Browsing by Subject "Heuristic methods"

Now showing 1 - 20 of 47

Open Access
An analysis of heuristics in a dynamic job shop with weighted tardiness objectives
(Taylor & Francis, 1999) Kutanoglu, E.; Sabuncuoğlu, İ.
Meeting due dates as a reflection of customer satisfaction is one of the scheduling criteria that is frequently encountered in today's manufacturing environments. The natural quantification of this qualitative goal involves tardiness related measures. In this study, we consider the dynamic job shop scheduling problem with the weighted tardiness criterion. After we present a comprehensive literature survey on the topic, we measure the long-run performances of more than 20 single-pass dispatching rules under various experimental conditions. In this study, we pay special attention to recently proposed dispatching heuristics such as CEXSPT, CR+ SPT, S/RPT+ SPT, and Bottleneck Dynamics (BD). We also investigate the effects of six resource pricing schemes proposed recently for BD. Moreover, we extend the earlier versions of inserted idleness and identify the conditions in which these techniques can be applied without incurring too much computational cost. Future research directions are also outlined in light of the computational results. © 1999 Taylor & Francis Ltd.
Open Access
Analysis of Lagrangian lower bounds for a graph partitioning problem
(Institute for Operations Research and the Management Sciences (INFORMS), 1999) Adil, G. K.; Ghosh, J. B.
Recently, Ahmadi and Tang (1991) demonstrated how various manufacturing problems can be modeled and solved as graph partitioning problems. They use Lagrangian relaxation of two different mixed integer programming formulations to obtain both heuristic solutions and lower bounds on optimal solution values. In this note, we point to certain inconsistencies in the reported results. Among other things, we show analytically that the first bound proposed is trivial (i.e., it can never have a value greater than zero) while the second is also trivial for certain sparse graphs. We also present limited empirical results on the behavior of this second bound as a function of graph density.
Open Access
Approximations in compensator design: a duality
(The Institution of Engineering and Technology (IET), 2002) Özgüler, A. B.; Gündeş, A. N.
In classical controller design, poles fat to the left of dominant poles are sometimes ignored. Similarly, in some proportional-integral compensation techniques, the controller zero is placed close to the origin and design proceeds after cancelling this zero with a pole at the origin. A rigorous basis for these methods is provided, it being shown that there is a duality between the two.
Open Access
An archiving model for a hierarchical information storage environment
(Elsevier, 2000) Moinzadeh, K.; Berk, E.
We consider an archiving model for a database consisting of secondary and tertiary storage devices in which the query rate for a record declines as it ages. We propose a `dynamic' archiving policy based on the number of records and the age of the records in the secondary device. We analyze the cases when the number of new records inserted in the system over time are either constant or follow a Poisson process. For both scenarios, we characterize the properties of the policy parameters and provide optimization results when the objective is to minimize the average record retrieval times. Furthermore, we propose a simple heuristic method for obtaining near-optimal policies in large databases when the record query rate declines exponentially with time. The e ectiveness of the heuristic is tested via a numerical experiment. Finally, we examine the behavior of performance measures such as the average record retrieval time and the hit rate as system parameters are varied.
Open Access
Assembly line balancing using genetic algorithms
(Kluwer Academic Publishers, 2000) Sabuncuoğlu İ.; Erel, E.; Tanyer, M.
Assembly Line Balancing (ALB) is one of the important problems of production/operations management area. As small improvements in the performance of the system can lead to significant monetary consequences, it is of utmost importance to develop practical solution procedures that yield high-quality design decisions with minimal computational requirements. Due to the NP-hard nature of the ALB problem, heuristics are generally used to solve real life problems. In this paper, we propose an efficient heuristic to solve the deterministic and single-model ALB problem. The proposed heuristic is a Genetic Algorithm (GA) with a special chromosome structure that is partitioned dynamically through the evolution process. Elitism is also implemented in the model by using some concepts of Simulated Annealing (SA). In this context, the proposed approach can be viewed as a unified framework which combines several new concepts of AI in the algorithmic design. Our computational experiments with the proposed algorithm indicate that it outperforms the existing heuristics on several test problems.
Open Access
A beam search algorithm to optimize robustness under random machine breakdowns and processing time variability
(Institute of Industrial Engineers, 2007) Gören, S.; Sabuncuoğlu, İhsan
The vast majority of the machine scheduling research assumes complete information about the scheduling problem and a static environment in which scheduling systems operate. In practice, however, scheduling systems are subject to considerable uncertainty in dynamic environments. The ability to cope with the uncertainty in scheduling process is becoming increasingly important in today's highly dynamic and competitive business environments. In the literature, two approaches have appeared as the effective way: reactive and proactive scheduling. The objective in reactive scheduling is to revise schedules as necessary, while proactive scheduling attempts to incorporate future disruptions when generating schedules. In this paper we take a proactive scheduling approach to solve a machine scheduling problem with two sources of uncertainty: processing time variability and machine breakdowns. We define two robustness measures and develop a heuristic based on beam search methodology to optimize them. The computational results show that the proposed algorithms perform significantly better than a number of heuristics available in the literature.
Open Access
A beam search-based algorithm and evaluation of scheduling approaches for fexible manufacturing systems
(Taylor & Francis, 1998) Sabuncuoglu İ.; Karabuk, S.
This paper presents a new algorithm for the flexible manufacturing system (FMS) scheduling problem. The proposed algorithm is a heuristic based on filtered beam search. It considers finite buffer capacity, routing and sequence flexibilities and generates machine and automated guided vehicle (AGV) schedules for a given scheduling period. A new deadlock resolution mechanism is also developed as an integral part of the proposed algorithm. The performance of the algorithm is compared with several machine and AGV dispatching rules using mean flow time, mean tardiness and makespan criteria. It is also used to examine the effects of scheduling factors (i.e., machine and AGV load levels, routing and sequence flexibilities, etc.) on the system performance. The results indicate thai the proposed scheduling algorithm yields considerable improvements in system performance over dispatching rules under a wide variety of experimental conditions. © 1998 "IIE".
Open Access
A comparative study of computational procedures for the resource constrained project scheduling problem
(Elsevier, 1994) Oğuz, O.; Bala, H.
Performance of two new integer programming based heuristics together with some special purpose algorithms for project scheduling are tested from a computational point of view. The objective of the study is to compare the quality of solutions obtained by using these algorithms and reach conclusions about their relative merits on this specific problem. © 1994.
Open Access
Comparison and combination of two novel commercial detection methods
(IEEE, 2004-06) Duygulu, Pınar; Chen, M.-Y.; Hauptmann, A.
Detection and removal of commercials plays an important role when searching for important broadcast news video material. In this study, two novel approaches are proposed based on two distinctive characteristics of commercials, namely, repetitive use of commercials over time and distinctive color and audio features. Furthermore, proposed strategies for combining the results of the two methods yield even better performance. Experiments show over 90% recall and precision on a test set of 5 hours of ABC and CNN broadcast news data.
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
Designing a road network for hazardous materials shipments
(Elsevier, 2007) Erkut, E.; Alp, O.
We consider the problem of designating hazardous materials routes in and through a major population center. Initially, we restrict our attention to a minimally connected network (a tree) where we can predict accurately the flows on the network. We formulate the tree design problem as an integer programming problem with an objective of minimizing the total transport risk. Such design problems of moderate size can be solved using commercial solvers. We then develop a simple construction heuristic to expand the solution of the tree design problem by adding road segments. Such additions provide carriers with routing choices, which usually increase risks but reduce costs. The heuristic adds paths incrementally, which allows local authorities to trade off risk and cost. We use the road network of the city of Ravenna, Italy, to demonstrate the solution of our integer programming model and our path-addition heuristic.
Open Access
Designing emergency response networks for hazardous materials transportation
(2007) Berman O.; Verter V.; Kara, B.Y.
Undesirable consequences of dangerous goods incidents can be mitigated by quick arrival of specialized response teams at the accident site. We present a novel methodology to determine the optimal design of a specialized team network so as to maximize its ability to respond to such incidents in a region. We show that this problem can be represented via a maximal arc-covering model. We discuss two formulations for the maximal arc-covering problem, a known one and a new one. Through computational experiments, we establish that the known formulation has excessive computational requirements for large-scale problems, whereas the alternative model constitutes a basis for an efficient heuristic. The methodology is applied to assess the emergency response capability to transport incidents, that involve gasoline, in Quebec and Ontario. We point out the possibility of a significant improvement via relocation of the existing specialized teams, which are currently stationed at the shipment origins. © 2005 Elsevier Ltd. All rights reserved.
Open Access
A distance-limited continuous location-allocation problem for spatial planning of decentralized systems
(Elsevier, 2017) Gokbayrak, K.; Kocaman, A. S.
We introduce a new continuous location-allocation problem where the facilities have both a fixed opening cost and a coverage distance limitation. The problem has wide applications especially in the spatial planning of water and/or energy access networks where the coverage distance might be associated with the physical loss constraints. We formulate a mixed integer quadratically constrained problem (MIQCP) under the Euclidean distance setting and present a three-stage heuristic algorithm for its solution: In the first stage, we solve a planar set covering problem (PSCP) under the distance limitation. In the second stage, we solve a discrete version of the proposed problem where the set of candidate locations for the facilities is formed by the union of the set of demand points and the set of locations in the PSCP solution. Finally, in the third stage, we apply a modified Weiszfeld's algorithm with projections that we propose to incorporate the coverage distance component of our problem for fine-tuning the discrete space solutions in the continuous space. We perform numerical experiments on three example data sets from the literature to demonstrate the performance of the suggested heuristic method.
Open Access
Dynamic lot sizing and tool management in automated manufacturing systems
(Elsevier, 2002) Aktürk, M. S.; Önen, S.
The overall aim of this study is to show that there is a critical interface between the lot sizing and tool management decisions, and these two problems cannot be viewed in isolation. We propose "ve alternative algorithms to solve lot sizing, tool allocation and machining conditions optimization problems simultaneously. The "rst algorithm is an exact algorithm which "nds the global optimum solution, and the others are heuristics equipped with a look-ahead mechanism to guarantee at least local optimality. The computational results indicate that the amount of improvement is statistically signi"cant for a set of randomly generated problems. The magnitude of cost savings is dependent on the system parameters.
Open Access
Exact and heuristic approaches based on noninterfering transmissions for joint gateway selection, time slot allocation, routing and power control for wireless mesh networks
(Elsevier, 2017) Gokbayrak, K.; Yıldırım, E. A.
Wireless mesh networks (WMNs) provide cost-effective alternatives for extending wireless communication over larger geographical areas. In this paper, given a WMN with its nodes and possible wireless links, we consider the problem of gateway node selection for connecting the network to the Internet along with operational problems such as routing, wireless transmission capacity allocation, and transmission power control for efficient use of wired and wireless resources. Under the assumption that each node of the WMN has a fixed traffic rate, our goal is to allocate capacities to the nodes in proportion to their traffic rates so as to maximize the minimum capacity-to-demand ratio, referred to as the service level. We adopt a time division multiple access (TDMA) scheme, in which a time frame on the same frequency channel is divided into several time slots and each node can transmit in one or more time slots. We propose two mixed integer linear programming formulations. The first formulation, which is based on individual transmissions in each time slot, is a straightforward extension of a previous formulation developed by the authors for a related problem under a different set of assumptions. The alternative formulation, on the other hand, is based on sets of noninterfering wireless transmissions. In contrast with the first formulation, the size of the alternative formulation is independent of the number of time slots in a frame. We identify simple necessary and sufficient conditions for simultaneous transmissions on different links of the network in the same time slot without any significant interference. Our characterization, as a byproduct, prescribes a power level for each of the transmitting nodes. Motivated by this characterization, we propose a simple scheme to enumerate all sets of noninterfering transmissions, which is used as an input for the alternative formulation. We also introduce a set of valid inequalities for both formulations. For large instances, we propose a three-stage heuristic approach. In the first stage, we solve a partial relaxation of our alternative optimization model and determine the gateway locations. This stage also provides an upper bound on the optimal service level. In the second stage, a routing tree is constructed for each gateway node computed in the first stage. Finally, in the third stage, the alternative optimization model is solved by fixing the resulting gateway locations and the routing trees from the previous two stages. For even larger networks, we propose a heuristic approach for solving the partial relaxation in the first stage using a neighborhood search on gateway locations. Our computational results demonstrate the promising performance of our exact and heuristic approaches and the valid inequalities
Open Access
Fast optimal load balancing algorithms for 1D partitioning
(Academic Press, 2004) Pınar, A.; Aykanat, Cevdet
The one-dimensional decomposition of nonuniform workload arrays with optimal load balancing is investigated. The problem has been studied in the literature as the "chains-on-chains partitioning" problem. Despite the rich literature on exact algorithms, heuristics are still used in parallel computing community with the "hope" of good decompositions and the "myth" of exact algorithms being hard to implement and not runtime efficient. We show that exact algorithms yield significant improvements in load balance over heuristics with negligible overhead. Detailed pseudocodes of the proposed algorithms are provided for reproducibility. We start with a literature review and propose improvements and efficient implementation tips for these algorithms. We also introduce novel algorithms that are asymptotically and runtime efficient. Our experiments on sparse matrix and direct volume rendering datasets verify that balance can be significantly improved by using exact algorithms. The proposed exact algorithms are 100 times faster than a single sparse-matrix vector multiplication for 64-way decompositions on the average. We conclude that exact algorithms with proposed efficient implementations can effectively replace heuristics. © 2004 Elsevier Inc. All rights reserved.
Open Access
Generalizing predicates with string arguments
(Springer New York LLC, 2006-06) Cicekli, I.; Cicekli, N. K.
The least general generalization (LGG) of strings may cause an over-generalization in the generalization process of the clauses of predicates with string arguments. We propose a specific generalization (SG) for strings to reduce over-generalization. SGs of strings are used in the generalization of a set of strings representing the arguments of a set of positive examples of a predicate with string arguments. In order to create a SG of two strings, first, a unique match sequence between these strings is found. A unique match sequence of two strings consists of similarities and differences to represent similar parts and differing parts between those strings. The differences in the unique match sequence are replaced to create a SG of those strings. In the generalization process, a coverage algorithm based on SGs of strings or learning heuristics based on match sequences are used. © Springer Science + Business Media, LLC 2006.
Open Access
Heuristics for scheduling file-sharing tasks on heterogeneous systems with distributed repositories
(Academic Press, 2007) Kaya, K.; Uçar, B.; Aykanat, Cevdet
We consider the problem of scheduling an application on a computing system consisting of heterogeneous processors and data repositories. The application consists of a large number of file-sharing otherwise independent tasks. The files initially reside on the repositories. The processors and the repositories are connected through a heterogeneous interconnection network. Our aim is to assign the tasks to the processors, to schedule the file transfers from the repositories, and to schedule the executions of tasks on each processor in such a way that the turnaround time is minimized. We propose a heuristic composed of three phases: initial task assignment, task assignment refinement, and execution ordering. We experimentally compare the proposed heuristics with three well-known heuristics on a large number of problem instances. The proposed heuristic runs considerably faster than the existing heuristics and obtains 10-14% better turnaround times than the best of the three existing heuristics. © 2006 Elsevier Inc. All rights reserved.
Open Access
An integrated approach for airline scheduling, aircraft fleeting and routing with cruise speed control
(Elsevier, 2016) Gürkan, H.; Gürel, S.; Aktürk, M. S.
To place an emphasis on profound relations among airline schedule planning problems and to mitigate the effect of unexpected delays, we integrate schedule design, fleet assignment and aircraft routing problems within a daily planning horizon while passengers' connection service levels are ensured via chance constraints. We propose a nonlinear mixed integer programming model due to the nonlinear fuel consumption and CO2 emission cost terms in the objective function, which is handled by second order conic reformulation. The key contribution of this study is to take into account the cruise time control for the first time in an integrated model of these three stages of airline operations. Changing cruise times of flights in an integrated model enables to construct a schedule to increase utilization of fuel efficient aircraft and even to decrease total number of aircraft needed while satisfying the same service level and maintenance requirements for aircraft fleeting and routing. There is a critical tradeoff between the number of aircraft needed to fulfill the required flights and overall operational expenses. We also propose two heuristic methods to solve larger size problems. Finally, computational results using real data obtained from a major U.S. carrier are presented to demonstrate potential profitability in applying the proposed solution methods.
Open Access
Job shop scheduling with beam search
(Elsevier Science B.V., Amsterdam, Netherlands, 1999) Sabuncuoglu I.; Bayiz, M.
Beam Search is a heuristic method for solving optimization problems. It is an adaptation of the branch and bound method in which only some nodes are evaluated in the search tree. At any level, only the promising nodes are kept for further branching and remaining nodes are pruned off permanently. In this paper, we develop a beam search based scheduling algorithm for the job shop problem. Both the makespan and mean tardiness are used as the performance measures. The proposed algorithm is also compared with other well known search methods and dispatching rules for a wide variety of problems. The results indicate that the beam search technique is a very competitive and promising tool which deserves further research in the scheduling literature.