Showing papers on "Routing (electronic design automation) published in 2014"
TL;DR: An overview of the different routing strategies used in wireless sensor networks is given and the comparison of these different routing protocols based on metrics such as mobility support, stability, issues and latency is shown.
Abstract: This paper represents energy efficient routing protocols in WSN. It is a collection of sensor nodes with a set of limited Processor and limited memory unit embedded in it. Reliable routing of packets from the sensor node to its base station is the most important task for the networks. The routing protocols applied for the other networks cannot be used here due to its battery powered nodes This paper gives an overview of the different routing strategies used in wireless sensor networks and gives a brief working model of energy efficient routing protocols in WSN. It also shows the comparison of these different routing protocols based on metrics such as mobility support, stability, issues and latency.
579 citations
TL;DR: In this article, the authors present several heuristics for a variation of the vehicle routing problem in which the transportation fleet is composed of electric vehicles with limited autonomy in need for recharge during their duties.
Abstract: This paper presents several heuristics for a variation of the vehicle routing problem in which the transportation fleet is composed of electric vehicles with limited autonomy in need for recharge during their duties. In addition to the routing plan, the amount of energy recharged and the technology used must also be determined. Constructive and local search heuristics are proposed, which are exploited within a non deterministic Simulated Annealing framework. Extensive computational results on varying instances are reported, evaluating the performance of the proposed algorithms and analyzing the distinctive elements of the problem (size, geographical configuration, recharge stations, autonomy, technologies, etc.).
359 citations
TL;DR: This paper proposes a layered-auxiliary-graph (LAG) approach that decomposes the physical infrastructure into several layered graphs according to the bandwidth requirement of a virtual optical network request, and designs a novel heuristic for opaque VONE, consecutiveness-aware LRC-K shortest-path-first fit (CaL RC-KSP-FF).
Abstract: Based on the concept of infrastructure as a service, optical network virtualization can facilitate the sharing of physical infrastructure among different users and applications. In this paper, we design algorithms for both transparent and opaque virtual optical network embedding (VONE) over flexible-grid elastic optical networks. For transparent VONE, we first formulate an integer linear programming (ILP) model that leverages the all-or-nothing multi-commodity flow in graphs. Then, to consider the continuity and consecutiveness of substrate fiber links' (SFLs') optical spectra, we propose a layered-auxiliary-graph (LAG) approach that decomposes the physical infrastructure into several layered graphs according to the bandwidth requirement of a virtual optical network request. With LAG, we design two heuristic algorithms: one applies LAG to achieve integrated routing and spectrum assignment in link mapping (i.e., local resource capacity (LRC)-layered shortest-path routing LaSP), while the other realizes coordinated node and link mapping using LAG (i.e., layered local resource capacity(LaLRC)-LaSP). The simulation results from three different substrate topologies demonstrate that LaLRC-LaSP achieves better blocking performance than LRC-LaSP and an existing benchmark algorithm. For the opaque VONE, an ILP model is also formulated. We then design a LRC metric that considers the spectrum consecutiveness of SFLs. With this metric, a novel heuristic for opaque VONE, consecutiveness-aware LRC-K shortest-path-first fit (CaLRC-KSP-FF), is proposed. Simulation results show that compared with the existing algorithms, CaLRC-KSP-FF can reduce the request blocking probability significantly.
326 citations
TL;DR: In this article, a single UAV routing problem where there are multiple depots and the vehicle is allowed to refuel at any depot is considered, and an approximation algorithm for the problem is developed.
Abstract: We consider a single Unmanned Aerial Vehicle (UAV) routing problem where there are multiple depots and the vehicle is allowed to refuel at any depot. The objective of the problem is to find a path for the UAV such that each target is visited at least once by the vehicle, the fuel constraint is never violated along the path for the UAV, and the total fuel required by the UAV is a minimum. We develop an approximation algorithm for the problem, and propose fast construction and improvement heuristics to solve the same. Computational results show that solutions whose costs are on an average within 1.4% of the optimum can be obtained relatively fast for the problem involving five depots and 25 targets.
217 citations
TL;DR: In this paper, the authors present a model that optimizes ship speed for a spectrum of routing scenarios in a single ship setting, with the main contribution being the incorporation of those fundamental parameters and other considerations that weigh heavily in a ship owner or charterer's speed decision and in his routing decision.
Abstract: The purpose of this paper is to clarify some important issues as regards ship speed optimization at the operational level and develop models that optimize ship speed for a spectrum of routing scenarios in a single ship setting. The paper’s main contribution is the incorporation of those fundamental parameters and other considerations that weigh heavily in a ship owner’s or charterer’s speed decision and in his routing decision, wherever relevant. Various examples are given so as to illustrate the properties of the optimal solution and the various trade-offs that are involved.
208 citations
24 Sep 2014
TL;DR: It is shown that DCR is correct and that is orders of magnitude more scalable than recent name-based routing approaches for ICNs, in terms of the time and signaling overhead needed to obtain correct routing to named content.
Abstract: The Distance-based Content Routing (DCR) protocol is introduced, which enables routers to maintain multiple loop-free routes to the nearest instances of a named data object or name prefix in an information centric network (ICN), and establish content delivery trees over which all or some instances of the same named data object or name prefix can be contacted. In contrast to all prior routing solutions for ICNs, DCR operates without requiring routers to establish overlays, knowing the network topology, using complete paths to content replicas, or knowing about all the sites storing replicas of named content. It is shown that DCR is correct and that is orders of magnitude more scalable than recent name-based routing approaches for ICNs, in terms of the time and signaling overhead needed to obtain correct routing to named content.
203 citations
TL;DR: This paper proposes a home-aware community model, whereby an MSN is turned into a network that only includes community homes, and proves that it can still compute the minimum expected delivery delays of nodes through a reverse Dijkstra algorithm and achieve the optimal opportunistic routing performance.
Abstract: Mobile social networks (MSNs) are a kind of delay tolerant network that consists of lots of mobile nodes with social characteristics. Recently, many social-aware algorithms have been proposed to address routing problems in MSNs. However, these algorithms tend to forward messages to the nodes with locally optimal social characteristics, and thus cannot achieve the optimal performance. In this paper, we propose a distributed optimal Community-Aware Opportunistic Routing (CAOR) algorithm. Our main contributions are that we propose a home-aware community model, whereby we turn an MSN into a network that only includes community homes. We prove that, in the network of community homes, we can still compute the minimum expected delivery delays of nodes through a reverse Dijkstra algorithm and achieve the optimal opportunistic routing performance. Since the number of communities is far less than the number of nodes in magnitude, the computational cost and maintenance cost of contact information are greatly reduced. We demonstrate how our algorithm significantly outperforms the previous ones through extensive simulations, based on a real MSN trace and a synthetic MSN trace.
200 citations
TL;DR: This work introduces multivehicle PRP and IRP formulations, with and without a vehicle index, to solve the problems under both the maximum level (ML) and order-up-to level (OU) inventory replenishment policies.
Abstract: The inventory routing problem (IRP) and the production routing problem (PRP) are two difficult problems arising in the planning of integrated supply chains. These problems are solved in an attempt to jointly optimize production, inventory, distribution, and routing decisions. Although several studies have proposed exact algorithms to solve the single-vehicle problems, the multivehicle aspect is often neglected because of its complexity. We introduce multivehicle PRP and IRP formulations, with and without a vehicle index, to solve the problems under both the maximum level (ML) and order-up-to level (OU) inventory replenishment policies. The vehicle index formulations are further improved using symmetry breaking constraints; the nonvehicle index formulations are strengthened by several cuts. A heuristic based on an adaptive large neighborhood search technique is also developed to determine initial solutions, and branch-and-cut algorithms are proposed to solve the different formulations. The results show tha...
199 citations
27 Aug 2014
TL;DR: A classification in three classes of matheuristics: decomposition approaches, improvement heuristics and branch-and-price/column generation-based approaches is proposed.
Abstract: In this paper, we survey the literature on matheuristics proposed to solve vehicle routing problems. A matheuristic makes use of mathematical programming models in a heuristic framework. Matheuristics have been applied to several different routing problems and include a number of different approaches. We propose a classification in three classes of matheuristics: decomposition approaches, improvement heuristics and branch-and-price/column generation-based approaches. The contribution of this paper is to offer to researchers interested in routing problems a structured overview of the most successful ideas to combine heuristic schemes and mathematical programming models to obtain high quality solutions. Moreover, we analyze the state of the art and provide insights and hints for future research.
180 citations
TL;DR: An adaptive large neighborhood search, exploiting the ruin-and-recreate principle, is proposed for solving the vehicle routing problem with multiple routes, and results on Euclidean instances demonstrate the benefits of this multi-level approach.
159 citations
TL;DR: An efficient implementation of variable neighborhood search that incorporates new features in addition to the adaptation of several existing neighborhoods and local search operators is proposed, including a preprocessing scheme for identifying borderline customers, and a neighborhood reduction test that saves nearly 80% of the CPU time, especially on the large instances.
TL;DR: This article presents a comprehensive survey of routing protocols proposed for routing in Vehicular Delay Tolerant Networks (VDTN) in vehicular environment, focusing on a special type of VANET, where the vehicular traffic is sparse and direct end-to-end paths between communicating parties do not always exist.
TL;DR: An optimization-based adaptive large neighborhood search heuristic for the production routing problem that outperforms existing heuristics for the PRP and can produce high-quality solutions in short computing times is introduced.
Abstract: Operational problems arising in the planning of integrated supply chains have been increasingly studied in the past decade. Among these, the production routing problem (PRP) is a difficult problem that aims to jointly optimize production, inventory, distribution, and routing decisions in order to satisfy the dynamic demand of customers and minimize the overall system cost. This paper introduces an optimization-based adaptive large neighborhood search heuristic for the PRP. In this heuristic, binary variables representing setup and routing decisions are handled by an enumeration scheme and upper-level search operators, respectively, and continuous variables associated with production, inventory, and shipment quantities are set by solving a network flow subproblem. Extensive computational experiments have been performed on benchmark instances from the literature. The results show that our algorithm generally outperforms existing heuristics for the PRP and can produce high-quality solutions in short computin...
01 Dec 2014
TL;DR: In this article, the authors demonstrate monolithic 3D integration of logic and memory in arbitrary vertical stacking order with the ability to use conventional inter-layer vias to connect between any layers of the 3D IC.
Abstract: We demonstrate monolithic 3D integration of logic and memory in arbitrary vertical stacking order with the ability to use conventional inter-layer vias to connect between any layers of the 3D IC. We experimentally show 4 vertically-stacked layers (logic layer followed by two memory layers followed by another logic layer), enabled by the integration of traditional silicon-FETs (on the bottom-most layer) with low-processing-temperature emerging nanotechnologies: metal-oxide resistive random-access memory (RRAM), and carbon nanotube-FETs (CNFETs). As a demonstration, we show a routing element of a switchbox for a field-programmable gate array (FPGA), with each component of the routing element (involving both logic and memory elements) on their own vertical layer.
TL;DR: In this paper, the authors consider an ordering of customers instead of building a giant tour, and propose an ordering-first split-second approach for vehicle routing. But this approach can be declined for different vehicle routing problems and reviews the associated literature.
Abstract: Cluster-first route-second methods like the sweep heuristic (Gillett and Miller, 1974) are well known in vehicle routing. They determine clusters of customers compatible with vehicle capacity and solve a traveling salesman problem for each cluster. The opposite approach, called route-first cluster-second, builds a giant tour covering all customers and splits it into feasible trips. Cited as a curiosity for a long time but lacking numerical evaluation, this technique has nevertheless led to successful metaheuristics for various vehicle routing problems in the last decade. As many implementations consider an ordering of customers instead of building a giant tour, we propose in this paper the more general name of ordering-first split-second methods. This article shows how this approach can be declined for different vehicle routing problems and reviews the associated literature, with more than 70 references.
TL;DR: This paper introduces a new model called environmental vehicle routing problem (EVRP) with the aim of reducing the adverse effect on the environment caused by the routing of vehicles and designs a hybrid artificial bee colony algorithm designed to solve the EVRP model.
Abstract: The vehicle routing problem (VRP) is a critical and vital problem in logistics for the design of an effective and efficient transportation network, within which the capacitated vehicle routing problem (CVRP) has been widely studied for several decades due to the practical relevance of logistics operation. However, CVRP with the objectives of minimizing the overall traveling distance or the traveling time cannot meet the latest requirements of green logistics, which concern more about the influence on the environment. This paper studies CVRP from an environmental perspective and introduces a new model called environmental vehicle routing problem (EVRP) with the aim of reducing the adverse effect on the environment caused by the routing of vehicles. In this research, the environmental influence is measured through the amount of the emission carbon dioxide, which is a widely acknowledged criteria and accounts for the major influence on environment. A hybrid artificial bee colony algorithm (ABC) is designed to solve the EVRP model, and the performance of the hybrid algorithm is evaluated through comparing with well-known CVRP instances. The computational results from numerical experiments suggest that the hybrid ABC algorithm outperforms the original ABC algorithm by 5% on average. The transformation from CVRP to EVRP can be recognized through the differentiation of their corresponding optimal solutions, which provides practical insights for operation management in green logistics.
01 Jan 2014
TL;DR: A direct interpretation of the DVRPFTW as a multi-objective problem where the total required fleet size, overall total traveling distance and waiting time imposed on vehicles are minimized and the overall customers' preferences for service is maximized.
Abstract: In this paper, a multi-objective dynamic vehicle routing problem with fuzzy time windows (DVRPFTW) is presented. In this problem, unlike most of the work where all the data are known in advance, a set of real time requests arrives randomly over time and the dispatcher does not have any deterministic or probabilistic information on the location and size of them until they arrive. Moreover, this model involves routing vehicles according to customer-specific time windows, which are highly relevant to the customers' satisfaction level. This preference information of customers can be represented as a convex fuzzy number with respect to the satisfaction for a service time. This paper uses a direct interpretation of the DVRPFTW as a multi-objective problem where the total required fleet size, overall total traveling distance and waiting time imposed on vehicles are minimized and the overall customers' preferences for service is maximized. A solving strategy based on the genetic algorithm (GA) and three basic modules are proposed, in which the state of the system including information of vehicles and customers is checked in a management module each time. The strategy module tries to organize the information reported by the management module and construct an efficient structure for solving in the subsequent module. The performance of the proposed approach is evaluated in different steps on various test problems generalized from a set of static instances in the literature. In the first step, the performance of the proposed approach is checked in static conditions and then the other assumptions and developments are added gradually and changes are examined. The computational experiments on data sets illustrate the efficiency and effectiveness of the proposed approach.
TL;DR: A joint order-batching and picker routing method is introduced to solve this combined precedence-constrained routing and order- batching problem and compares well to other heuristics from literature.
Abstract: This paper studies a vehicle routing problem with time-dependent and stochastic travel times. In our problem setting, customers have soft time windows. A mathematical model is used in which both efficiency for service as well as reliability for customers are taken into account. Depending on whether service times are included or not, we consider two versions of this problem. Two metaheuristics are built: a Tabu Search and an Adaptive Large Neighborhood Search. We carry out our experiments for well-known problem instances and perform comprehensive analyses on the numerical results in terms of the computational time and the solution quality. Experiments confirm that the proposed procedure is effective to obtain very good solutions to be performed in real-life environment.
TL;DR: A divide-and-conquer approach is proposed to solve the large-scale capacitated arc routing problem (LSCARP) more effectively, which adopts the cooperative coevolution framework to decompose it into smaller ones and solve them separately.
Abstract: In this paper, a divide-and-conquer approach is proposed to solve the large-scale capacitated arc routing problem (LSCARP) more effectively. Instead of considering the problem as a whole, the proposed approach adopts the cooperative coevolution (CC) framework to decompose it into smaller ones and solve them separately. An effective decomposition scheme called the route distance grouping (RDG) is developed to decompose the problem. Its merit is twofold. First, it employs the route information of the best-so-far solution, so that the quality of the decomposition is upper bounded by that of the best-so-far solution. Thus, it can keep improving the decomposition by updating the best-so-far solution during the search. Second, it defines a distance between routes, based on which the potentially better decompositions can be identified. Therefore, RDG is able to obtain promising decompositions and focus the search on the promising regions of the vast solution space. Experimental studies verified the efficacy of RDG on the instances with a large number of tasks and tight capacity constraints, where it managed to obtain significantly better results than its counterpart without decomposition in a much shorter time. Furthermore, the best-known solutions of the EGL-G LSCARP instances are much improved.
TL;DR: The results and analysis indicate that the proposed two-stage programming with fuzzy shortest path surpasses the performance of shortest path problem with time windows and capacity constraint (SPPTWCC) in terms of less computational time and CPU memory consumption.
Abstract: A supply chain network design needs to consider the future probability of reconfiguration due to some problems of disaster or price changes. The objective of this article is to design a reconfigurable supply chain network by optimizing inventory allocation and transportation routing. A two-stage programming is composed according to Benders decomposition by allocating inventory in advance and anticipating the changes of transportation routings; thus the transportation routing is stochastic in nature. In addition, the fuzzy shortest path is developed to solve the problem complexity in terms of the multi-criteria of lead time and capacity with an efficient computational method. The results and analysis indicate that the proposed two-stage programming with fuzzy shortest path surpasses the performance of shortest path problem with time windows and capacity constraint (SPPTWCC) in terms of less computational time and CPU memory consumption. Finally, management decision-making is discussed among other concluding remarks.
TL;DR: The proposed Tabu Search method combined with different local search schemes including both feasible and infeasible local searches reduces the total cost and better balances the workloads of vehicles.
Abstract: This paper addresses a periodic vehicle routing problem encountered in home health care (HHC) logistics. It extends the classical Periodic Vehicle Routing Problem with Time Windows (PVRPTW) to three types of demands of patients at home. Demands include transportation of drugs/medical devices between the \{HHC\} depot and patients׳ homes, delivery of special drugs from the hospital to patients, and delivery of blood samples from patients to the lab. Each patient requires a certain number of visits within a planning horizon and has a set of possible combinations of visit days. Daily routing should meet time window constraints associated with patients, the hospital and the lab. The problem consists in determining the visit days of each patient and vehicle routes for each day in order to minimize the maximal routing costs among all routes over the horizon. We propose a Tabu Search method combined with different local search schemes including both feasible and infeasible local searches. The proposed approaches are tested on a range of instances derived from existing Vehicle Routing Problem with Time Window (VRPTW) benchmarks and benchmarks on special cases of our problem. Numerical results show that local search scheme starting with an infeasible local search with a small probability followed by a feasible local search with high probability is an interesting hybridization. Experiments with field data from a \{HHC\} company show that the proposed approach reduces the total cost and better balances the workloads of vehicles.
Patent•
15 Apr 2014
TL;DR: In this article, a system and method for managing, routing and controlling devices and inter-device connections located within an environment to manage and control the environment using a control client is presented.
Abstract: A system and method for managing, routing and controlling devices and inter-device connections located within an environment to manage and control the environment using a control client is presented. A user configures a presentation environment into one or more sub-environments, restricts access to one or more devices of a presentation sub-environment, or schedules one or more resources within a presentation sub-environment.
TL;DR: This work presents a mathematical formulation for the bi-objective TLRP and proposes a new representation for the TLRP based on priorities, which lets us manage the problem easily and reduces the computational effort.
Patent•
01 Aug 2014TL;DR: In this article, a method and device for opportunistic compression of routing segment identifiers is described, which includes routing a first data packet through a first node in a network, and subsequently entering into an arrangement with an adjacent node in the network.
Abstract: A method and device are disclosed for opportunistic compression of routing segment identifiers. In one embodiment, the method includes participating in routing of a first data packet through a first node in a network, and subsequently entering into an arrangement with an adjacent node in the network. The first data packet includes a first plurality of routing segment identifiers, and additional data packets to be routed through the first node also include the first plurality of routing segment identifiers. The arrangement entered into includes representation of the first plurality of routing segment identifiers by a single compression identifier. The method further includes participating in routing of at least one of the additional data packets using the compression identifier instead of the first plurality of routing segment identifiers. In an embodiment, the device includes one or more network interfaces and a processor configured to perform the steps of the method.
Posted Content•
TL;DR: In this article, the authors proposed a method which combines a local search-based metaheuristic with an integer programming approach over a set covering formulation and a recursive speed-optimization algorithm.
Abstract: This paper deals with the Pollution-Routing Problem (PRP), a Vehicle Routing Problem (VRP) with environmental considerations, recently introduced in the literature by [Bektas and Laporte (2011), Transport. Res. B-Meth. 45 (8), 1232-1250]. The objective is to minimize operational and environmental costs while respecting capacity constraints and service time windows. Costs are based on driver wages and fuel consumption, which depends on many factors, such as travel distance and vehicle load. The vehicle speeds are considered as decision variables. They complement routing decisions, impacting the total cost, the travel time between locations, and thus the set of feasible routes. We propose a method which combines a local search-based metaheuristic with an integer programming approach over a set covering formulation and a recursive speed-optimization algorithm. This hybridization enables to integrate more tightly route and speed decisions. Moreover, two other "green" VRP variants, the Fuel Consumption VRP (FCVRP) and the Energy Minimizing VRP (EMVRP), are addressed. The proposed method compares very favorably with previous algorithms from the literature and many new improved solutions are reported.
TL;DR: This paper reviews the state-of-the-art for secure WSN routing protocols that illustrates the issues and challenges in the context design matters and proposes the schematic taxonomy of key design issues for WSN routes: basic, essential, and optional.
30 Jun 2014
TL;DR: A study of possible attacks that exploit the DODAG version system is presented and the impact on overhead, delivery ratio, end-to-end delay, rank inconsistencies and loops is studied.
Abstract: The IETF designed the Routing Protocol for Low power and Lossy Networks (RPL) as a candidate for use in constrained networks. Keeping in mind the different requirements of such networks, the protocol was designed to support multiple routing topologies, called DODAGs, constructed using different objective functions, so as to optimize routing based on divergent metrics. A DODAG versioning system is incorporated into RPL in order to ensure that the topology does not become stale and that loops are not formed over time. However, an attacker can exploit this versioning system to gain an advantage in the topology and also acquire children that would be forced to route packets via this node. In this paper we present a study of possible attacks that exploit the DODAG version system. The impact on overhead, delivery ratio, end-to-end delay, rank inconsistencies and loops is studied.
TL;DR: In this article, a comprehensive mathematical formulation is developed in order to model the one-to-many vehicle routing and scheduling problem with electric vehicles and the multiple constraints appeared due to capacity limitations, time window restrictions and the predefined charging level of the vehicles.
Abstract: This paper presents and analyzes the one-to-many vehicle routing and scheduling problem with electric vehicles. Initially, focus is given on the problem formulation and the restrictions imposed in practice are examined. EVRP is NP-hard in the strong sense since it is natural extension of the well-known Capacitated Vehicle Routing Problem and requires substantial computational effort for determining optimal or near optimal solutions for medium and large scale problem instances. A comprehensive mathematical formulation is developed in order to model the EVRP and the multiple constraints appeared due to capacity limitations, time window restrictions and the predefined charging level of the vehicles. In addition, recent trends for the EVRP are analyzed producing valuable insights for future research regarding extra operational constraints, real-life data sets and solution frameworks that embody approximation algorithms for an efficient and effective search of the solution space.
05 Oct 2014
TL;DR: This work introduces a general technique for supporting the rapid prototyping of interactivity by removing interior material from3D models to form internal pipes, and presents PipeDream, a tool for routing such pipes through the interior of 3D models, integrated within a 3D modeling program.
Abstract: 3D printers offer extraordinary flexibility for prototyping the shape and mechanical function of objects. We investigate how 3D models can be modified to facilitate the creation of interactive objects that offer dynamic input and output. We introduce a general technique for supporting the rapid prototyping of interactivity by removing interior material from 3D models to form internal pipes. We describe this new design space of pipes for interaction design, where variables include openings, path constraints, topologies, and inserted media. We then present PipeDream, a tool for routing such pipes through the interior of 3D models, integrated within a 3D modeling program. We use two distinct routing algorithms. The first has users define pipes' terminals, and uses path routing and physics-based simulation to minimize pipe bending energy, allowing easy insertion of media post-print. The second allows users to supply a desired internal shape to which we fit a pipe route: for this we describe a graph-routing algorithm. We present several prototypes created using our tool to show its flexibility and potential.