based metaheuristics.
Open Access
Robust optimization models for the dicrete time/cost trade-off problem
(Elsevier, 2011-03) Hazır, O.; Erel, E.; Günalay, Y.
Developing models and algorithms to generate robust project schedules that are less sensitive to disturbances are essential in today’s highly competitive uncertain project environments. This paper addresses robust scheduling in project environments; specifically, we address the discrete time/cost trade-off problem (DTCTP). We formulate the robust DTCTP with three alternative optimization models in which interval uncertainty is assumed for the unknown cost parameters. We develop exact and heuristic algorithms to solve these robust optimization models. Furthermore, we compare the schedules that have been generated with these models on the basis of schedule robustness. & 2010 Elsevier B.V. All rights reserved.
Open Access
Robustness and stability measures for scheduling: single-machine environment
(Taylor & Francis, 2008) Goren, S.; Sabuncuoglu, I.
This paper addresses the issue of finding robust and stable schedules with respect to random disruptions. Specifically, two surrogate measures for robustness and stability are developed. The proposed surrogate measures, which consider both busy and repair time distributions, are embedded in a tabu-search-based scheduling algorithm, which generates schedules in a single-machine environment subject to machine breakdowns. The performance of the proposed scheduling algorithm and the surrogate measures are tested under a wide range of experimental conditions. The results indicate that one of the proposed surrogate measures performs better than existing methods for the total tardiness and total flowtime criteria in a periodic scheduling environment. A comprehensive bibliography is also presented.
Open Access
Solving the hub location problem with modular link capacities
(Elsevier, 2005) Yaman, H.; Carello, G.
This paper deals with a capacitated hub location problem arising in the design of telecommunications networks. The problem is different from the classical hub location problem in two ways: the cost of using an edge is not linear but stepwise and the capacity of a hub restricts the amount of traffic transiting through the hub rather than the incoming traffic. In this paper both an exact and a heuristic method are presented. They are compared and combined in a heuristic concentration approach to investigate whether it is possible to improve the results within limited computational times.
Open Access
A tabu search algorithm for sparse placement of wavelength converters in optical networks
(Springer, 2004) Sengezer, N.; Karasan, E.
In this paper, we study the problem of placing limited number of wavelength converting nodes in a multi-fiber network with static traffic demands and propose a tabu search based heuristic algorithm. The objective of the algorithm is to achieve the performance of full wavelength conversion in terms of minimizing the total number of fibers used in the network by placing minimum number of wavelength converting nodes. We also present a greedy algorithm and compare its performance with the tabu search algorithm. Finally, we present numerical results that demonstrate the high correlation between placing a wavelength converting node and the amount of transit traffic passing through that node. © Springer-Verlag 2004.
Open Access
Wide area telecommunication network design: Application to the Alberta SuperNet
(2008) Cabral, E.A.; Erkut, E.; Laporte G.; Patterson, R.A.
This article proposes a solution methodology for the design of a wide area telecommunication network. This study is motivated by the Alberta SuperNet project, which provides broadband Internet access to 422 communities across Alberta. There are two components to this problem: the network design itself, consisting of selecting which links will be part of the solution and which nodes should house shelters; and the loading problem which consists of determining which signal transport technology should be installed on the selected edges of the network. Mathematical models are described for these two subproblems. A tabu search algorithm heuristic is developed and tested on randomly generated instances and on Alberta SuperNet data. © 2008 Operational Research Society Ltd. All rights reserved.