Browsing by Subject "Heuristic algorithms"

Now showing 1 - 19 of 19

Open Access
Assortment planning considering split orders
(2021-08) Söylemez, Duygu
When multi-item orders cannot be satisﬁed through a single shipment stemming from not having all the items in an order in the same warehouse, the cost of packaging and transportation increases and the delivery of the orders can be delayed. In this regard, split order problem is one of the most signiﬁcant challenges that the online retailers face. As the capacities of the warehouses are limited, it is not possible to stock every item in every warehouse. To minimize the number of orders that cannot be satisﬁed in a single shipment, it is important to determine how the limited capacities of the warehouses should be allocated to items or it is necessary to decrease the transportation costs through consolidating the split orders. Since this problem is NP-hard, the previous studies in the literature are based on heuristic algorithms. In this study, exact and heuristic methods have been examined to solve large scale problems. Some of the heuristic algorithms oﬀered uses the LP relaxation of the model provided by Jehl et al.(2018). In this sense, the analytical characterization of the optimal solution of the LP relaxation has also been revealed. It is proved that the allocation variables can only take three diﬀerent values at most one being fractional. It is shown that this solution can be found without actually solving the LP relaxation by beneﬁting from an algorithm oﬀered in literature to solve 0-1 fractional programming problems. Moreover, it is proved that a similar characterization is preserved for multiple warehouses or when a central depot with unlimited capacity and a forward distribution center are considered together. Additionally, the working principle of the greedy ranking algorithm oﬀered in the literature is theoretically justiﬁed and a dynamic version of this algorithm is developed. To evaluate the performance of the heuristic algorithms oﬀered and the run time of the integer programming problem, an extensive numerical study has been conducted. The change in the diﬃculty level of the problem based on the plant capacity, the number of orders, and the number of stock keeping units (SKU) is scrutinized. Furthermore, the assortment allocation problem is modeled together with the consolidation problem. The performance of the model is evaluated through comparing its solution to the solution obtained through solving two problems consecutively.
Open Access
Bicriteria multiresource generalized assignment problem
(John Wiley & Sons, 2014) Karsu, O.; Azizoglu, M.
In this study,we consider a bicriteria multiresource generalized assignment problem. Our criteria are the total assignment load and maximum assignment load over all agents. We aim to generate all nondominated objective vectors and the corresponding efficient solutions. We propose several lower and upper bounds and use them in our optimization and heuristic algorithms. The computational results have shown the satisfactory behaviors of our approaches.
Open Access
Çok kollu haydutlar ile dinamik ambulans konumlandırma
(IEEE, 2019-04) Şahin, Ümitcan; Yücesoy, V.
Bir ülkenin acil yardım sistemlerinin iyileştirilmesi, daha çok acil vakaya zamanında müdahale edilmesi ve daha çok hayatın kurtarılmasını sağlar. 112 Acil Yardım sisteminin bir parçası olan ambulans konumlandırma problemi, ambulansların vakalara mümkün olan en kısa sürede ulaşmasını sağlayacak şekilde konumlandırılmasını sağlayan birçok yöntemden oluşur. Bu çalışmada ambulanslar, literatürdeki yöntemlerin aksine, bir çok kollu haydut (ÇKH) algoritması kullanılarak konumlandırılmaktadır. OpenStreetMap (OSM) harita uygulaması kullanılarak oluşturulmuş iki yönlü kenarlardan ve toplam 2400 düğümden oluşan bir Ankara şehri haritası üzerinde konumlandırma işlemi yapılmaktadır. Düğümler üzerindeki vaka dağılımları ve aralarındaki seyahat süreleri ÇKH algoritması tarafından bilinmemektedir ve zamanla öğrenilmektedir. Bu öğrenim keşif ve istifade arasındaki ödünleşim sistemi ile sağlanmaktadır. Algoritma karşılaştırmaları için literatürde sıkça kullanılan ve dinamik bir konumlandırma yöntemi olan DMEXCLP modeli kullanılmıştır. Simülasyonlarda algoritma karşılaştırmaları için iki ölçüt değerlendirilmiştir: 1) vakalara ortalama müdahale süresi ve 2) 15 dakika altında varılan vaka yüzdesi. Sonuç olarak aynı şartlar altında önerilen ÇKH algoritmasının DMEXCLP modeline göre bu iki ölçüt açısından daha iyi performans verdiği gösterilmiştir.
Open Access
Design of a fully automated robotic spot-welding line
(Science and Technology Publications, 2011) Aktürk, M. Selim; Tula, Adnan; Gültekin, H.
The mixed model assembly line design problem includes allocating operations to the stations in the robotic cell and satisfying the demand and cycle time within a desired interval for each model to be produced. We also ensure that assignability, precedence and tool life constraints are met. Each pair of spot welding tools can process a certain number of welds and must be replaced at the end of tool life. Tool replacement decisions not only affect the tooling cost, but also the production rate. Therefore, we determine the number of stations and allocate the operations into the stations in such a way that tool change periods coincide with the unavailability periods to eliminate tool change related line stoppages in a mixed model fully automated robotic assembly line. We provide a mathematical formulation of the problem, and propose a heuristic algorithm.
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 congestion control in interconnected computer networks
(IEEE, 1988-10) Ulusoy, Özgür; Baray, Mehmet
The authors evaluate a window-based congestion control mechanism in an internetwork environment. They also propose and study two dynamic-window congestion-control algorithms. These algorithms provide further control to the window mechanism by adjusting the window size in accordance with the availability of the network resources at the destination. A comparison of dynamic algorithms with fixed window control is provided in terms of throughput and delay performance. It is shown that dynamic algorithms have considerable performance advantages over fixed-window control.
Open Access
Evaluation of a broadcast scheduling algorithm
(Springer, Berlin, Heidelberg, 2001) Karakaya, M.; Ulusoy, Özgür
One of the two main approaches of data broadcasting is pull- based data delivery. In this paper, we focus on the problem of scheduling data items to broadcast in such a pull-based environment. Previous work has shown that the Longest Wait First heuristic has the best performance results compared to all other broadcast scheduling algorithms, however the decision overhead avoids its practical implementation. Observing this fact, we propose an efficient broadcast scheduling algorithm which is based on an approximate version of the Longest Wait First heuristic. We also compare the performance of the proposed algorithm against well- known broadcast scheduling algorithms. © Springer-Verlag Berlin Heidelberg 2001.
Open Access
Fair task allocation in crowdsourced delivery
(Institute of Electrical and Electronics Engineers, 2018) Basik, F.; Gedik, B.; Ferhatosmanoglu, H.; Wu, K.
Faster and more cost-efficient, crowdsourced delivery is needed to meet the growing customer demands of many industries. In this work, we introduce a new crowdsourced delivery platform that takes fairness towards workers into consideration, while maximizing the task completion ratio. Since redundant assignments are not possible in delivery tasks, we first introduce a 2-phase assignment model that increases the reliability of a worker to complete a given task. To realize the effectiveness of our model in practice, we present both offline and online versions of our proposed algorithm called F-Aware. Given a task-to-worker bipartite graph, F-Aware assigns each task to a worker that maximizes fairness, while allocating tasks to use worker capacities as much as possible. We present an evaluation of our algorithms with respect to running time, task completion ratio, as well as fairness and assignment ratio. Experiments show that F-Aware runs around $10^7\times$ faster than the TAR-optimal solution and assigns 96.9% of the tasks that can be assigned by it. Moreover, it is shown that, F-Aware is able to provide a much fair distribution of tasks to workers than the best competitor algorithm. IEEE
Open Access
Investigation of multi-objective optimization criteria for RNA design
(IEEE, 2017-12) Hampson, D. J. D.; Sav, Sinem; Tsang, H. H.
RNA design is the inverse of RNA folding and it appears to be NP-hard. In RNA design, a secondary structure is given and the goal is to find a nucleotide sequence that will fold into this structure. To find such sequence(s) involves exploring the exponentially large sequence space. In literature, heuristic algorithms are the standard technique for tackling the RNA design. Heuristic algorithms enable effective and efficient exploration of the high-dimensional sequence-structure space when searching for candidates that fold into a given target structure. The main goal of this paper is to investigate the use of multi-objective criteria in SIMARD and Quality Pre-selection Strategy (QPS). The objectives that we optimize are Hamming distance (between designed structure and target structure) and thermodynamic free energy. We examine the different combinations of optimization criteria, and attempt to draw conclusions about the relationships between them. We find that energy is a poor primary objective but makes an excellent secondary objective. We also find that using multi-objective pre-selection produces viable solutions in far fewer steps than was previously possible with SIMARD. © 2016 IEEE.
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
Network-aware virtual machine placement in cloud data centers with multiple traffic-intensive components
(Elsevier BV, 2015) Ilkhechi, A. R.; Korpeoglu, I.; Ulusoy, Özgür
Following a shift from computing as a purchasable product to computing as a deliverable service to consumers over the Internet, cloud computing has emerged as a novel paradigm with an unprecedented success in turning utility computing into a reality. Like any emerging technology, with its advent, it also brought new challenges to be addressed. This work studies network and traffic aware virtual machine (VM) placement in a special cloud computing scenario from a provider's perspective, where certain infrastructure components have a predisposition to be the endpoints of a large number of intensive flows whose other endpoints are VMs located in physical machines (PMs). In the scenarios of interest, the performance of any VM is strictly dependent on the infrastructure's ability to meet their intensive traffic demands. We first introduce and attempt to maximize the total value of a metric named "satisfaction" that reflects the performance of a VM when placed on a particular PM. The problem of finding a perfect assignment for a set of given VMs is NP-hard and there is no polynomial time algorithm that can yield optimal solutions for large problems. Therefore, we introduce several off-line heuristic-based algorithms that yield nearly optimal solutions given the communication pattern and flow demand profiles of subject VMs. With extensive simulation experiments we evaluate and compare the effectiveness of our proposed algorithms against each other and also against naïve approaches.
Open Access
Parallel dedicated machine scheduling with a single server: full precedence case
(IIE, 2004) Schultz, S. R.; Taner, Mehmet Rüştü
The motivation for this study was the observation of a practical scenario that involves scheduling of two parallel machines attended by a single setup crew so as to minimize the makespan. This problem is known in scheduling literature as the parallel machine scheduling problem with a single server, P2S1/ / C max. In order to gain insight on this problem, we analyzed a constrained version of it. In this constrained case, jobs are dedicated to each machine, and the processing sequence on each machine is given and fixed. The problem is thus referred to as the parallel, dedicated machine scheduling problem with a single server and full precedence, PD2S1/full prec./ C max. We explore the combinatoric structure of the problem, and develop a branch and bound procedure and five heuristic algorithms.
Open Access
Pipelined fission for stream programs with dynamic selectivity and partitioned state
(Academic Press, 2016) Gedik, B.; Özsema, H. G.; Öztürk, Ö.
There is an ever increasing rate of digital information available in the form of online data streams. In many application domains, high throughput processing of such data is a critical requirement for keeping up with the soaring input rates. Data stream processing is a computational paradigm that aims at addressing this challenge by processing data streams in an on-the-fly manner, in contrast to the more traditional and less efficient store-and-then process approach. In this paper, we study the problem of automatically parallelizing data stream processing applications in order to improve throughput. The parallelization is automatic in the sense that stream programs are written sequentially by the application developers and are parallelized by the system. We adopt the asynchronous data flow model for our work, which is typical in Data Stream Processing Systems (DSPS), where operators often have dynamic selectivity and are stateful. We solve the problem of pipelined fission, in which the original sequential program is parallelized by taking advantage of both pipeline parallelism and data parallelism at the same time. Our pipelined fission solution supports partitioned stateful data parallelism with dynamic selectivity and is designed for shared-memory multi-core machines. We first develop a cost-based formulation that enables us to express pipelined fission as an optimization problem. The bruteforce solution of this problem takes a long time for moderately sized stream programs. Accordingly, we develop a heuristic algorithm that can quickly, but approximately, solve the pipelined fission problem. We provide an extensive evaluation studying the performance of our pipelined fission solution, including simulations as well as experiments with an industrial-strength DSPS. Our results show good scalability for applications that contain sufficient parallelism, as well as close to optimal performance for the heuristic pipelined fission algorithm.
Open Access
Solution methodologies for debris removal in disaster response
(Springer, 2016) Berktaş, N.; Kara, B. Y.; Karaşan, O. E.
During the disaster response phase of the emergency relief, the aim is to reduce loss of human life by reaching disaster affected areas with relief items as soon as possible. Debris caused by the disaster blocks the roads and prevents emergency aid teams to access the disaster affected regions. Deciding which roads to clean to transport relief items is crucial to diminish the negative impact of a disaster on human health. Despite the significance of the problem during response phase, in the literature debris removal is mostly studied in the recovery or the reconstruction phases of a disaster. The aim of this study is providing solution methodologies for debris removal problem in the response phase in which effective and fast relief routing is of utmost importance. In particular, debris removal activities on certain blocked arcs have to be scheduled to reach a set of critical nodes such as schools and hospitals. To this end, two mathematical models are developed with different objectives. The first model aims to minimize the total time spent to reach all the critical nodes whereas the second minimizes the weighted sum of visiting times where weights indicate the priorities of critical nodes. Since obtaining solutions quickly is important in the early post-disaster, heuristic algorithms are also proposed. Two data sets belonging to Kartal and Bakırköy districts of İstanbul are used to test the mathematical models and heuristics.
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
Traveling repairmen problem: A biogeography-based optimization
(Springer Cham, 2022-07-14) Öder Uzun, G.; Dengiz, B.; Kara, İ.; Karasan, Oya Ekin; Xu, Jiuping; Altıparmak, Fulya; Hassan, Mohamed Hag Ali; Márquez, Fausto Pedro García; Hajiyev, Asaf
Traveling Repairman Problem (TRP), which is also known by names cumulative traveling salesman problem, the deliveryman prob lem and the minimum latency problem, is a special variant of Traveling Salesman Problem (TSP). In contrast to the minimization of completion time objective of TSP, the desired objective of TRP is to minimize the cumulative latency (waiting time or delay time) of all customers. In this paper, a generalized version of TRP with multi depots and time windows, namely Multi Depot Traveling Repairman Problem with Time Windows (MDTRPTW) is considered. A group of homogeneous repairmen initi ate and finish their visit tours at multiple depots. Each customer must be visited exactly by one repairman within their provided earliest end latest times. Being a challenging Nondeterministic Polynomial-hard (NP hard) optimization problem, exact solution approaches are not expected to scale to realistic dimensions of MDTRPTW. Thus, we propose a biogeography-based optimization algorithm (BBOA) as a metaheuristic approach to solve large size MDTRPTW problems. The proposed meta heuristic is analyzed in terms of solution quality, coefficient of variation as well as computation time by solving some test problems adapted from the related literature. The efficacy of the proposed solution methodology is demonstrated by solving instances with 288 customers within seconds.
Open Access
Uniform weighted round robin scheduling algorithms for input queued switches
(IEEE, 2001-06) Rai, Idris A.; Alanyalı, Murat
This paper concentrates on obtaining uniform weighted round robin schedules for input queued packet switches. The desired schedules are uniform in the sense that each connection is serviced at regularly spaced time slots, where the spacing is proportional to the inverse of the guaranteed data rate. Suitable applications include ATM networks as well as satellite switched TDMA systems that provide per packet delay guarantees. Three heuristic algorithms are proposed to obtain such schedules under the constraints imposed by the unit speedup of input queued switches. Numerical experiments indicate that the algorithms have remarkable performance in finding uniform schedules.
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.