A new hybrid GA-PSO method for solving multi-period inventory routing problem with considering financial decisions

Directory of Open Access Journals (Sweden)

Masoud Rabbani

2013-09-01

Full Text Available Integration of various logistical components in supply chain management, such as transportation, inventory control and facility location are becoming common practice to avoid sub-optimization in nowadays’ competitive environment. The integration of transportation and inventory decisions is known as inventory routing problem (IRP in the literature. The problem aims to determine the delivery quantity for each customer and the network routes to be used in each period, so that the total inventory and transportation costs are to be minimized. On the contrary of conventional IRP that each retailer can only provide its demand from the supplier, in this paper, a new multi-period, multi-item IRP model with considering lateral trans-shipment, back-log and financial decisions is proposed as a business model in a distinct organization. The main purpose of this paper is applying an applicable inventory routing model with considering real world setting and solving it with an appropriate method.

Rich Vehicle Routing Problems and Applications

DEFF Research Database (Denmark)

Wen, Min

very short computational time on real-life data involving up to 200 pairs of suppliers and customers. The second problem we consider is a dynamic vehicle routing problem with multiple objectives over a planning horizon that consists of multiple periods. In this problem, customer orders are revealed...... the company’s solution in terms of all the objectives, including the travel time, customer waiting and daily workload balances, under the given constraints considered in the work. Finally, we address an integrated vehicle routing and driver scheduling problem, in which a large number of practical constraints....... The method is implemented and tested on real-life data involving up to 2000 orders. It is shown that the method is able to provide solutions of good quality within reasonable running time....

A constructive heuristic for time-dependent multi-depot vehicle routing problem with time-windows and heterogeneous fleet

Directory of Open Access Journals (Sweden)

Behrouz Afshar-Nadjafi

2017-01-01

Full Text Available In this paper, we consider the time-dependent multi-depot vehicle routing problem. The objective is to minimize the total heterogeneous fleet cost assuming that the travel time between locations depends on the departure time. Also, hard time window constraints for the customers and limitation on maximum number of the vehicles in depots must be satisfied. The problem is formulated as a mixed integer programming model. A constructive heuristic procedure is proposed for the problem. Also, the efficiency of the proposed algorithm is evaluated on 180 test problems. The obtained computational results indicate that the procedure is capable to obtain a satisfying solution.

Design and Implementation of a Combinatorial Optimization Multi-population Meta-heuristic for Solving Vehicle Routing Problems

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Eneko Osaba

2016-12-01

Full Text Available This paper aims to give a presentation of the PhD defended by Eneko Osaba on November 16th, 2015, at the University of Deusto. The thesis can be placed in the field of artificial intelligence. Specifically, it is related with multi- population meta-heuristics for solving vehicle routing problems. The dissertation was held in the main auditorium of the University, in a publicly open presentation. After the presentation, Eneko was awarded with the highest grade (cum laude. Additionally, Eneko obtained the PhD obtaining award granted by the Basque Government through.

The Pyramidal Capacitated Vehicle Routing Problem

DEFF Research Database (Denmark)

Lysgaard, Jens

This paper introduces the Pyramidal Capacitated Vehicle Routing Problem (PCVRP) as a restricted version of the Capacitated Vehicle Routing Problem (CVRP). In the PCVRP each route is required to be pyramidal in a sense generalized from the Pyramidal Traveling Salesman Problem (PTSP). A pyramidal...

The pyramidal capacitated vehicle routing problem

DEFF Research Database (Denmark)

Lysgaard, Jens

2010-01-01

This paper introduces the pyramidal capacitated vehicle routing problem (PCVRP) as a restricted version of the capacitated vehicle routing problem (CVRP). In the PCVRP each route is required to be pyramidal in a sense generalized from the pyramidal traveling salesman problem (PTSP). A pyramidal...

A heterogeneous fleet vehicle routing model for solving the LPG distribution problem: A case study

International Nuclear Information System (INIS)

Onut, S; Kamber, M R; Altay, G

2014-01-01

Vehicle Routing Problem (VRP) is an important management problem in the field of distribution and logistics. In VRPs, routes from a distribution point to geographically distributed points are designed with minimum cost and considering customer demands. All points should be visited only once and by one vehicle in one route. Total demand in one route should not exceed the capacity of the vehicle that assigned to that route. VRPs are varied due to real life constraints related to vehicle types, number of depots, transportation conditions and time periods, etc. Heterogeneous fleet vehicle routing problem is a kind of VRP that vehicles have different capacity and costs. There are two types of vehicles in our problem. In this study, it is used the real world data and obtained from a company that operates in LPG sector in Turkey. An optimization model is established for planning daily routes and assigned vehicles. The model is solved by GAMS and optimal solution is found in a reasonable time

A heterogeneous fleet vehicle routing model for solving the LPG distribution problem: A case study

Science.gov (United States)

Onut, S.; Kamber, M. R.; Altay, G.

2014-03-01

Vehicle Routing Problem (VRP) is an important management problem in the field of distribution and logistics. In VRPs, routes from a distribution point to geographically distributed points are designed with minimum cost and considering customer demands. All points should be visited only once and by one vehicle in one route. Total demand in one route should not exceed the capacity of the vehicle that assigned to that route. VRPs are varied due to real life constraints related to vehicle types, number of depots, transportation conditions and time periods, etc. Heterogeneous fleet vehicle routing problem is a kind of VRP that vehicles have different capacity and costs. There are two types of vehicles in our problem. In this study, it is used the real world data and obtained from a company that operates in LPG sector in Turkey. An optimization model is established for planning daily routes and assigned vehicles. The model is solved by GAMS and optimal solution is found in a reasonable time.

Locating Depots for Capacitated Vehicle Routing

DEFF Research Database (Denmark)

Gørtz, Inge Li; Nagarajan, Viswanath

2016-01-01

We study a location-routing problem in the context of capacitated vehicle routing. The input to the k-location capacitated vehicle routing problem (k-LocVRP) consists of a set of demand locations in a metric space and a fleet of k identical vehicles, each of capacity Q. The objective is to locate k...... depots, one for each vehicle, and compute routes for the vehicles so that all demands are satisfied and the total cost is minimized. Our main result is a constant-factor approximation algorithm for k-LocVRP. In obtaining this result, we introduce a common generalization of the k-median and minimum...... spanning tree problems (called k median forest), which might be of independent interest. We give a local-search based (3+ε)-approximation algorithm for k median forest, which leads to a (12+ε)-approximation algorithm for k-LocVRP, for any constant ε>0....

Locating Depots for Capacitated Vehicle Routing

DEFF Research Database (Denmark)

Gørtz, Inge Li; Nagarajan, Viswanath

2016-01-01

depots, one for each vehicle, and compute routes for the vehicles so that all demands are satisfied and the total cost is minimized. Our main result is a constant-factor approximation algorithm for k-LocVRP. In obtaining this result, we introduce a common generalization of the k-median and minimum...... spanning tree problems (called k median forest), which might be of independent interest. We give a local-search based (3+ε)-approximation algorithm for k median forest, which leads to a (12+ε)-approximation algorithm for k-LocVRP, for any constant ε>0.......We study a location-routing problem in the context of capacitated vehicle routing. The input to the k-location capacitated vehicle routing problem (k-LocVRP) consists of a set of demand locations in a metric space and a fleet of k identical vehicles, each of capacity Q. The objective is to locate k...

Opportunity costs calculation in agent-based vehicle routing and scheduling

NARCIS (Netherlands)

Mes, Martijn R.K.; van der Heijden, Matthijs C.; Schuur, Peter

2006-01-01

In this paper we consider a real-time, dynamic pickup and delivery problem with timewindows where orders should be assigned to one of a set of competing transportation companies. Our approach decomposes the problem into a multi-agent structure where vehicle agents are responsible for the routing and

Design of a Multi-layer Lane-Level Map for Vehicle Route Planning

Directory of Open Access Journals (Sweden)

Liu Chaoran

2017-01-01

Full Text Available With the development of intelligent transportation system, there occurs further demand for high precision localization and route planning, and simultaneously the traditional road-level map fails to meet with this requirement, by which this paper is motivated. In this paper, t he three-layer lane-level map architecture for vehicle path guidance is established, and the mathematical models of road-level layer, intermediate layer and lane-level layer are designed considering efficiency and precision. The geometric model of the lane-level layer of the map is characterized by Cubic Hermite Spline for continuity. A method of generating the lane geometry with fixed and variable control points is proposed, which can effectively ensure the accuracy with limited num ber of control points. In experimental part, a multi-layer map of an intersection is built to validate the map model, and an example of a local map was generated with the lane-level geometry.

Classification of Dynamic Vehicle Routing Systems

DEFF Research Database (Denmark)

Larsen, Allan; Madsen, Oli B.G.; Solomon, Marius M.

2007-01-01

This chapter discusses important characteristics seen within dynamic vehicle routing problems. We discuss the differences between the traditional static vehicle routing problems and its dynamic counterparts. We give an in-depth introduction to the degree of dynamism measure which can be used to c...

Improved Ant Colony Optimization for Seafood Product Delivery Routing Problem

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Baozhen Yao

2014-02-01

Full Text Available This paper deals with a real-life vehicle delivery routing problem, which is a seafood product delivery routing problem. Considering the features of the seafood product delivery routing problem, this paper formulated this problem as a multi-depot open vehicle routing problem. Since the multi-depot open vehicle routing problem is a very complex problem, a method is used to reduce the complexity of the problem by changing the multi-depot open vehicle routing problem into an open vehicle routing problem with a dummy central depot in this paper. Then, ant colony optimization is used to solve the problem. To improve the performance of the algorithm, crossover operation and some adaptive strategies are used. Finally, the computational results for the benchmark problems of the multi-depot vehicle routing problem indicate that the proposed ant colony optimization is an effective method to solve the multi-depot vehicle routing problem. Furthermore, the computation results of the seafood product delivery problem from Dalian, China also suggest that the proposed ant colony optimization is feasible to solve the seafood product delivery routing problem.

On the vehicle routing problem with time windows

DEFF Research Database (Denmark)

Kallehauge, Brian

2006-01-01

. The fourth and final paper ‘Vehicle routing problem with time windows’ (Kallehauge, Larsen, Madsen, and Solomon. In Desaulniers, Desrosiers, and Solomon, editors, Column generation, pages 67-98, Springer, New York, 2005) is a contribution to a book on column generation edited by G. Desaulniers, J. Desrosiers......The vehicle routing problem with time windows is concerned with the optimal routing of a fleet of vehicles between a depot and a number of customers that must be visited within a specified time interval, called a time window. The purpose of this thesis is to develop new and efficient solution...... techniques for solving the vehicle routing problem with time windows (VRPTW). The thesis consists of a section of introductory remarks and four independent papers. The first paper ‘Formulations and exact approaches for the vehicle routing problem with time windows’ (Kallehauge, 2005, unpublished) is a review...

Locating Depots for Capacitated Vehicle Routing

DEFF Research Database (Denmark)

Gørtz, Inge Li; Nagarajan, Viswanath

2011-01-01

that all demands are satisfied and the total cost is minimized. Our main result is a constant-factor approximation algorithm for k-LocVRP. To achieve this result, we reduce k-LocVRP to the following generalization of k median, which might be of independent interest. Given a metric (V, d), bound k...... median forest, which leads to a (12+E)-approximation algorithm for k-LocVRP, for any constant E > 0. The algorithm for k median forest is t-swap local search, and we prove that it has locality gap 3 + 2 t ; this generalizes the corresponding result for k median [3]. Finally we consider the k median......We study a location-routing problem in the context of capacitated vehicle routing. The input to k-LocVRP is a set of demand locations in a metric space and a fleet of k vehicles each of capacity Q. The objective is to locate k depots, one for each vehicle, and compute routes for the vehicles so...

The Time-Dependent Multiple-Vehicle Prize-Collecting Arc Routing Problem

DEFF Research Database (Denmark)

Black, Daniel; Eglese, Richard; Wøhlk, Sanne

2015-01-01

-life traffic situations where the travel times change with the time of day are taken into account. Two metaheuristic algorithms, one based on Variable Neighborhood Search and one based on Tabu Search, are proposed and tested for a set of benchmark problems, generated from real road networks and travel time......In this paper, we introduce a multi vehicle version of the Time-Dependent Prize-Collecting Arc Routing Problem (TD-MPARP). It is inspired by a situation where a transport manager has to choose between a number of full truck load pick-ups and deliveries to be performed by a fleet of vehicles. Real...

Analysis of an Automated Vehicle Routing Problem in Logistics considering Path Interruption

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Yong Zhang

2017-01-01

Full Text Available The application of automated vehicles in logistics can efficiently reduce the cost of logistics and reduce the potential risks in the last mile. Considering the path restriction in the initial stage of the application of automated vehicles in logistics, the conventional model for a vehicle routing problem (VRP is modified. Thus, the automated vehicle routing problem with time windows (AVRPTW model considering path interruption is established. Additionally, an improved particle swarm optimisation (PSO algorithm is designed to solve this problem. Finally, a case study is undertaken to test the validity of the model and the algorithm. Four automated vehicles are designated to execute all delivery tasks required by 25 stores. Capacities of all of the automated vehicles are almost fully utilised. It is of considerable significance for the promotion of automated vehicles in last-mile situations to develop such research into real problems arising in the initial period.

The Time Window Vehicle Routing Problem Considering Closed Route

Science.gov (United States)

Irsa Syahputri, Nenna; Mawengkang, Herman

2017-12-01

The Vehicle Routing Problem (VRP) determines the optimal set of routes used by a fleet of vehicles to serve a given set of customers on a predefined graph; the objective is to minimize the total travel cost (related to the travel times or distances) and operational cost (related to the number of vehicles used). In this paper we study a variant of the predefined graph: given a weighted graph G and vertices a and b, and given a set X of closed paths in G, find the minimum total travel cost of a-b path P such that no path in X is a subpath of P. Path P is allowed to repeat vertices and edges. We use integer programming model to describe the problem. A feasible neighbourhood approach is proposed to solve the model

Time and timing in vehicle routing problems

NARCIS (Netherlands)

Jabali, O.

2010-01-01

The distribution of goods to a set of geographically dispersed customers is a common problem faced by carrier companies, well-known as the Vehicle Routing Problem (VRP). The VRP consists of finding an optimal set of routes that minimizes total travel times for a given number of vehicles with a fixed

Dynamic route guidance strategy in a two-route pedestrian-vehicle mixed traffic flow system

Science.gov (United States)

Liu, Mianfang; Xiong, Shengwu; Li, Bixiang

2016-05-01

With the rapid development of transportation, traffic questions have become the major issue for social, economic and environmental aspects. Especially, during serious emergencies, it is very important to alleviate road traffic congestion and improve the efficiency of evacuation to reduce casualties, and addressing these problems has been a major task for the agencies responsible in recent decades. Advanced road guidance strategies have been developed for homogeneous traffic flows, or to reduce traffic congestion and enhance the road capacity in a symmetric two-route scenario. However, feedback strategies have rarely been considered for pedestrian-vehicle mixed traffic flows with variable velocities and sizes in an asymmetric multi-route traffic system, which is a common phenomenon in many developing countries. In this study, we propose a weighted road occupancy feedback strategy (WROFS) for pedestrian-vehicle mixed traffic flows, which considers the system equilibrium to ease traffic congestion. In order to more realistic simulating the behavior of mixed traffic objects, the paper adopted a refined and dynamic cellular automaton model (RDPV_CA model) as the update mechanism for pedestrian-vehicle mixed traffic flow. Moreover, a bounded rational threshold control was introduced into the feedback strategy to avoid some negative effect of delayed information and reduce. Based on comparisons with the two previously proposed strategies, the simulation results obtained in a pedestrian-vehicle traffic flow scenario demonstrated that the proposed strategy with a bounded rational threshold was more effective and system equilibrium, system stability were reached.

Vehicle Routing With User Generated Trajectory Data

DEFF Research Database (Denmark)

Ceikute, Vaida; Jensen, Christian S.

Rapidly increasing volumes of GPS data collected from vehicles provide new and increasingly comprehensive insight into the routes that drivers prefer. While routing services generally compute shortest or fastest routes, recent studies suggest that local drivers often prefer routes that are neithe...

Optimizing departure times in vehicle routes

NARCIS (Netherlands)

Kok, A.L.; Hans, Elias W.; Schutten, Johannes M.J.

2008-01-01

Most solution methods for the vehicle routing problem with time windows (VRPTW) develop routes from the earliest feasible departure time. However, in practice, temporal traffic congestions make that such solutions are not optimal with respect to minimizing the total duty time. Furthermore, VRPTW

Joint optimization of green vehicle scheduling and routing problem with time-varying speeds

Science.gov (United States)

Zhang, Dezhi; Wang, Xin; Ni, Nan; Zhang, Zhuo

2018-01-01

Based on an analysis of the congestion effect and changes in the speed of vehicle flow during morning and evening peaks in a large- or medium-sized city, the piecewise function is used to capture the rules of the time-varying speed of vehicles, which are very important in modelling their fuel consumption and CO2 emission. A joint optimization model of the green vehicle scheduling and routing problem with time-varying speeds is presented in this study. Extra wages during nonworking periods and soft time-window constraints are considered. A heuristic algorithm based on the adaptive large neighborhood search algorithm is also presented. Finally, a numerical simulation example is provided to illustrate the optimization model and its algorithm. Results show that, (1) the shortest route is not necessarily the route that consumes the least energy, (2) the departure time influences the vehicle fuel consumption and CO2 emissions and the optimal departure time saves on fuel consumption and reduces CO2 emissions by up to 5.4%, and (3) extra driver wages have significant effects on routing and departure time slot decisions. PMID:29466370

A location-routing problem model with multiple periods and fuzzy demands

Directory of Open Access Journals (Sweden)

Ali Nadizadeh

2014-08-01

Full Text Available This paper puts forward a dynamic capacitated location-routing problem with fuzzy demands (DCLRP-FD. It is given on input a set of identical vehicles (each having a capacity, a fixed cost and availability level, a set of depots with restricted capacities and opening costs, a set of customers with fuzzy demands, and a planning horizon with multiple periods. The problem consists of determining the depots to be opened only in the first period of the planning horizon, the customers and the vehicles to be assigned to each opened depot, and performing the routes that may be changed in each time period due to fuzzy demands. A fuzzy chance-constrained programming (FCCP model has been designed using credibility theory and a hybrid heuristic algorithm with four phases is presented in order to solve the problem. To obtain the best value of the fuzzy parameters of the model and show the influence of the availability level of vehicles on final solution, some computational experiments are carried out. The validity of the model is then evaluated in contrast with CLRP-FD's models in the literature. The results indicate that the model and the proposed algorithm are robust and could be used in real world problems.

Optimizing Departure Times in Vehicle Routes

NARCIS (Netherlands)

Kok, A.L.; Hans, Elias W.; Schutten, Johannes M.J.

2011-01-01

Most solution methods for the vehicle routing problem with time windows (VRPTW) develop routes from the earliest feasible departure time. In practice, however, temporary traffic congestion make such solutions non-optimal with respect to minimizing the total duty time. Furthermore, the VRPTW does not

Navigation API Route Fuel Saving Opportunity Assessment on Large-Scale Real-World Travel Data for Conventional Vehicles and Hybrid Electric Vehicles: Preprint

Energy Technology Data Exchange (ETDEWEB)

Zhu, Lei [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Holden, Jacob [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Gonder, Jeffrey D [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

2017-12-06

The green routing strategy instructing a vehicle to select a fuel-efficient route benefits the current transportation system with fuel-saving opportunities. This paper introduces a navigation API route fuel-saving evaluation framework for estimating fuel advantages of alternative API routes based on large-scale, real-world travel data for conventional vehicles (CVs) and hybrid electric vehicles (HEVs). The navigation APIs, such Google Directions API, integrate traffic conditions and provide feasible alternative routes for origin-destination pairs. This paper develops two link-based fuel-consumption models stratified by link-level speed, road grade, and functional class (local/non-local), one for CVs and the other for HEVs. The link-based fuel-consumption models are built by assigning travel from a large number of GPS driving traces to the links in TomTom MultiNet as the underlying road network layer and road grade data from a U.S. Geological Survey elevation data set. Fuel consumption on a link is calculated by the proposed fuel consumption model. This paper envisions two kinds of applications: 1) identifying alternate routes that save fuel, and 2) quantifying the potential fuel savings for large amounts of travel. An experiment based on a large-scale California Household Travel Survey GPS trajectory data set is conducted. The fuel consumption and savings of CVs and HEVs are investigated. At the same time, the trade-off between fuel saving and time saving for choosing different routes is also examined for both powertrains.

Routing Cooperating Vehicles to Perform Precedence-Linked Tasks

National Research Council Canada - National Science Library

Vakhutinsky, Andrew; Wu, Cynara

2005-01-01

The problem of scheduling cooperating vehicles is a generalization of the classical vehicle routing problem where certain tasks are linked by precedence constraints and vehicles have varying constrained resources...

Implementation of Cooperation for Recycling Vehicle Routing Optimization in Two-Echelon Reverse Logistics Networks

Directory of Open Access Journals (Sweden)

Yong Wang

2018-04-01

Full Text Available The formation of a cooperative alliance is an effective means of approaching the vehicle routing optimization in two-echelon reverse logistics networks. Cooperative mechanisms can contribute to avoiding the inefficient assignment of resources for the recycling logistics operations and reducing long distance transportation. With regard to the relatively low performance of waste collection, this paper proposes a three-phase methodology to properly address the corresponding vehicle routing problem on two echelons. First, a bi-objective programming model is established to minimize the total cost and the number of vehicles considering semitrailers and vehicles sharing. Furthermore, the Clarke–Wright (CW savings method and the Non-dominated Sorting Genetic Algorithm-II (NSGA-II are combined to design a hybrid routing optimization heuristic, which is denoted CW_NSGA-II. Routes on the first and second echelons are obtained on the basis of sub-optimal solutions provided by CW algorithm. Compared to other intelligent algorithms, CW_NSGA-II reduces the complexity of the multi-objective solutions search and mostly converges to optimality. The profit generated by cooperation among retail stores and the recycling hub in the reverse logistics network is fairly and reasonably distributed to the participants by applying the Minimum Costs-Remaining Savings (MCRS method. Finally, an empirical study in Chengdu City, China, reveals the superiority of CW_NSGA over the multi-objective particle swarm optimization and the multi objective genetic algorithms in terms of solutions quality and convergence. Meanwhile, the comparison of MCRS method with the Shapley value model, equal profit method and cost gap allocation proves that MCRS method is more conducive to the stability of the cooperative alliance. In general, the implementation of cooperation in the optimization of the reverse logistics network effectively leads to the sustainable development of urban and sub

Dynamic vehicle routing problems: Three decades and counting

DEFF Research Database (Denmark)

Psaraftis, Harilaos N.; Wen, Min; Kontovas, Christos A.

2016-01-01

of DVRP papers according to 11 criteria. These are (1) type of problem, (2) logistical context, (3) transportation mode, (4) objective function, (5) fleet size, (6) time constraints, (7) vehicle capacity constraints, (8) the ability to reject customers, (9) the natureof the dynamic element, (10......Since the late 70s, much research activity has taken place on the class of dynamic vehicle routing problems (DVRP), with the time period after year 2000 witnessing areal explosion in related papers. Our paper sheds more light into work in this area over more than 3 decades by developing a taxonomy......) the nature of the stochasticity (if any), and (11) the solution method. We comment on technological vis-à-vis methodological advances for this class of problems and suggest directions for further research. The latter include alternative objective functions, vehicle speed as decision variable, more explicit...

A Column Generation for the Heterogeneous Fixed Fleet Open Vehicle Routing Problem

Directory of Open Access Journals (Sweden)

Majid Yousefikhoshbakht

2017-07-01

Full Text Available This paper addressed the heterogeneous fixed fleet open vehicle routing problem (HFFOVRP, in which the vehicles are not required to return to the depot after completing a service. In this new problem, the demands of customers are fulfilled by a heterogeneous fixed fleet of vehicles having various capacities, fixed costs and variable costs. This problem is an important variant of the open vehicle routing problem (OVRP and can cover more practical situations in transportation and logistics. Since this problem belongs to NP-hard Problems, An approach based on column generation (CG is applied to solve the HFFOVRP. A tight integer programming model is presented and the linear programming relaxation of which is solved by the CG technique. Since there have been no existing benchmarks, this study generated 19 test problems and the results of the proposed CG algorithm is compared to the results of exact algorithm. Computational experience confirms that the proposed algorithm can provide better solutions within a comparatively shorter period of time.

Vehicle routing with dynamic travel times : a queueing approach

NARCIS (Netherlands)

Woensel, van T.; Kerbache, L.; Peremans, H.; Vandaele, N.J.

2008-01-01

Transportation is an important component of supply chain competitiveness since it plays a major role in the inbound, inter-facility, and outbound logistics. In this context, assigning and scheduling vehicle routes is a crucial management problem. In this paper, a vehicle routing problem with dynamic

Routing of Electric Vehicles: City Distribution in Copenhagen

DEFF Research Database (Denmark)

Linde, Esben; Larsen, Allan; Nørrelund, Anders Vedsted

In this work, a Vehicle Routing Problem with Time Windows considering EV constraints of limited driving range and freight capacity is addressed (EVRPTW). The EVs are allowed to recharge at certain locations, and aspects of intelligent location of these recharging points are considered....... The objective is to find the least cost plan for EV routing and compare this to conventional routing. A heuristic method is developed and tested on data based on real-life collected data on distribution vehicles in central Copenhagen, Denmark. The EVRPTW has so far received little attention in the literature...

A Multi-Depot Two-Echelon Vehicle Routing Problem with Delivery Options Arising in the Last Mile Distribution

NARCIS (Netherlands)

Zhou, Lin; Baldacci, Roberto; Vigo, Daniele; Wang, Xu

2018-01-01

In this paper, we introduce a new city logistics problem arising in the last mile distribution of e-commerce. The problem involves two levels of routing problems. The first requires a design of the routes for a vehicle fleet located at the depots to transport the customer demands to a subset of the

The vehicle routing problem latest advances and new challenges

CERN Document Server

Golden, Bruce L; Wasil, Edward A

2008-01-01

The Vehicle Routing Problem (VRP) has been an especially active and fertile area of research. Over the past five to seven years, there have been numerous technological advances and exciting challenges that are of considerable interest to students, teachers, and researchers. The Vehicle Routing Problem: Latest Advances and New Challenges will focus on a host of significant technical advances that have evolved over the past few years for modeling and solving vehicle routing problems and variants. New approaches for solving VRPs have been developed from important methodological advances. These developments have resulted in faster solution algorithms, more accurate techniques, and an improvement in the ability to solve large-scale, complex problems. The book will systematically examine these recent developments in the VRP and provide the following in a unified and carefully developed presentation: Present novel problems that have arisen in the vehicle routing domain and highlight new challenges for the field; Pre...

A branch-and-cut algorithm for the vehicle routing problem with multiple use of vehicles

Directory of Open Access Journals (Sweden)

İsmail Karaoğlan

2015-06-01

Full Text Available This paper addresses the vehicle routing problem with multiple use of vehicles (VRPMUV, an important variant of the classic vehicle routing problem (VRP. Unlike the classical VRP, vehicles are allowed to use more than one route in the VRPMUV. We propose a branch-and-cut algorithm for solving the VRPMUV. The proposed algorithm includes several valid inequalities from the literature for the purpose of improving its lower bounds, and a heuristic algorithm based on simulated annealing and a mixed integer programming-based intensification procedure for obtaining the upper bounds. The algorithm is evaluated in terms of the test problems derived from the literature. The computational results which follow show that, if there were 120 customers on the route (in the simulation, the problem would be solved optimally in a reasonable amount of time.

New mathematical modeling for a location-routing-inventory problem in a multi-period closed-loop supply chain in a car industry

Science.gov (United States)

Forouzanfar, F.; Tavakkoli-Moghaddam, R.; Bashiri, M.; Baboli, A.; Hadji Molana, S. M.

2017-11-01

This paper studies a location-routing-inventory problem in a multi-period closed-loop supply chain with multiple suppliers, producers, distribution centers, customers, collection centers, recovery, and recycling centers. In this supply chain, centers are multiple levels, a price increase factor is considered for operational costs at centers, inventory and shortage (including lost sales and backlog) are allowed at production centers, arrival time of vehicles of each plant to its dedicated distribution centers and also departure from them are considered, in such a way that the sum of system costs and the sum of maximum time at each level should be minimized. The aforementioned problem is formulated in the form of a bi-objective nonlinear integer programming model. Due to the NP-hard nature of the problem, two meta-heuristics, namely, non-dominated sorting genetic algorithm (NSGA-II) and multi-objective particle swarm optimization (MOPSO), are used in large sizes. In addition, a Taguchi method is used to set the parameters of these algorithms to enhance their performance. To evaluate the efficiency of the proposed algorithms, the results for small-sized problems are compared with the results of the ɛ-constraint method. Finally, four measuring metrics, namely, the number of Pareto solutions, mean ideal distance, spacing metric, and quality metric, are used to compare NSGA-II and MOPSO.

Discrete Optimization Model for Vehicle Routing Problem with Scheduling Side Cosntraints

Science.gov (United States)

Juliandri, Dedy; Mawengkang, Herman; Bu'ulolo, F.

2018-01-01

Vehicle Routing Problem (VRP) is an important element of many logistic systems which involve routing and scheduling of vehicles from a depot to a set of customers node. This is a hard combinatorial optimization problem with the objective to find an optimal set of routes used by a fleet of vehicles to serve the demands a set of customers It is required that these vehicles return to the depot after serving customers’ demand. The problem incorporates time windows, fleet and driver scheduling, pick-up and delivery in the planning horizon. The goal is to determine the scheduling of fleet and driver and routing policies of the vehicles. The objective is to minimize the overall costs of all routes over the planning horizon. We model the problem as a linear mixed integer program. We develop a combination of heuristics and exact method for solving the model.

Commercial vehicle route tracking using video detection.

Science.gov (United States)

2010-10-31

Interstate commercial vehicle traffic is a major factor in the life of any road surface. The ability to track : these vehicles and their routes through the state can provide valuable information to planning : activities. We propose a method using vid...

Enhanced intelligent water drops algorithm for multi-depot vehicle routing problem.

Science.gov (United States)

Ezugwu, Absalom E; Akutsah, Francis; Olusanya, Micheal O; Adewumi, Aderemi O

2018-01-01

The intelligent water drop algorithm is a swarm-based metaheuristic algorithm, inspired by the characteristics of water drops in the river and the environmental changes resulting from the action of the flowing river. Since its appearance as an alternative stochastic optimization method, the algorithm has found applications in solving a wide range of combinatorial and functional optimization problems. This paper presents an improved intelligent water drop algorithm for solving multi-depot vehicle routing problems. A simulated annealing algorithm was introduced into the proposed algorithm as a local search metaheuristic to prevent the intelligent water drop algorithm from getting trapped into local minima and also improve its solution quality. In addition, some of the potential problematic issues associated with using simulated annealing that include high computational runtime and exponential calculation of the probability of acceptance criteria, are investigated. The exponential calculation of the probability of acceptance criteria for the simulated annealing based techniques is computationally expensive. Therefore, in order to maximize the performance of the intelligent water drop algorithm using simulated annealing, a better way of calculating the probability of acceptance criteria is considered. The performance of the proposed hybrid algorithm is evaluated by using 33 standard test problems, with the results obtained compared with the solutions offered by four well-known techniques from the subject literature. Experimental results and statistical tests show that the new method possesses outstanding performance in terms of solution quality and runtime consumed. In addition, the proposed algorithm is suitable for solving large-scale problems.

An inventory location routing model with environmental considerations

Directory of Open Access Journals (Sweden)

Lerhlaly Sanaa

2017-01-01

Full Text Available In this work we consider an integrated Inventory Location Routing problem ILRP. The objective is to select depots to open, the routes to perform distribution from the capacitated depots to the clients by a homogeneous fleet of vehicles and over a multi-period planning horizon. To solve the problem, an exact model is designed in order to minimize the total cost (location, routing and inventory and the routing CO2 emissions, while respecting transport and storage constraints for a hazardous material. We have also studied an industrial real case to illustrate the problem.

Route-Based Signal Preemption Control of Emergency Vehicle

Directory of Open Access Journals (Sweden)

Haibo Mu

2018-01-01

Full Text Available This paper focuses on the signal preemption control of emergency vehicles (EV. A signal preemption control method based on route is proposed to reduce time delay of EV at intersections. According to the time at which EV is detected and the current phase of each intersection on the travelling route of EV, the calculation methods of the earliest start time and the latest start time of green light at each intersection are given. Consequently, the effective time range of green light at each intersection is determined in theory. A multiobjective programming model, whose objectives are the minimal residence time of EV at all intersections and the maximal passing numbers of general society vehicles, is presented. Finally, a simulation calculation is carried out. Calculation results indicate that, by adopting the signal preemption method based on route, the delay of EV is reduced and the number of society vehicles passing through the whole system is increased. The signal preemption control method of EV based on route can reduce the time delay of EV and improve the evacuation efficiency of the system.

Optimization Using Simulation of the Vehicle Routing Problem

OpenAIRE

Nayera E. El-Gharably; Khaled S. El-Kilany; Aziz E. El-Sayed

2013-01-01

A key element of many distribution systems is the routing and scheduling of vehicles servicing a set of customers. A wide variety of exact and approximate algorithms have been proposed for solving the vehicle routing problems (VRP). Exact algorithms can only solve relatively small problems of VRP, which is classified as NP-Hard. Several approximate algorithms have proven successful in finding a feasible solution not necessarily optimum. Although different parts of the pro...

Congestion avoidance and break scheduling within vehicle routing

NARCIS (Netherlands)

Kok, A.L.

2010-01-01

Vehicle routing is a complex daily task for businesses such as logistic service providers and distribution firms. Planners have to assign many orders to many vehicles and, for each vehicle, assign a delivery sequence. The objective is to minimize total transport costs. These costs typically include

Research on the optimization of vehicle distribution routes in logistics enterprises

Science.gov (United States)

Fan, Zhigou; Ma, Mengkun

2018-01-01

With the rapid development of modern logistics, the vehicle routing problem has become one of the urgent problems in the logistics industry. The rationality of distribution route planning directly affects the efficiency and quality of logistics distribution. This paper first introduces the definition of logistics distribution and the three methods of optimizing the distribution routes, and then analyzes the current vehicle distribution route by using a representative example, finally puts forward the optimization schemes of logistics distribution route.

The Emergency Vehicle Routing Problem with Uncertain Demand under Sustainability Environments

Directory of Open Access Journals (Sweden)

Jin Qin

2017-02-01

Full Text Available The reasonable utilization of limited resources is critical to realize the sustainable developments. In the initial 72-h crucial rescue period after the disaster, emergency supplies have always been insufficient and the demands in the affected area have always been uncertain. In order to improve timeliness, utilization and sustainability of emergency service, the allocation of the emergency supplies and the emergency vehicle routes should be determined simultaneously. Assuming the uncertain demands follow normal distribution, an optimization model for the emergency vehicle routing, by considering the insufficient supplies and the uncertain demands, is developed. The objective function is applied to minimize the total costs, including the penalty costs induced by more or less supplies than the actual demands at all demand points, as well as the constraints of the time windows and vehicle load capacity taken into account. In more details, a solution method for the model, based on the genetic algorithm, is proposed, which solves the problem in two stages. A numerical example is presented to demonstrate the efficiency and validity of the proposed model and algorithm.

The Linehaul-Feeder Vehicle Routing Problem with Virtual Depots and Time Windows

Directory of Open Access Journals (Sweden)

Huey-Kuo Chen

2011-01-01

Full Text Available This paper addresses the linehaul-feeder vehicle routing problem with virtual depots and time windows (LFVRPTW. Small and large vehicles deliver services to customers within time constraints; small vehicles en route may reload commodities from either the physical depot or from the larger vehicle at a virtual depot before continuing onward. A two-stage solution heuristic involving Tabu search is proposed to solve this problem. The test results show that the LFVRPTW performs better than the vehicle routing problem with time windows in terms of both objective value and the number of small vehicles dispatched.

Energy integration on multi-periods and multi-usages for hybrid electric and thermal powertrains

International Nuclear Information System (INIS)

Dimitrova, Zlatina; Maréchal, François

2015-01-01

The improvement of the efficiency of vehicle energy systems promotes an active search to find innovative solutions during the design process. This requires more accurate modeling of complex systems, which offers new ways to improve the design efficiency of energy systems. The vehicle is a highly dynamic system. The size and the efficiency of the convertors are dependent on the dynamic driving profile. In order to increase the energy efficiency, using energy integration techniques, an adapted methodology is required to choose the best points for the integrated system design. The idea is to clusterize the dynamic profile on typical multi-periods of the vehicle use. The energy system design is then optimized for these typical multi-periods. In this article a new methodology is applied on hybrid electric vehicles, in order to define the energy integrated powertrain configuration of the vehicle. The energy recovery potential of a single stage Organic Rankine Cycle for a thermal engine in combination with a hybrid electric powertrain is assessed for different drive cycles profiles and comfort situations. After the energy integration, a multi-objective optimization is applied to define the optimal design of a hybrid electric vehicle with a waste heat recovery system. - Highlights: • K-means algorithm transforms the dynamic driving profile on static multi-periods. • The clusters represent the typical powertrain use and size the heat recovery utility. • The maximal heat recovery potential on thermal powertrains is 11% for urban driving. • The maximal heat recovery potential on hybrid electric powertrains is 5%. • Engine downsizing increases heat recovery potential on hybrid electric powertrains

Fund allocation using capacitated vehicle routing problem

Science.gov (United States)

Mamat, Nur Jumaadzan Zaleha; Jaaman, Saiful Hafizah; Ahmad, Rokiah Rozita; Darus, Maslina

2014-09-01

In investment fund allocation, it is unwise for an investor to distribute his fund into several assets simultaneously due to economic reasons. One solution is to allocate the fund into a particular asset at a time in a sequence that will either maximize returns or minimize risks depending on the investor's objective. The vehicle routing problem (VRP) provides an avenue to this issue. VRP answers the question on how to efficiently use the available fleet of vehicles to meet a given service demand, subjected to a set of operational requirements. This paper proposes an idea of using capacitated vehicle routing problem (CVRP) to optimize investment fund allocation by employing data of selected stocks in the FTSE Bursa Malaysia. Results suggest that CRVP can be applied to solve the issue of investment fund allocation and increase the investor's profit.

Performansi Algoritma CODEQ dalam Penyelesaian Vehicle Routing Problem

Directory of Open Access Journals (Sweden)

Annisa Kesy Garside

2014-01-01

Full Text Available Genetic Algorithm, Tabu Search, Simulated Annealing, and Ant Colony Optimization showed a good performance in solving vehicle routing problem. However, the generated solution of those algorithms was changeable regarding on the input parameter of each algorithm. CODEQ is a new, parameter free meta-heuristic algorithm that had been successfully used to solve constrained optimization problems, integer programming, and feed-forward neural network. The purpose of this research are improving CODEQ algorithm to solve vehicle routing problem and testing the performance of the improved algorithm. CODEQ algorithm is started with population initiation as initial solution, generated of mutant vector for each parent in every iteration, replacement of parent by mutant when fitness function value of mutant is better than parent’s, generated of new vector for each iteration based on opposition value or chaos principle, replacement of worst solution by new vector when fitness function value of new vector is better, iteration ceasing when stooping criterion is achieved, and sub-tour determination based on vehicle capacity constraint. The result showed that the average deviation of the best-known and the best-test value is 6.35%. Therefore, CODEQ algorithm is good in solving vehicle routing problem.

Multicriteria vehicle routing problem solved by artificial immune system

Directory of Open Access Journals (Sweden)

Bogna MRÓWCZYŃSKA

2015-09-01

Full Text Available Vehicles route planning in large transportation companies, where drivers are workers, usually takes place on the basis of experience or intuition of the employees. Because of the cost and environmental protection, it is important to save fuel, thus planning routes in an optimal way. In this article an example of the problem is presented solving delivery vans route planning taking into account the distance and travel time within the constraints of vehicle capacities, restrictions on working time of drivers and having varying degrees of movement. An artificial immune system was used for the calculations.

Optimizing investment fund allocation using vehicle routing problem framework

Science.gov (United States)

Mamat, Nur Jumaadzan Zaleha; Jaaman, Saiful Hafizah; Ahmad, Rokiah Rozita

2014-07-01

The objective of investment is to maximize total returns or minimize total risks. To determine the optimum order of investment, vehicle routing problem method is used. The method which is widely used in the field of resource distribution shares almost similar characteristics with the problem of investment fund allocation. In this paper we describe and elucidate the concept of using vehicle routing problem framework in optimizing the allocation of investment fund. To better illustrate these similarities, sectorial data from FTSE Bursa Malaysia is used. Results show that different values of utility for risk-averse investors generate the same investment routes.

Optimization for routing vehicles of seafood product transportation

Science.gov (United States)

Soenandi, I. A.; Juan, Y.; Budi, M.

2017-12-01

Recently, increasing usage of marine products is creating new challenges for businesses of marine products in terms of transportation that used to carry the marine products like seafood to the main warehouse. This can be a problem if the carrier fleet is limited, and there are time constraints in terms of the freshness of the marine product. There are many ways to solve this problem, including the optimization of routing vehicles. In this study, this strategy is to implement in the marine product business in Indonesia with such an expected arrangement of the company to optimize routing problem in transportation with time and capacity windows. Until now, the company has not used the scientific method to manage the routing of their vehicle from warehouse to the location of marine products source. This study will solve a stochastic Vehicle Routing Problems (VRP) with time and capacity windows by using the comparison of six methods and looking the best results for the optimization, in this situation the company could choose the best method, in accordance with the existing condition. In this research, we compared the optimization with another method such as branch and bound, dynamic programming and Ant Colony Optimization (ACO). Finally, we get the best result after running ACO algorithm with existing travel time data. With ACO algorithm was able to reduce vehicle travel time by 3189.65 minutes, which is about 23% less than existing and based on consideration of the constraints of time within 2 days (including rest time for the driver) using 28 tons capacity of truck and the companies need two units of vehicles for transportation.

An adaptive large neighborhood search heuristic for Two-Echelon Vehicle Routing Problems arising in city logistics

Science.gov (United States)

Hemmelmayr, Vera C.; Cordeau, Jean-François; Crainic, Teodor Gabriel

2012-01-01

In this paper, we propose an adaptive large neighborhood search heuristic for the Two-Echelon Vehicle Routing Problem (2E-VRP) and the Location Routing Problem (LRP). The 2E-VRP arises in two-level transportation systems such as those encountered in the context of city logistics. In such systems, freight arrives at a major terminal and is shipped through intermediate satellite facilities to the final customers. The LRP can be seen as a special case of the 2E-VRP in which vehicle routing is performed only at the second level. We have developed new neighborhood search operators by exploiting the structure of the two problem classes considered and have also adapted existing operators from the literature. The operators are used in a hierarchical scheme reflecting the multi-level nature of the problem. Computational experiments conducted on several sets of instances from the literature show that our algorithm outperforms existing solution methods for the 2E-VRP and achieves excellent results on the LRP. PMID:23483764

An adaptive large neighborhood search heuristic for Two-Echelon Vehicle Routing Problems arising in city logistics.

Science.gov (United States)

Hemmelmayr, Vera C; Cordeau, Jean-François; Crainic, Teodor Gabriel

2012-12-01

In this paper, we propose an adaptive large neighborhood search heuristic for the Two-Echelon Vehicle Routing Problem (2E-VRP) and the Location Routing Problem (LRP). The 2E-VRP arises in two-level transportation systems such as those encountered in the context of city logistics. In such systems, freight arrives at a major terminal and is shipped through intermediate satellite facilities to the final customers. The LRP can be seen as a special case of the 2E-VRP in which vehicle routing is performed only at the second level. We have developed new neighborhood search operators by exploiting the structure of the two problem classes considered and have also adapted existing operators from the literature. The operators are used in a hierarchical scheme reflecting the multi-level nature of the problem. Computational experiments conducted on several sets of instances from the literature show that our algorithm outperforms existing solution methods for the 2E-VRP and achieves excellent results on the LRP.

Vehicle Routing Problems for Drone Delivery

OpenAIRE

Dorling, Kevin; Heinrichs, Jordan; Messier, Geoffrey G.; Magierowski, Sebastian

2016-01-01

Unmanned aerial vehicles, or drones, have the potential to significantly reduce the cost and time of making last-mile deliveries and responding to emergencies. Despite this potential, little work has gone into developing vehicle routing problems (VRPs) specifically for drone delivery scenarios. Existing VRPs are insufficient for planning drone deliveries: either multiple trips to the depot are not permitted, leading to solutions with excess drones, or the effect of battery and payload weight ...

An optimization algorithm for a capacitated vehicle routing problem ...

Indian Academy of Sciences (India)

In this paper, vehicle routing problem (VRP) with time windows and real world constraints are considered as a real-world application on google maps. Also, tabu search is used and Hopfield neural networks is utilized. Basic constraints consist of customer demands, time windows, vehicle speed, vehicle capacity andworking ...

METHOD OF CHOOSING THE TECHNOLOGY OF VEHICLE OPERATION ON DELIVERY ROUTES

Directory of Open Access Journals (Sweden)

Ye. Nagornyi

2014-10-01

Full Text Available A method for determining the technology of vehicles operation on delivery (team routes, which allows to determine the optimal sequence of cargo delivery to customers by vehicles of certain capacity in order to meet the requirements of cargo owners regarding the conditions of service is offered. Recommendations for creation of an automated system of forming the technology of vehicles operation on delivery routes are developed.

Optimum Route Planning and Scheduling for Unmanned Aerial Vehicles

National Research Council Canada - National Science Library

Sonmezocak, Erkan; Kurt, Senol

2008-01-01

.... The route planning of UAVs is the most critical and challenging problem of wartime. This thesis will develop three algorithms to solve a model that produces executable routings in order to dispatch three Unmanned Aerial Vehicles (UAV...

Using Grey Wolf Algorithm to Solve the Capacitated Vehicle Routing Problem

Science.gov (United States)

Korayem, L.; Khorsid, M.; Kassem, S. S.

2015-05-01

The capacitated vehicle routing problem (CVRP) is a class of the vehicle routing problems (VRPs). In CVRP a set of identical vehicles having fixed capacities are required to fulfill customers' demands for a single commodity. The main objective is to minimize the total cost or distance traveled by the vehicles while satisfying a number of constraints, such as: the capacity constraint of each vehicle, logical flow constraints, etc. One of the methods employed in solving the CVRP is the cluster-first route-second method. It is a technique based on grouping of customers into a number of clusters, where each cluster is served by one vehicle. Once clusters are formed, a route determining the best sequence to visit customers is established within each cluster. The recently bio-inspired grey wolf optimizer (GWO), introduced in 2014, has proven to be efficient in solving unconstrained, as well as, constrained optimization problems. In the current research, our main contributions are: combining GWO with the traditional K-means clustering algorithm to generate the ‘K-GWO’ algorithm, deriving a capacitated version of the K-GWO algorithm by incorporating a capacity constraint into the aforementioned algorithm, and finally, developing 2 new clustering heuristics. The resulting algorithm is used in the clustering phase of the cluster-first route-second method to solve the CVR problem. The algorithm is tested on a number of benchmark problems with encouraging results.

Routing Unmanned Vehicles in GPS-Denied Environments

OpenAIRE

Sundar, Kaarthik; Misra, Sohum; Rathinam, Sivakumar; Sharma, Rajnikant

2017-01-01

Most of the routing algorithms for unmanned vehicles, that arise in data gathering and monitoring applications in the literature, rely on the Global Positioning System (GPS) information for localization. However, disruption of GPS signals either intentionally or unintentionally could potentially render these algorithms not applicable. In this article, we present a novel method to address this difficulty by combining methods from cooperative localization and routing. In particular, the article...

A green vehicle routing problem with customer satisfaction criteria

Science.gov (United States)

Afshar-Bakeshloo, M.; Mehrabi, A.; Safari, H.; Maleki, M.; Jolai, F.

2016-12-01

This paper develops an MILP model, named Satisfactory-Green Vehicle Routing Problem. It consists of routing a heterogeneous fleet of vehicles in order to serve a set of customers within predefined time windows. In this model in addition to the traditional objective of the VRP, both the pollution and customers' satisfaction have been taken into account. Meanwhile, the introduced model prepares an effective dashboard for decision-makers that determines appropriate routes, the best mixed fleet, speed and idle time of vehicles. Additionally, some new factors evaluate the greening of each decision based on three criteria. This model applies piecewise linear functions (PLFs) to linearize a nonlinear fuzzy interval for incorporating customers' satisfaction into other linear objectives. We have presented a mixed integer linear programming formulation for the S-GVRP. This model enriches managerial insights by providing trade-offs between customers' satisfaction, total costs and emission levels. Finally, we have provided a numerical study for showing the applicability of the model.

Approximation Algorithm for a Heterogeneous Vehicle Routing Problem

Directory of Open Access Journals (Sweden)

Jungyun Bae

2015-08-01

Full Text Available This article addresses a fundamental path planning problem which aims to route a collection of heterogeneous vehicles such that each target location is visited by some vehicle and the sum of the travel costs of the vehicles is minimal. Vehicles are heterogeneous as the cost of traveling between any two locations depends on the type of the vehicle. Algorithms are developed for this path planning problem with bounds on the quality of the solutions produced by the algorithms. Computational results show that high quality solutions can be obtained for the path planning problem involving four vehicles and 40 targets using the proposed approach.

Real time monitoring system used in route planning for the electric vehicle

Science.gov (United States)

Ionescu, LM; Mazare, A.; Serban, G.; Ionita, S.

2017-10-01

The electric vehicle is a new consumer of electricity that is becoming more and more widespread. Under these circumstances, new strategies for optimizing power consumption and increasing vehicle autonomy must be designed. These must include route planning along with consumption, fuelling points and points of interest. The hardware and software solution proposed by us allows: non-invasive monitoring of power consumption, energy autonomy - it does not add any extra consumption, data transmission to a server and data fusion with the route, the points of interest of the route and the power supply points. As a result: an optimal route planning service will be provided to the driver, considering the route, the requirements of the electric vehicle and the consumer profile. The solution can be easily installed on any type of electric car - it does not involve any intervention on the equipment.

Partial Path Column Generation for the Vehicle Routing Problem

DEFF Research Database (Denmark)

Jepsen, Mads Kehlet; Petersen, Bjørn

This paper presents a column generation algorithm for the Capacitated Vehicle Routing Problem (CVRP) and the Vehicle Routing Problem with Time Windows (VRPTW). Traditionally, column generation models of the CVRP and VRPTW have consisted of a Set Partitioning master problem with each column...... of the giant tour’; a so-called partial path, i.e., not necessarily starting and ending in the depot. This way, the length of the partial path can be bounded and a better control of the size of the solution space for the pricing problem can be obtained....

Nearest greedy for solving the waste collection vehicle routing problem: A case study

Science.gov (United States)

Mat, Nur Azriati; Benjamin, Aida Mauziah; Abdul-Rahman, Syariza; Wibowo, Antoni

2017-11-01

This paper presents a real case study pertaining to an issue related to waste collection in the northern part of Malaysia by using a constructive heuristic algorithm known as the Nearest Greedy (NG) technique. This technique has been widely used to devise initial solutions for issues concerning vehicle routing. Basically, the waste collection cycle involves the following steps: i) each vehicle starts from a depot, ii) visits a number of customers to collect waste, iii) unloads waste at the disposal site, and lastly, iv) returns to the depot. Moreover, the sample data set used in this paper consisted of six areas, where each area involved up to 103 customers. In this paper, the NG technique was employed to construct an initial route for each area. The solution proposed from the technique was compared with the present vehicle routes implemented by a waste collection company within the city. The comparison results portrayed that NG offered better vehicle routes with a 11.07% reduction of the total distance traveled, in comparison to the present vehicle routes.

Evolutionary algorithms for the Vehicle Routing Problem with Time Windows

NARCIS (Netherlands)

Bräysy, Olli; Dullaert, Wout; Gendreau, Michel

2004-01-01

This paper surveys the research on evolutionary algorithms for the Vehicle Routing Problem with Time Windows (VRPTW). The VRPTW can be described as the problem of designing least cost routes from a single depot to a set of geographically scattered points. The routes must be designed in such a way

Dynamic origin-to-destination routing of wirelessly connected, autonomous vehicles on a congested network

Science.gov (United States)

Davis, L. C.

2017-07-01

Up-to-date information wirelessly communicated among vehicles can be used to select the optimal route between a given origin and destination. To elucidate how to make use of such information, simulations are performed for autonomous vehicles traveling on a square lattice of roads. All the possible routes between the origin and the destination (without backtracking) are of the same length. Congestion is the only determinant of delay. At each intersection, right-of-way is given to the closest vehicle. There are no traffic lights. Trip times of a subject vehicle are recorded for various initial conditions using different routing algorithms. Surprisingly, the simplest algorithm, which is based on the total number of vehicles on a route, is as good as one based on computing travel times from the average velocity of vehicles on each road segment.

A multi-objective location routing problem using imperialist competitive algorithm

Directory of Open Access Journals (Sweden)

Amir Mohammad Golmohammadi

2016-06-01

Full Text Available Nowadays, most manufacturing units try to locate their requirements and the depot vehicle routing in order to transport the goods at optimum cost. Needless to mention that the locations of the required warehouses influence on the performance of vehicle routing. In this paper, a mathematical programming model to optimize the storage location and vehicle routing are presented. The first objective function of the model minimizes the total cost associated with the transportation and storage, and the second objective function minimizes the difference distance traveled by vehicles. The study uses Imperialist Competitive Algorithm (ICA to solve the resulted problems in different sizes. The preliminary results have indicated that the proposed study has performed better than NSGA-II and PAES methods in terms of Quality metric and Spacing metric.

Formulations and Branch-and-Cut Algorithms for the Generalized Vehicle Routing Problem

DEFF Research Database (Denmark)

Bektas, Tolga; Erdogan, Günes; Røpke, Stefan

2011-01-01

The Generalized Vehicle Routing Problem (GVRP) consists of nding a set of routes for a number of vehicles with limited capacities on a graph with the vertices partitioned into clusters with given demands such that the total cost of travel is minimized and all demands are met. This paper offers four...

Shortest Paths and Vehicle Routing

DEFF Research Database (Denmark)

Petersen, Bjørn

This thesis presents how to parallelize a shortest path labeling algorithm. It is shown how to handle Chvátal-Gomory rank-1 cuts in a column generation context. A Branch-and-Cut algorithm is given for the Elementary Shortest Paths Problem with Capacity Constraint. A reformulation of the Vehicle...... Routing Problem based on partial paths is presented. Finally, a practical application of finding shortest paths in the telecommunication industry is shown....

Two models of the capacitated vehicle routing problem

Directory of Open Access Journals (Sweden)

Zuzana Borčinova

2017-01-01

Full Text Available The aim of the Capacitated Vehicle Routing Problem (CVRP is to find a set of minimum total cost routes for a fleet of capacitated vehicles based at a single depot, to serve a set of customers. There exist various integer linear programming models of the CVRP. One of the main differences lies in the way to eliminate sub-tours, i.e. cycles that do not go through the depot. In this paper, we describe a well-known flow formulation of CVRP, where sub-tour elimination constraints have a cardinality exponentially growing with the number of customers. Then we present a mixed linear programming formulation with polynomial cardinality of sub-tour elimination constraints. Both of the models were implemented and compared on several benchmarks.

Model and algorithm for bi-fuel vehicle routing problem to reduce GHG emissions.

Science.gov (United States)

Abdoli, Behroz; MirHassani, Seyed Ali; Hooshmand, Farnaz

2017-09-01

Because of the harmful effects of greenhouse gas (GHG) emitted by petroleum-based fuels, the adoption of alternative green fuels such as biodiesel and compressed natural gas (CNG) is an inevitable trend in the transportation sector. However, the transition to alternative fuel vehicle (AFV) fleets is not easy and, particularly at the beginning of the transition period, drivers may be forced to travel long distances to reach alternative fueling stations (AFSs). In this paper, the utilization of bi-fuel vehicles is proposed as an operational approach. We present a mathematical model to address vehicle routing problem (VRP) with bi-fuel vehicles and show that the utilization of bi-fuel vehicles can lead to a significant reduction in GHG emissions. Moreover, a simulated annealing algorithm is adopted to solve large instances of this problem. The performance of the proposed algorithm is evaluated on some random instances.

Vehicular Networking Enhancement And Multi-Channel Routing Optimization, Based on Multi-Objective Metric and Minimum Spanning Tree

Directory of Open Access Journals (Sweden)

Peppino Fazio

2013-01-01

Full Text Available Vehicular Ad hoc NETworks (VANETs represent a particular mobile technology that permits the communication among vehicles, offering security and comfort. Nowadays, distributed mobile wireless computing is becoming a very important communications paradigm, due to its flexibility to adapt to different mobile applications. VANETs are a practical example of data exchanging among real mobile nodes. To enable communications within an ad-hoc network, characterized by continuous node movements, routing protocols are needed to react to frequent changes in network topology. In this paper, the attention is focused mainly on the network layer of VANETs, proposing a novel approach to reduce the interference level during mobile transmission, based on the multi-channel nature of IEEE 802.11p (1609.4 standard. In this work a new routing protocol based on Distance Vector algorithm is presented to reduce the delay end to end and to increase packet delivery ratio (PDR and throughput in VANETs. A new metric is also proposed, based on the maximization of the average Signal-to-Interference Ratio (SIR level and the link duration probability between two VANET nodes. In order to relieve the effects of the co-channel interference perceived by mobile nodes, transmission channels are switched on a basis of a periodical SIR evaluation. A Network Simulator has been used for implementing and testing the proposed idea.

A hybrid GA-TS algorithm for open vehicle routing optimization of coal mines material

Energy Technology Data Exchange (ETDEWEB)

Yu, S.W.; Ding, C.; Zhu, K.J. [China University of Geoscience, Wuhan (China)

2011-08-15

In the open vehicle routing problem (OVRP), the objective is to minimize the number of vehicles and the total distance (or time) traveled. This study primarily focuses on solving an open vehicle routing problem (OVRP) by applying a novel hybrid genetic algorithm and the Tabu search (GA-TS), which combines the GA's parallel computing and global optimization with TS's Tabu search skill and fast local search. Firstly, the proposed algorithm uses natural number coding according to the customer demands and the captivity of the vehicle for globe optimization. Secondly, individuals of population do TS local search with a certain degree of probability, namely, do the local routing optimization of all customer sites belong to one vehicle. The mechanism not only improves the ability of global optimization, but also ensures the speed of operation. The algorithm was used in Zhengzhou Coal Mine and Power Supply Co., Ltd.'s transport vehicle routing optimization.

Stochastic time-dependent vehicle routing problem: Mathematical models and ant colony algorithm

Directory of Open Access Journals (Sweden)

Zhengyu Duan

2015-11-01

Full Text Available This article addresses the stochastic time-dependent vehicle routing problem. Two mathematical models named robust optimal schedule time model and minimum expected schedule time model are proposed for stochastic time-dependent vehicle routing problem, which can guarantee delivery within the time windows of customers. The robust optimal schedule time model only requires the variation range of link travel time, which can be conveniently derived from historical traffic data. In addition, the robust optimal schedule time model based on robust optimization method can be converted into a time-dependent vehicle routing problem. Moreover, an ant colony optimization algorithm is designed to solve stochastic time-dependent vehicle routing problem. As the improvements in initial solution and transition probability, ant colony optimization algorithm has a good performance in convergence. Through computational instances and Monte Carlo simulation tests, robust optimal schedule time model is proved to be better than minimum expected schedule time model in computational efficiency and coping with the travel time fluctuations. Therefore, robust optimal schedule time model is applicable in real road network.

A Framing Link Based Tabu Search Algorithm for Large-Scale Multidepot Vehicle Routing Problems

Directory of Open Access Journals (Sweden)

Xuhao Zhang

2014-01-01

Full Text Available A framing link (FL based tabu search algorithm is proposed in this paper for a large-scale multidepot vehicle routing problem (LSMDVRP. Framing links are generated during continuous great optimization of current solutions and then taken as skeletons so as to improve optimal seeking ability, speed up the process of optimization, and obtain better results. Based on the comparison between pre- and postmutation routes in the current solution, different parts are extracted. In the current optimization period, links involved in the optimal solution are regarded as candidates to the FL base. Multiple optimization periods exist in the whole algorithm, and there are several potential FLs in each period. If the update condition is satisfied, the FL base is updated, new FLs are added into the current route, and the next period starts. Through adjusting the borderline of multidepot sharing area with dynamic parameters, the authors define candidate selection principles for three kinds of customer connections, respectively. Link split and the roulette approach are employed to choose FLs. 18 LSMDVRP instances in three groups are studied and new optimal solution values for nine of them are obtained, with higher computation speed and reliability.

Optimization of municipal waste collection scheduling and routing using vehicle assignment problem (case study of Surabaya city waste collection)

Science.gov (United States)

Ramdhani, M. N.; Baihaqi, I.; Siswanto, N.

2018-04-01

Waste collection and disposal become a major problem for many metropolitan cities. Growing population, limited vehicles, and increased road traffic make the waste transportation become more complex. Waste collection involves some key considerations, such as vehicle assignment, vehicle routes, and vehicle scheduling. In the scheduling process, each vehicle has a scheduled departure that serve each route. Therefore, vehicle’s assignments should consider the time required to finish one assigment on that route. The objective of this study is to minimize the number of vehicles needed to serve all routes by developing a mathematical model which uses assignment problem approach. The first step is to generated possible routes from the existing routes, followed by vehicle assignments for those certain routes. The result of the model shows fewer vehicles required to perform waste collection asa well as the the number of journeys that the vehicle to collect the waste to the landfill. The comparison of existing conditions with the model result indicates that the latter’s has better condition than the existing condition because each vehicle with certain route has an equal workload, all the result’s model has the maximum of two journeys for each route.

Research on vehicle routing optimization for the terminal distribution of B2C E-commerce firms

Science.gov (United States)

Zhang, Shiyun; Lu, Yapei; Li, Shasha

2018-05-01

In this paper, we established a half open multi-objective optimization model for the vehicle routing problem of B2C (business-to-customer) E-Commerce firms. To minimize the current transport distance as well as the disparity between the excepted shipments and the transport capacity in the next distribution, we applied the concept of dominated solution and Pareto solutions to the standard particle swarm optimization and proposed a MOPSO (multi-objective particle swarm optimization) algorithm to support the model. Besides, we also obtained the optimization solution of MOPSO algorithm based on data randomly generated through the system, which verified the validity of the model.

Routing protocol extension for resilient GMPLS multi-domain networks

DEFF Research Database (Denmark)

Manolova, Anna Vasileva; Ruepp, Sarah Renée; Romeral, Ricardo

2010-01-01

This paper evaluates the performance of multi-domain networks under the Generalized Multi-Protocol Label Switching control framework in case of a single inter-domain link failure. We propose and evaluate a routing protocol extension for the Border Gateway Protocol, which allows domains to obtain...... two Autonomous System disjoint paths and use them efficiently under failure conditions. Three main applications for the protocol extension are illustrated: reducing traffic loss on existing connections by xploiting pre-selected backup paths derived with our proposal, applying multi-domain restoration...... as survivability mechanism in case of single link failure, and employing proper failure notification mechanisms for routing of future connection requests under routing protocol re-convergence. Via simulations we illustrate the benefits of utilizing the proposed routing protocol extension for networks employing...

Dynamic UAV-based traffic monitoring under uncertainty as a stochastic arc-inventory routing policy

Directory of Open Access Journals (Sweden)

Joseph Y.J. Chow

2016-10-01

Full Text Available Given the rapid advances in unmanned aerial vehicles, or drones, and increasing need to monitor at a city level, one of the current research gaps is how to systematically deploy drones over multiple periods. We propose a real-time data-driven approach: we formulate the first deterministic arc-inventory routing problem and derive its stochastic dynamic policy. The policy is expected to be of greatest value in scenarios where uncertainty is highest and costliest, such as city monitoring during major events. The Bellman equation for an approximation of the proposed inventory routing policy is formulated as a selective vehicle routing problem. We propose an approximate dynamic programming algorithm based on Least Squares Monte Carlo simulation to find that policy. The algorithm has been modified so that the least squares dependent variable is defined to be the “expected stock out cost upon the next replenishment”. The new algorithm is tested on 30 simulated instances of real time trajectories over 5 time periods of the selective vehicle routing problem to evaluate the proposed policy and algorithm. Computational results on the selected instances show that the algorithm on average outperforms the myopic policy by 23–28%, depending on the parametric design. Further tests are conducted on classic benchmark arc routing problem instances. The 11-link instance gdb19 (Golden et al., 1983 is expanded into a sequential 15-period stochastic dynamic example and used to demonstrate why a naïve static multi-period deployment plan would not be effective in real networks.

Methodology for kinematic cycle characterization of vehicles with fixed routes in urban areas

OpenAIRE

Jiménez Alonso, Felipe; Román de Andrés, Alfonso; López Martínez, José María

2013-01-01

This paper analyses the driving cycles of a fleet of vehicles with predetermined urban itineraries. Most driving cycles developed for such type of vehicles do not properly address variability among itineraries. Here we develop a polygonal driving cycle that assesses each group of related routes, based on microscopic parameters. It measures the kinematic cycles of the routes traveled by the vehicle fleet, segments cycles into micro-cycles, and characterizes their properties, groups them int...

Routing Optimization of Intelligent Vehicle in Automated Warehouse

Directory of Open Access Journals (Sweden)

Yan-cong Zhou

2014-01-01

Full Text Available Routing optimization is a key technology in the intelligent warehouse logistics. In order to get an optimal route for warehouse intelligent vehicle, routing optimization in complex global dynamic environment is studied. A new evolutionary ant colony algorithm based on RFID and knowledge-refinement is proposed. The new algorithm gets environmental information timely through the RFID technology and updates the environment map at the same time. It adopts elite ant kept, fallback, and pheromones limitation adjustment strategy. The current optimal route in population space is optimized based on experiential knowledge. The experimental results show that the new algorithm has higher convergence speed and can jump out the U-type or V-type obstacle traps easily. It can also find the global optimal route or approximate optimal one with higher probability in the complex dynamic environment. The new algorithm is proved feasible and effective by simulation results.

Potential air pollutant emission from private vehicles based on vehicle route

Science.gov (United States)

Huboyo, H. S.; Handayani, W.; Samadikun, B. P.

2017-06-01

Air emissions related to the transportation sector has been identified as the second largest emitter of ambient air quality in Indonesia. This is due to large numbers of private vehicles commuting within the city as well as inter-city. A questionnaire survey was conducted in Semarang city involving 711 private vehicles consisting of cars and motorcycles. The survey was conducted in random parking lots across the Semarang districts and in vehicle workshops. Based on the parking lot survey, the average distance private cars travelled in kilometers (VKT) was 17,737 km/year. The machine start-up number of cars during weekdays; weekends were on average 5.19 and 3.79 respectively. For motorcycles the average of kilometers travelled was 27,092 km/year. The machine start-up number of motorcycles during weekdays and weekends were on average 5.84 and 3.98, respectively. The vehicle workshop survey showed the average kilometers travelled to be 9,510 km/year for motorcycles, while for private cars the average kilometers travelled was 21,347 km/year. Odometer readings for private cars showed a maximum of 3,046,509 km and a minimum of 700 km. Meanwhile, for motorcycles, odometer readings showed a maximum of 973,164 km and a minimum of roughly 54.24 km. Air pollutant emissions on East-West routes were generally higher than those on South-North routes. Motorcycles contribute significantly to urban air pollution, more so than cars. In this study, traffic congestion and traffic volume contributed much more to air pollution than the impact of fluctuating terrain.

The Electric Fleet Size and Mix Vehicle Routing Problem with Time Windows and Recharging Stations

DEFF Research Database (Denmark)

Hiermann, Gerhard; Puchinger, Jakob; Røpke, Stefan

2016-01-01

Due to new regulations and further technological progress in the field of electric vehicles, the research community faces the new challenge of incorporating the electric energy based restrictions into vehicle routing problems. One of these restrictions is the limited battery capacity which makes...... detours to recharging stations necessary, thus requiring efficient tour planning mechanisms in order to sustain the competitiveness of electric vehicles compared to conventional vehicles. We introduce the Electric Fleet Size and Mix Vehicle Routing Problem with Time Windows and Recharging Stations (E......-FSMFTW) to model decisions to be made with regards to fleet composition and the actual vehicle routes including the choice of recharging times and locations. The available vehicle types differ in their transport capacity, battery size and acquisition cost. Furthermore, we consider time windows at customer...

Time Dependent Heterogeneous Vehicle Routing Problem for Catering Service Delivery Problem

Science.gov (United States)

Azis, Zainal; Mawengkang, Herman

2017-09-01

The heterogeneous vehicle routing problem (HVRP) is a variant of vehicle routing problem (VRP) which describes various types of vehicles with different capacity to serve a set of customers with known geographical locations. This paper considers the optimal service deliveries of meals of a catering company located in Medan City, Indonesia. Due to the road condition as well as traffic, it is necessary for the company to use different type of vehicle to fulfill customers demand in time. The HVRP incorporates time dependency of travel times on the particular time of the day. The objective is to minimize the sum of the costs of travelling and elapsed time over the planning horizon. The problem can be modeled as a linear mixed integer program and we address a feasible neighbourhood search approach to solve the problem.

Route-Based Control of Hybrid Electric Vehicles: Preprint

Energy Technology Data Exchange (ETDEWEB)

Gonder, J. D.

2008-01-01

Today's hybrid electric vehicle controls cannot always provide maximum fuel savings over all drive cycles. Route-based controls could improve HEV fuel efficiency by 2%-4% and help save nearly 6.5 million gallons of fuel annually.

Single-Commodity Vehicle Routing Problem with Pickup and Delivery Service

Directory of Open Access Journals (Sweden)

Goran Martinovic

2008-01-01

Full Text Available We present a novel variation of the vehicle routing problem (VRP. Single commodity cargo with pickup and delivery service is considered. Customers are labeled as either cargo sink or cargo source, depending on their pickup or delivery demand. This problem is called a single commodity vehicle routing problem with pickup and delivery service (1-VRPPD. 1-VRPPD deals with multiple vehicles and is the same as the single-commodity traveling salesman problem (1-PDTSP when the number of vehicles is equal to 1. Since 1-VRPPD specializes VRP, it is hard in the strong sense. Iterative modified simulated annealing (IMSA is presented along with greedy random-based initial solution algorithm. IMSA provides a good approximation to the global optimum in a large search space. Experiment is done for the instances with different number of customers and their demands. With respect to average values of IMSA execution times, proposed method is appropriate for practical applications.

An Opportunistic Routing for Data Forwarding Based on Vehicle Mobility Association in Vehicular Ad Hoc Networks

Directory of Open Access Journals (Sweden)

Leilei Wang

2017-11-01

Full Text Available Vehicular ad hoc networks (VANETs have emerged as a new powerful technology for data transmission between vehicles. Efficient data transmission accompanied with low data delay plays an important role in selecting the ideal data forwarding path in VANETs. This paper proposes a new opportunity routing protocol for data forwarding based on vehicle mobility association (OVMA. With assistance from the vehicle mobility association, data can be forwarded without passing through many extra intermediate nodes. Besides, each vehicle carries the only replica information to record its associated vehicle information, so the routing decision can adapt to the vehicle densities. Simulation results show that the OVMA protocol can extend the network lifetime, improve the performance of data delivery ratio, and reduce the data delay and routing overhead when compared to the other well-known routing protocols.

Design of a multi-vehicles delivery tours satisfying duration constraints

Energy Technology Data Exchange (ETDEWEB)

Langevin, A; Soumis, F

1987-01-01

The following organization was studied for the letter and parcel pick-up and delivery problem in an urban environment. The day is divided in periods of time in which each vehicle starts from a sorting centre, travels to a very precise area of the region, picks up and delivers letters and parcels, and returns to the depot to have the collected material sorted out for delivery during the following period. The intent of this approach is to have each zone serviced by one vehicle only, in order to facilitate the work of the dispatcher and routing of each vehicle. A method has been developed of partitioning an urban region into zones to be assigned, each one to a specific vehicle, so as to minimize the total number of vehicles used or the total distance travelled by all vehicles. The first part of the method determines the zones and the average number of points to visit. Then, a first refinement of the method takes into account the daily variability of the demand in each zone, whereas a second refinement examines the advantage of allowing some overlapping of zones for the purpose of having an overloaded vehicle relieved by one from an adjacent zone. 17 refs., 11 figs., 2 tabs.

Multi-objective evacuation routing optimization for toxic cloud releases

International Nuclear Information System (INIS)

Gai, Wen-mei; Deng, Yun-feng; Jiang, Zhong-an; Li, Jing; Du, Yan

2017-01-01

This paper develops a model for assessing the risks associated with the evacuation process in response to potential chemical accidents, based on which a multi-objective evacuation routing model for toxic cloud releases is proposed taking into account that the travel speed on each arc will be affected by disaster extension. The objectives of the evacuation routing model are to minimize travel time and individual evacuation risk along a path respectively. Two heuristic algorithms are proposed to solve the multi-objective evacuation routing model. Simulation results show the effectiveness and feasibility of the model and algorithms presented in this paper. And, the methodology with appropriate modification is suitable for supporting decisions in assessing emergency route selection in other cases (fires, nuclear accidents). - Highlights: • A model for assessing and visualizing the risks is developed. • A multi-objective evacuation routing model is proposed for toxic cloud releases. • A modified Dijkstra algorithm is designed to obtain an solution of the model. • Two heuristic algorithms have been developed as the optimization tool.

Full truckload vehicle routing problem with profits

Directory of Open Access Journals (Sweden)

Jian Li

2014-04-01

Full Text Available A new variant of the full truckload vehicle routing problem is studied. In this problem there are more than one delivery points corresponding to the same pickup point, and one order is allowed to be served several times by the same vehicle or different vehicles. For the orders which cannot be assigned because of resource constraint, the logistics company outsources them to other logistics companies at a certain cost. To maximize its profits, logistics company decides which to be transported by private fleet and which to be outsourced. The mathematical model is constructed for the problem. Since the problem is NP-hard and it is difficult to solve the large-scale problems with an exact algorithm, a hybrid genetic algorithm is proposed. Computational results show the effectiveness of the hybrid genetic algorithm.

Vehicle routing with stochastic time-dependent travel times

NARCIS (Netherlands)

Lecluyse, C.; Woensel, van T.; Peremans, H.

2009-01-01

Assigning and scheduling vehicle routes in a stochastic time-dependent environment is a crucial management problem. The assumption that in a real-life environment everything goes according to an a priori determined static schedule is unrealistic. Our methodology builds on earlier work in which the

Vehicle routing with stochastic time-dependent travel times

NARCIS (Netherlands)

Lecluyse, C.; Woensel, van T.; Peremans, H.

2007-01-01

Assigning and scheduling vehicle routes in a stochastic time-dependent environment is a crucial management problem. The assumption that in a real-life environment everything goes according to an a priori determined static schedule is unrealistic. Our methodology builds on earlier work in which the

A Monarch Butterfly Optimization for the Dynamic Vehicle Routing Problem

Directory of Open Access Journals (Sweden)

Shifeng Chen

2017-09-01

Full Text Available The dynamic vehicle routing problem (DVRP is a variant of the Vehicle Routing Problem (VRP in which customers appear dynamically. The objective is to determine a set of routes that minimizes the total travel distance. In this paper, we propose a monarch butterfly optimization (MBO algorithm to solve DVRPs, utilizing a greedy strategy. Both migration operation and the butterfly adjusting operator only accept the offspring of butterfly individuals that have better fitness than their parents. To improve performance, a later perturbation procedure is implemented, to maintain a balance between global diversification and local intensification. The computational results indicate that the proposed technique outperforms the existing approaches in the literature for average performance by at least 9.38%. In addition, 12 new best solutions were found. This shows that this proposed technique consistently produces high-quality solutions and outperforms other published heuristics for the DVRP.

Multi-Hop Link Capacity of Multi-Route Multi-Hop MRC Diversity for a Virtual Cellular Network

Science.gov (United States)

Daou, Imane; Kudoh, Eisuke; Adachi, Fumiyuki

In virtual cellular network (VCN), proposed for high-speed mobile communications, the signal transmitted from a mobile terminal is received by some wireless ports distributed in each virtual cell and relayed to the central port that acts as a gateway to the core network. In this paper, we apply the multi-route MHMRC diversity in order to decrease the transmit power and increase the multi-hop link capacity. The transmit power, the interference power and the link capacity are evaluated for DS-CDMA multi-hop VCN by computer simulation. The multi-route MHMRC diversity can be applied to not only DS-CDMA but also other access schemes (i. e. MC-CDMA, OFDM, etc.).

A New Plant Intelligent Behaviour Optimisation Algorithm for Solving Vehicle Routing Problem

OpenAIRE

Chagwiza, Godfrey

2018-01-01

A new plant intelligent behaviour optimisation algorithm is developed. The algorithm is motivated by intelligent behaviour of plants and is implemented to solve benchmark vehicle routing problems of all sizes, and results were compared to those in literature. The results show that the new algorithm outperforms most of algorithms it was compared to for very large and large vehicle routing problem instances. This is attributed to the ability of the plant to use previously stored memory to respo...

Minimizing the Carbon Footprint for the Time-Dependent Heterogeneous-Fleet Vehicle Routing Problem with Alternative Paths

Directory of Open Access Journals (Sweden)

Wan-Yu Liu

2014-07-01

Full Text Available Torespondto the reduction of greenhouse gas emissions and global warming, this paper investigates the minimal-carbon-footprint time-dependent heterogeneous-fleet vehicle routing problem with alternative paths (MTHVRPP. This finds a route with the smallestcarbon footprint, instead of the shortestroute distance, which is the conventional approach, to serve a number of customers with a heterogeneous fleet of vehicles in cases wherethere may not be only one path between each pair of customers, and the vehicle speed differs at different times of the day. Inheriting from the NP-hardness of the vehicle routing problem, the MTHVRPP is also NP-hard. This paper further proposes a genetic algorithm (GA to solve this problem. The solution representedbyour GA determines the customer serving ordering of each vehicle type. Then, the capacity check is used to classify multiple routes of each vehicle type, and the path selection determines the detailed paths of each route. Additionally, this paper improves the energy consumption model used for calculating the carbon footprint amount more precisely. Compared with the results without alternative paths, our experimental results show that the alternative path in this experimenthas a significant impact on the experimental results in terms of carbon footprint.

Periodic vehicle inspection (MOT). [previously: Periodic Vehicle Inspection of cars (MOT).

NARCIS (Netherlands)

2010-01-01

In the 1980s the periodic vehicle inspection (MOT) of various categories of vehicles was introduced in the Netherlands. This fact sheet will discuss the legal framework of this measure and the research carried out into its effects on road safety, also in an international context. For instance, the

A branch-and-cut-and-price algorithm for the cumulative capacitated vehicle routing problem

DEFF Research Database (Denmark)

Wøhlk, Sanne; Lysgaard, Jens

2014-01-01

The paper considers the Cumulative Capacitated Vehicle Routing Problem (CCVRP), which is a variation of the well-known Capacitated Vehicle Routing Problem (CVRP). In this problem, the traditional objective of minimizing total distance or time traveled by the vehicles is replaced by minimizing...... the sum of arrival times at the customers. A branch-and-cut-and-price algorithm for obtaining optimal solutions to the problem is proposed. Computational results based on a set of standard CVRP benchmarks are presented....

Optimal Routing for Heterogeneous Fixed Fleets of Multicompartment Vehicles

OpenAIRE

Wang, Qian; Ji, Qingkai; Chiu, Chun-Hung

2014-01-01

We present a metaheuristic called the reactive guided tabu search (RGTS) to solve the heterogeneous fleet multicompartment vehicle routing problem (MCVRP), where a single vehicle is required for cotransporting multiple customer orders. MCVRP is commonly found in delivery of fashion apparel, petroleum distribution, food distribution, and waste collection. In searching the optimum solution of MCVRP, we need to handle a large amount of local optima in the solution spaces. To overcome this proble...

A capacitated vehicle routing problem with order available time in e-commerce industry

Science.gov (United States)

Liu, Ling; Li, Kunpeng; Liu, Zhixue

2017-03-01

In this article, a variant of the well-known capacitated vehicle routing problem (CVRP) called the capacitated vehicle routing problem with order available time (CVRPOAT) is considered, which is observed in the operations of the current e-commerce industry. In this problem, the orders are not available for delivery at the beginning of the planning period. CVRPOAT takes all the assumptions of CVRP, except the order available time, which is determined by the precedent order picking and packing stage in the warehouse of the online grocer. The objective is to minimize the sum of vehicle completion times. An efficient tabu search algorithm is presented to tackle the problem. Moreover, a Lagrangian relaxation algorithm is developed to obtain the lower bounds of reasonably sized problems. Based on the test instances derived from benchmark data, the proposed tabu search algorithm is compared with a published related genetic algorithm, as well as the derived lower bounds. Also, the tabu search algorithm is compared with the current operation strategy of the online grocer. Computational results indicate that the gap between the lower bounds and the results of the tabu search algorithm is small and the tabu search algorithm is superior to the genetic algorithm. Moreover, the CVRPOAT formulation together with the tabu search algorithm performs much better than the current operation strategy of the online grocer.

Planning of Vehicle Routing with Backup Provisioning Using Wireless Sensor Technologies

Directory of Open Access Journals (Sweden)

Noélia Correia

2017-08-01

Full Text Available Wireless sensor technologies can be used by intelligent transportation systems to provide innovative services that lead to improvements in road safety and congestion, increasing end-user satisfaction. In this article, we address vehicle routing with backup provisioning, where the possibility of reacting to overloading/overcrowding of vehicles at certain stops is considered. This is based on the availability of vehicle load information, which can be captured using wireless sensor technologies. After discussing the infrastructure and monitoring tool, the problem is mathematically formalized, and a heuristic algorithm using local search procedures is proposed. Results show that planning routes with backup provisioning can allow fast response to overcrowding while reducing costs. Therefore, sustainable urban mobility, with efficient use of resources, can be provided while increasing the quality of service perceived by users.

Waste Collection Vehicle Routing Problem: Literature Review

Directory of Open Access Journals (Sweden)

Hui Han

2015-08-01

Full Text Available Waste generation is an issue which has caused wide public concern in modern societies, not only for the quantitative rise of the amount of waste generated, but also for the increasing complexity of some products and components. Waste collection is a highly relevant activity in the reverse logistics system and how to collect waste in an efficient way is an area that needs to be improved. This paper analyzes the major contribution about Waste Collection Vehicle Routing Problem (WCVRP in literature. Based on a classification of waste collection (residential, commercial and industrial, firstly the key findings for these three types of waste collection are presented. Therefore, according to the model (Node Routing Problems and Arc Routing problems used to represent WCVRP, different methods and techniques are analyzed in this paper to solve WCVRP. This paper attempts to serve as a roadmap of research literature produced in the field of WCVRP.

A novel heuristic algorithm for capacitated vehicle routing problem

Science.gov (United States)

Kır, Sena; Yazgan, Harun Reşit; Tüncel, Emre

2017-09-01

The vehicle routing problem with the capacity constraints was considered in this paper. It is quite difficult to achieve an optimal solution with traditional optimization methods by reason of the high computational complexity for large-scale problems. Consequently, new heuristic or metaheuristic approaches have been developed to solve this problem. In this paper, we constructed a new heuristic algorithm based on the tabu search and adaptive large neighborhood search (ALNS) with several specifically designed operators and features to solve the capacitated vehicle routing problem (CVRP). The effectiveness of the proposed algorithm was illustrated on the benchmark problems. The algorithm provides a better performance on large-scaled instances and gained advantage in terms of CPU time. In addition, we solved a real-life CVRP using the proposed algorithm and found the encouraging results by comparison with the current situation that the company is in.

On the multiple depots vehicle routing problem with heterogeneous fleet capacity and velocity

Science.gov (United States)

Hanum, F.; Hartono, A. P.; Bakhtiar, T.

2018-03-01

This current manuscript concerns with the optimization problem arising in a route determination of products distribution. The problem is formulated in the form of multiple depots and time windowed vehicle routing problem with heterogeneous capacity and velocity of fleet. Model includes a number of constraints such as route continuity, multiple depots availability and serving time in addition to generic constraints. In dealing with the unique feature of heterogeneous velocity, we generate a number of velocity profiles along the road segments, which then converted into traveling-time tables. An illustrative example of rice distribution among villages by bureau of logistics is provided. Exact approach is utilized to determine the optimal solution in term of vehicle routes and starting time of service.

Routing strategies for efficient deployment of alternative fuel vehicles for freight delivery.

Science.gov (United States)

2017-02-01

With increasing concerns on environmental issues, recent research on Vehicle Routing Problems : (VRP) has added new factors such as greenhouse gas emissions and alternative fuel vehicles into : the models. In this report, we consider one such promisi...

Vehicle routing for the eco-efficient collection of household plastic waste.

Science.gov (United States)

Bing, Xiaoyun; de Keizer, Marlies; Bloemhof-Ruwaard, Jacqueline M; van der Vorst, Jack G A J

2014-04-01

Plastic waste is a special category of municipal solid waste. Plastic waste collection is featured with various alternatives of collection methods (curbside/drop-off) and separation methods (source-/post-separation). In the Netherlands, the collection routes of plastic waste are the same as those of other waste, although plastic is different than other waste in terms of volume to weight ratio. This paper aims for redesigning the collection routes and compares the collection options of plastic waste using eco-efficiency as performance indicator. Eco-efficiency concerns the trade-off between environmental impacts, social issues and costs. The collection problem is modeled as a vehicle routing problem. A tabu search heuristic is used to improve the routes. Collection alternatives are compared by a scenario study approach. Real distances between locations are calculated with MapPoint. The scenario study is conducted based on real case data of the Dutch municipality Wageningen. Scenarios are designed according to the collection alternatives with different assumptions in collection method, vehicle type, collection frequency and collection points, etc. Results show that the current collection routes can be improved in terms of eco-efficiency performance by using our method. The source-separation drop-off collection scenario has the best performance for plastic collection assuming householders take the waste to the drop-off points in a sustainable manner. The model also shows to be an efficient decision support tool to investigate the impacts of future changes such as alternative vehicle type and different response rates. Crown Copyright © 2014. Published by Elsevier Ltd. All rights reserved.

Intelligent emission-sensitive routing for plugin hybrid electric vehicles.

Science.gov (United States)

Sun, Zhonghao; Zhou, Xingshe

2016-01-01

The existing transportation sector creates heavily environmental impacts and is a prime cause for the current climate change. The need to reduce emissions from this sector has stimulated efforts to speed up the application of electric vehicles (EVs). A subset of EVs, called plug-in hybrid electric vehicles (PHEVs), backup batteries with combustion engine, which makes PHEVs have a comparable driving range to conventional vehicles. However, this hybridization comes at a cost of higher emissions than all-electric vehicles. This paper studies the routing problem for PHEVs to minimize emissions. The existing shortest-path based algorithms cannot be applied to solving this problem, because of the several new challenges: (1) an optimal route may contain circles caused by detour for recharging; (2) emissions of PHEVs not only depend on the driving distance, but also depend on the terrain and the state of charge (SOC) of batteries; (3) batteries can harvest energy by regenerative braking, which makes some road segments have negative energy consumption. To address these challenges, this paper proposes a green navigation algorithm (GNA) which finds the optimal strategies: where to go and where to recharge. GNA discretizes the SOC, then makes the PHEV routing problem to satisfy the principle of optimality. Finally, GNA adopts dynamic programming to solve the problem. We evaluate GNA using synthetic maps generated by the delaunay triangulation. The results show that GNA can save more than 10 % energy and reduce 10 % emissions when compared to the shortest path algorithm. We also observe that PHEVs with the battery capacity of 10-15 KWh detour most and nearly no detour when larger than 30 KWh. This observation gives some insights when developing PHEVs.

Variable neighborhood search to solve the vehicle routing problem for hazardous materials transportation.

Science.gov (United States)

Bula, Gustavo Alfredo; Prodhon, Caroline; Gonzalez, Fabio Augusto; Afsar, H Murat; Velasco, Nubia

2017-02-15

This work focuses on the Heterogeneous Fleet Vehicle Routing problem (HFVRP) in the context of hazardous materials (HazMat) transportation. The objective is to determine a set of routes that minimizes the total expected routing risk. This is a nonlinear function, and it depends on the vehicle load and the population exposed when an incident occurs. Thus, a piecewise linear approximation is used to estimate it. For solving the problem, a variant of the Variable Neighborhood Search (VNS) algorithm is employed. To improve its performance, a post-optimization procedure is implemented via a Set Partitioning (SP) problem. The SP is solved on a pool of routes obtained from executions of the local search procedure embedded on the VNS. The algorithm is tested on two sets of HFVRP instances based on literature with up to 100 nodes, these instances are modified to include vehicle and arc risk parameters. The results are competitive in terms of computational efficiency and quality attested by a comparison with Mixed Integer Linear Programming (MILP) previously proposed. Copyright © 2016 Elsevier B.V. All rights reserved.

Optimal Routing and Scheduling of Charge for Electric Vehicles: Case Study

OpenAIRE

Barco, John; Guerra, Andres; Muñoz, Luis; Quijano, Nicanor

2013-01-01

In Colombia, there is an increasing interest about improving public transportation. One of the proposed strategies in that way is the use battery electric vehicles (BEVs). One of the new challenges is the BEVs routing problem, which is subjected to the traditional issues of the routing problems, and must also consider the particularities of autonomy, charge and battery degradation of the BEVs. In this work, a scheme that coordinates the routing, scheduling of charge and operating costs of BEV...

Minimum Makespan Multi-Vehicle Dial-a-Ride

DEFF Research Database (Denmark)

Gørtz, Inge Li; Nagarajan, Viswanath; Ravi, R.

2015-01-01

of multi-vehicle Dial-a-Ride, in which an object may be left at intermediate vertices and transported by more than one vehicle, while being moved from source to destination. Our main results are an O(log(3) n)-approximation algorithm for preemptive multi-vehicle Dial-a-Ride, and an improved O(log t...

The vehicle routing problem with edge set costs

DEFF Research Database (Denmark)

Reinhardt, Line Blander; Jepsen, Mads Kehlet; Pisinger, David

We consider an important generalization of the vehicle routing problem with time windows in which a fixed cost must be paid for accessing a set of edges. This fixed cost could reflect payment for toll roads, investment in new facilities, the need for certifications and other costly investments....... The certifications and contributions impose a cost for the company while they also give unlimited usage of a set of roads to all vehicles belonging to the company. Different versions for defining the edge sets are discussed and formulated. A MIP-formulation of the problem is presented, and a solution method based...

Solving a multi-objective location routing problem for infectious waste disposal using hybrid goal programming and hybrid genetic algorithm

Directory of Open Access Journals (Sweden)

Narong Wichapa

2018-01-01

Full Text Available Infectious waste disposal remains one of the most serious problems in the medical, social and environmental domains of almost every country. Selection of new suitable locations and finding the optimal set of transport routes for a fleet of vehicles to transport infectious waste material, location routing problem for infectious waste disposal, is one of the major problems in hazardous waste management. Determining locations for infectious waste disposal is a difficult and complex process, because it requires combining both intangible and tangible factors. Additionally, it depends on several criteria and various regulations. This facility location problem for infectious waste disposal is complicated, and it cannot be addressed using any stand-alone technique. Based on a case study, 107 hospitals and 6 candidate municipalities in Upper-Northeastern Thailand, we considered criteria such as infrastructure, geology and social & environmental criteria, evaluating global priority weights using the fuzzy analytical hierarchy process (Fuzzy AHP. After that, a new multi-objective facility location problem model which hybridizes fuzzy AHP and goal programming (GP, namely the HGP model, was tested. Finally, the vehicle routing problem (VRP for a case study was formulated, and it was tested using a hybrid genetic algorithm (HGA which hybridizes the push forward insertion heuristic (PFIH, genetic algorithm (GA and three local searches including 2-opt, insertion-move and interexchange-move. The results show that both the HGP and HGA can lead to select new suitable locations and to find the optimal set of transport routes for vehicles delivering infectious waste material. The novelty of the proposed methodologies, HGP, is the simultaneous combination of relevant factors that are difficult to interpret and cost factors in order to determine new suitable locations, and HGA can be applied to determine the transport routes which provide a minimum number of vehicles

Penerapan Algoritma Genetika Untuk Penyelesaian Vehicle Routing Problem With Delivery And Pick-Up (VRP-DP)

OpenAIRE

Simanullang, Herlin

2013-01-01

Vehicle Routing Problem (VRP) is a problem of combinatorial optimization complexeses that has essential role in management distribution system which is aimed to minimize the needed cost, the cost is determined in relationship with the distance of route which is taken by the distribution vehicle. The characteristic from VRP is the use of vehicle in certain capacity and its activity is centralized in one depot to serve the customer on certain locations with certain known demand. ...

A Hybrid Tabu Search Algorithm for a Real-World Open Vehicle Routing Problem Involving Fuel Consumption Constraints

Directory of Open Access Journals (Sweden)

Yunyun Niu

2018-01-01

Full Text Available Outsourcing logistics operation to third-party logistics has attracted more attention in the past several years. However, very few papers analyzed fuel consumption model in the context of outsourcing logistics. This problem involves more complexity than traditional open vehicle routing problem (OVRP, because the calculation of fuel emissions depends on many factors, such as the speed of vehicles, the road angle, the total load, the engine friction, and the engine displacement. Our paper proposed a green open vehicle routing problem (GOVRP model with fuel consumption constraints for outsourcing logistics operations. Moreover, a hybrid tabu search algorithm was presented to deal with this problem. Experiments were conducted on instances based on realistic road data of Beijing, China, considering that outsourcing logistics plays an increasingly important role in China’s freight transportation. Open routes were compared with closed routes through statistical analysis of the cost components. Compared with closed routes, open routes reduce the total cost by 18.5% with the fuel emissions cost down by nearly 29.1% and the diver cost down by 13.8%. The effect of different vehicle types was also studied. Over all the 60- and 120-node instances, the mean total cost by using the light-duty vehicles is the lowest.

A Hybrid Genetic Algorithm for Multi-Trip Green Capacitated Arc Routing Problem in the Scope of Urban Services

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Erfan Babaee Tirkolaee

2018-04-01

Full Text Available Greenhouse gases (GHG are the main reason for the global warming during the past decades. On the other hand, establishing a well-structured transportation system will yield to create least cost-pollution. This paper addresses a novel model for the multi-trip Green Capacitated Arc Routing Problem (G-CARP with the aim of minimizing total cost including the cost of generation and emission of greenhouse gases, the cost of vehicle usage and routing cost. The cost of generation and emission of greenhouse gases is based on the calculation of the amount of carbon dioxide emitted from vehicles, which depends on such factors as the vehicle speed, weather conditions, load on the vehicle and traveled distance. The main applications of this problem are in municipalities for urban waste collection, road surface marking and so forth. Due to NP-hardness of the problem, a Hybrid Genetic Algorithm (HGA is developed, wherein a heuristic and simulated annealing algorithm are applied to generate initial solutions and a Genetic Algorithm (GA is then used to generate the best possible solution. The obtained numerical results indicate that the proposed algorithm could present desirable performance within a suitable computational run time. Finally, a sensitivity analysis is implemented on the maximum available time of the vehicles in order to determine the optimal policy.

Multi-hop routing in wireless sensor networks an overview, taxonomy, and research challenges

CERN Document Server

Rani, Shalli

2016-01-01

This brief provides an overview of recent developments in multi-hop routing protocols for Wireless Sensor Networks (WSNs). It introduces the various classifications of routing protocols and lists the pros and cons of each category, going beyond the conceptual overview of routing classifications offered in other books. Recently many researchers have proposed numerous multi-hop routing protocols and thereby created a need for a book that provides its readers with an up-to-date road map of this research paradigm.   The authors present some of the most relevant results achieved by applying an algorithmic approach to the research on multi-hop routing protocols. The book covers measurements, experiences and lessons learned from the implementation of multi-hop communication prototypes. Furthermore, it describes future research challenges and as such serves as a useful guide for students and researchers alike.

High throughput route selection in multi-rate wireless mesh networks

Institute of Scientific and Technical Information of China (English)

WEI Yi-fei; GUO Xiang-li; SONG Mei; SONG Jun-de

2008-01-01

Most existing Ad-hoc routing protocols use the shortest path algorithm with a hop count metric to select paths. It is appropriate in single-rate wireless networks, but has a tendency to select paths containing long-distance links that have low data rates and reduced reliability in multi-rate networks. This article introduces a high throughput routing algorithm utilizing the multi-rate capability and some mesh characteristics in wireless fidelity (WiFi) mesh networks. It uses the medium access control (MAC) transmission time as the routing metric, which is estimated by the information passed up from the physical layer. When the proposed algorithm is adopted, the Ad-hoc on-demand distance vector (AODV) routing can be improved as high throughput AODV (HT-AODV). Simulation results show that HT-AODV is capable of establishing a route that has high data-rate, short end-to-end delay and great network throughput.

Analysis of parameter estimation and optimization application of ant colony algorithm in vehicle routing problem

Science.gov (United States)

Xu, Quan-Li; Cao, Yu-Wei; Yang, Kun

2018-03-01

Ant Colony Optimization (ACO) is the most widely used artificial intelligence algorithm at present. This study introduced the principle and mathematical model of ACO algorithm in solving Vehicle Routing Problem (VRP), and designed a vehicle routing optimization model based on ACO, then the vehicle routing optimization simulation system was developed by using c ++ programming language, and the sensitivity analyses, estimations and improvements of the three key parameters of ACO were carried out. The results indicated that the ACO algorithm designed in this paper can efficiently solve rational planning and optimization of VRP, and the different values of the key parameters have significant influence on the performance and optimization effects of the algorithm, and the improved algorithm is not easy to locally converge prematurely and has good robustness.

Comparing genetic algorithm and particle swarm optimization for solving capacitated vehicle routing problem

Science.gov (United States)

Iswari, T.; Asih, A. M. S.

2018-04-01

In the logistics system, transportation plays an important role to connect every element in the supply chain, but it can produces the greatest cost. Therefore, it is important to make the transportation costs as minimum as possible. Reducing the transportation cost can be done in several ways. One of the ways to minimizing the transportation cost is by optimizing the routing of its vehicles. It refers to Vehicle Routing Problem (VRP). The most common type of VRP is Capacitated Vehicle Routing Problem (CVRP). In CVRP, the vehicles have their own capacity and the total demands from the customer should not exceed the capacity of the vehicle. CVRP belongs to the class of NP-hard problems. These NP-hard problems make it more complex to solve such that exact algorithms become highly time-consuming with the increases in problem sizes. Thus, for large-scale problem instances, as typically found in industrial applications, finding an optimal solution is not practicable. Therefore, this paper uses two kinds of metaheuristics approach to solving CVRP. Those are Genetic Algorithm and Particle Swarm Optimization. This paper compares the results of both algorithms and see the performance of each algorithm. The results show that both algorithms perform well in solving CVRP but still needs to be improved. From algorithm testing and numerical example, Genetic Algorithm yields a better solution than Particle Swarm Optimization in total distance travelled.

Periodic vehicle inspection (MOT). [previously: Periodic Vehicle Inspection of cars (MOT).

OpenAIRE

2010-01-01

In the 1980s the periodic vehicle inspection (MOT) of various categories of vehicles was introduced in the Netherlands. This fact sheet will discuss the legal framework of this measure and the research carried out into its effects on road safety, also in an international context. For instance, the technical conditions of cars at inspection as well as that of cars involved in crashes were studied. Tyre pressure will also be discussed in this fact sheet.

Modeling a four-layer location-routing problem

Directory of Open Access Journals (Sweden)

Mohsen Hamidi

2012-01-01

Full Text Available Distribution is an indispensable component of logistics and supply chain management. Location-Routing Problem (LRP is an NP-hard problem that simultaneously takes into consideration location, allocation, and vehicle routing decisions to design an optimal distribution network. Multi-layer and multi-product LRP is even more complex as it deals with the decisions at multiple layers of a distribution network where multiple products are transported within and between layers of the network. This paper focuses on modeling a complicated four-layer and multi-product LRP which has not been tackled yet. The distribution network consists of plants, central depots, regional depots, and customers. In this study, the structure, assumptions, and limitations of the distribution network are defined and the mathematical optimization programming model that can be used to obtain the optimal solution is developed. Presented by a mixed-integer programming model, the LRP considers the location problem at two layers, the allocation problem at three layers, the vehicle routing problem at three layers, and a transshipment problem. The mathematical model locates central and regional depots, allocates customers to plants, central depots, and regional depots, constructs tours from each plant or open depot to customers, and constructs transshipment paths from plants to depots and from depots to other depots. Considering realistic assumptions and limitations such as producing multiple products, limited production capacity, limited depot and vehicle capacity, and limited traveling distances enables the user to capture the real world situations.

Waste Collection Vehicle Routing Problem: Literature Review

OpenAIRE

Hui Han; Eva Ponce Cueto

2015-01-01

Waste generation is an issue which has caused wide public concern in modern societies, not only for the quantitative rise of the amount of waste generated, but also for the increasing complexity of some products and components. Waste collection is a highly relevant activity in the reverse logistics system and how to collect waste in an efficient way is an area that needs to be improved. This paper analyzes the major contribution about Waste Collection Vehicle Routing Problem (WCVRP) in litera...

Municipal solid waste transportation optimisation with vehicle routing approach: case study of Pontianak City, West Kalimantan

Science.gov (United States)

Kamal, M. A.; Youlla, D.

2018-03-01

Municipal solid waste (MSW) transportation in Pontianak City becomes an issue that need to be tackled by the relevant agencies. The MSW transportation service in Pontianak City currently requires very high resources especially in vehicle usage. Increasing the number of fleets has not been able to increase service levels while garbage volume is growing every year along with population growth. In this research, vehicle routing optimization approach was used to find optimal and efficient routes of vehicle cost in transporting garbage from several Temporary Garbage Dump (TGD) to Final Garbage Dump (FGD). One of the problems of MSW transportation is that there is a TGD which exceed the the vehicle capacity and must be visited more than once. The optimal computation results suggest that the municipal authorities only use 3 vehicles from 5 vehicles provided with the total minimum cost of IDR. 778,870. The computation time to search optimal route and minimal cost is very time consuming. This problem is influenced by the number of constraints and decision variables that have are integer value.

Capacitated vehicle-routing problem model for scheduled solid waste collection and route optimization using PSO algorithm.

Science.gov (United States)

Hannan, M A; Akhtar, Mahmuda; Begum, R A; Basri, H; Hussain, A; Scavino, Edgar

2018-01-01

Waste collection widely depends on the route optimization problem that involves a large amount of expenditure in terms of capital, labor, and variable operational costs. Thus, the more waste collection route is optimized, the more reduction in different costs and environmental effect will be. This study proposes a modified particle swarm optimization (PSO) algorithm in a capacitated vehicle-routing problem (CVRP) model to determine the best waste collection and route optimization solutions. In this study, threshold waste level (TWL) and scheduling concepts are applied in the PSO-based CVRP model under different datasets. The obtained results from different datasets show that the proposed algorithmic CVRP model provides the best waste collection and route optimization in terms of travel distance, total waste, waste collection efficiency, and tightness at 70-75% of TWL. The obtained results for 1 week scheduling show that 70% of TWL performs better than all node consideration in terms of collected waste, distance, tightness, efficiency, fuel consumption, and cost. The proposed optimized model can serve as a valuable tool for waste collection and route optimization toward reducing socioeconomic and environmental impacts. Copyright © 2017 Elsevier Ltd. All rights reserved.

Comparative chlorpyrifos pharmacokinetics via multiple routes of exposure and vehicles of administration in the adult rat

International Nuclear Information System (INIS)

Smith, Jordan Ned; Campbell, James A.; Busby-Hjerpe, Andrea L.; Lee, Sookwang; Poet, Torka S.; Barr, Dana B.; Timchalk, Charles

2009-01-01

Chlorpyrifos (CPF) is a commonly used organophosphorus pesticide. A number of toxicity and mechanistic studies have been conducted in animals, where CPF has been administered via a variety of different exposure routes and dosing vehicles. This study compared chlorpyrifos (CPF) pharmacokinetics using oral, intravenous (IV), and subcutaneous (SC) exposure routes and corn oil, saline/Tween 20, and dimethyl sulfoxide (DMSO) as dosing vehicles. Two groups of rats were co-administered target doses (5 mg/kg) of CPF and isotopically labeled CPF (L-CPF). One group was exposed by both oral (CPF) and IV (L-CPF) routes using saline/Tween 20 vehicle; whereas, the second group was exposed by the SC route using two vehicles, corn oil (CPF) and DMSO (L-CPF). A third group was only administered CPF by the oral route in corn oil. For all treatments, blood and urine time course samples were collected and analyzed for 3,5,6-trichloro-2-pyridinol (TCPy), and isotopically labeled 3,5,6-trichloro-2-pyridinol (L-TCPy). Peak TCPy/L-TCPy concentrations in blood (20.2 μmol/l), TCPy/L-TCPy blood AUC (94.9 μmol/l h), and percent of dose excreted in urine (100%) were all highest in rats dosed orally with CPF in saline/Tween 20 and second highest in rats dosed orally with CPF in corn oil. Peak TCPy concentrations in blood were more rapidly obtained after oral administration of CPF in saline/Tween 20 compared to all other dosing scenarios (>1.5 h). These results indicate that orally administered CPF is more extensively metabolized than systemic exposures of CPF (SC and IV), and vehicle of administration also has an effect on absorption rates. Thus, equivalent doses via different routes and/or vehicles of administration could potentially lead to different body burdens of CPF, different rates of bioactivation to CPF-oxon, and different toxic responses. Simulations using a physiologically based pharmacokinetic and pharmacodynamic (PBPK/PD) model for CPF are consistent with these possibilities

Mathematical Formulation and Comparison of Solution Approaches for the Vehicle Routing Problem with Access Time Windows

Directory of Open Access Journals (Sweden)

Rafael Grosso

2018-01-01

Full Text Available The application of the principles of sustainability to the implementation of urban freight policies requires the estimation of all the costs and externalities involved. We focus here on the case of access time windows, which ban the access of freight vehicles to central urban areas in many European cities. Even though this measure seeks to reduce congestion and emissions in the most crowded periods of the day, it also imposes additional costs for carriers and results in higher emissions and energy consumption. We present here a mathematical model for the Vehicle Routing Problem with Access Time Windows, a variant of the VRP suitable for planning delivery routes in a city subject to this type of accessibility restriction. We use the model to find exact solutions to small problem instances based on a case study and then compare the performance over larger instances of a modified savings algorithm, a genetic algorithm, and a tabu search procedure, with the results showing no clear prevalence of any of them, but confirming the significance of those additional costs and externalities.

Reachability cuts for the vehicle routing problem with time windows

DEFF Research Database (Denmark)

Lysgaard, Jens

2004-01-01

This paper introduces a class of cuts, called reachability cuts, for the Vehicle Routing Problem with Time Windows (VRPTW). Reachability cuts are closely related to cuts derived from precedence constraints in the Asymmetric Traveling Salesman Problem with Time Windows and to k-path cuts...

A stochastic time-dependent green capacitated vehicle routing and scheduling problem with time window, resiliency and reliability: a case study

Directory of Open Access Journals (Sweden)

Masoud Rabbani

2018-09-01

Full Text Available This paper presents a new multi-objective model for a vehicle routing problem under a stochastic uncertainty. It considers traffic point as an inflection point to deal with the arrival time of vehicles. It aims to minimize the total transportation cost, traffic pollution, customer dissatisfaction and maximizes the reliability of vehicles. Moreover, resiliency factors are included in the model to increase the flexibility of the system and decrease the possible losses that may impose on the system. Due to the NP-hardness of the presented model, a meta-heuristic algorithm, namely Simulated Annealing (SA is developed. Furthermore, a number of sensitivity analyses are provided to validate the effectiveness of the proposed model. Lastly, the foregoing meta-heuristic is compared with GAMS, in which the computational results demonstrate an acceptable performance of the proposed SA.

Multi-Objective Weather Routing of Sailing Vessels

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Życzkowski Marcin

2017-12-01

Full Text Available The paper presents a multi-objective deterministic method of weather routing for sailing vessels. Depending on a particular purpose of sailboat weather routing, the presented method makes it possible to customize the criteria and constraints so as to fit a particular user’s needs. Apart from a typical shortest time criterion, safety and comfort can also be taken into account. Additionally, the method supports dynamic weather data: in its present version short-term, mid-term and long-term term weather forecasts are used during optimization process. In the paper the multi-objective optimization problem is first defined and analysed. Following this, the proposed method solving this problem is described in detail. The method has been implemented as an online SailAssistance application. Some representative examples solutions are presented, emphasizing the effects of applying different criteria or different values of customized parameters.

A model-based eco-routing strategy for electric vehicles in large urban networks

OpenAIRE

De Nunzio , Giovanni; Thibault , Laurent; Sciarretta , Antonio

2016-01-01

International audience; A novel eco-routing navigation strategy and energy consumption modeling approach for electric vehicles are presented in this work. Speed fluctuations and road network infrastructure have a large impact on vehicular energy consumption. Neglecting these effects may lead to large errors in eco-routing navigation, which could trivially select the route with the lowest average speed. We propose an energy consumption model that considers both accelerations and impact of the ...

Path inequalities for the vehicle routing problem with time windows

DEFF Research Database (Denmark)

Kallehauge, Brian; Boland, Natashia; Madsen, Oli B.G.

2007-01-01

In this paper we introduce a new formulation of the vehicle routing problem with time windows (VRPTW) involving only binary variables. The new formulation is based on the formulation of the asymmetric traveling salesman problem with time windows by Ascheuer et al. (Networks 36 (2000) 69-79) and has...

Global forward-predicting dynamic routing for traffic concurrency space stereo multi-layer scale-free network

International Nuclear Information System (INIS)

Xie Wei-Hao; Zhou Bin; Liu En-Xiao; Lu Wei-Dang; Zhou Ting

2015-01-01

Many real communication networks, such as oceanic monitoring network and land environment observation network, can be described as space stereo multi-layer structure, and the traffic in these networks is concurrent. Understanding how traffic dynamics depend on these real communication networks and finding an effective routing strategy that can fit the circumstance of traffic concurrency and enhance the network performance are necessary. In this light, we propose a traffic model for space stereo multi-layer complex network and introduce two kinds of global forward-predicting dynamic routing strategies, global forward-predicting hybrid minimum queue (HMQ) routing strategy and global forward-predicting hybrid minimum degree and queue (HMDQ) routing strategy, for traffic concurrency space stereo multi-layer scale-free networks. By applying forward-predicting strategy, the proposed routing strategies achieve better performances in traffic concurrency space stereo multi-layer scale-free networks. Compared with the efficient routing strategy and global dynamic routing strategy, HMDQ and HMQ routing strategies can optimize the traffic distribution, alleviate the number of congested packets effectively and reach much higher network capacity. (paper)

Refinements of the column generation process for the Vehicle Routing Problem with Time Windows

DEFF Research Database (Denmark)

Larsen, Jesper

2004-01-01

interval denoted the time window. The objective is to determine routes for the vehicles that minimizes the accumulated cost (or distance) with respect to the above mentioned constraints. Currently the best approaches for determining optimal solutions are based on column generation and Branch......-and-Bound, also known as Branch-and-Price. This paper presents two ideas for run-time improvements of the Branch-and-Price framework for the Vehicle Routing Problem with Time Windows. Both ideas reveal a significant potential for using run-time refinements when speeding up an exact approach without compromising...

SOLVING THE PROBLEM OF VEHICLE ROUTING BY EVOLUTIONARY ALGORITHM

Directory of Open Access Journals (Sweden)

Remigiusz Romuald Iwańkowicz

2016-03-01

Full Text Available In the presented work the vehicle routing problem is formulated, which concerns planning the collection of wastes by one garbage truck from a certain number of collection points. The garbage truck begins its route in the base point, collects the load in subsequent collection points, then drives the wastes to the disposal site (landfill or sorting plant and returns to the another visited collection points. The filled garbage truck each time goes to the disposal site. It returns to the base after driving wastes from all collection points. Optimization model is based on genetic algorithm where individual is the whole garbage collection plan. Permutation is proposed as the code of the individual.

Cooperative Path-Planning for Multi-Vehicle Systems

Directory of Open Access Journals (Sweden)

Qichen Wang

2014-11-01

Full Text Available In this paper, we propose a collision avoidance algorithm for multi-vehicle systems, which is a common problem in many areas, including navigation and robotics. In dynamic environments, vehicles may become involved in potential collisions with each other, particularly when the vehicle density is high and the direction of travel is unrestricted. Cooperatively planning vehicle movement can effectively reduce and fairly distribute the detour inconvenience before subsequently returning vehicles to their intended paths. We present a novel method of cooperative path planning for multi-vehicle systems based on reinforcement learning to address this problem as a decision process. A dynamic system is described as a multi-dimensional space formed by vectors as states to represent all participating vehicles’ position and orientation, whilst considering the kinematic constraints of the vehicles. Actions are defined for the system to transit from one state to another. In order to select appropriate actions whilst satisfying the constraints of path smoothness, constant speed and complying with a minimum distance between vehicles, an approximate value function is iteratively developed to indicate the desirability of every state-action pair from the continuous state space and action space. The proposed scheme comprises two phases. The convergence of the value function takes place in the former learning phase, and it is then used as a path planning guideline in the subsequent action phase. This paper summarizes the concept and methodologies used to implement this online cooperative collision avoidance algorithm and presents results and analysis regarding how this cooperative scheme improves upon two baseline schemes where vehicles make movement decisions independently.

The Vehicle Routing Problem with Time Windows and Temporal Dependencies

DEFF Research Database (Denmark)

Rasmussen, Matias Sevel; Dohn, Anders Høeg; Larsen, Jesper

to be scheduled with a certain slack between them. They refer to the vehicle problem as having interdependent time windows. Temporal dependencies have been modeled for a home care routing problem in a mixed integer programming model (MIP) which was solved with a standard MIP solver. An application with general...

Multi-objective scheduling of electric vehicles in smart distribution system

International Nuclear Information System (INIS)

Zakariazadeh, Alireza; Jadid, Shahram; Siano, Pierluigi

2014-01-01

Highlights: • Environmental/economic operational scheduling of electric vehicles. • The Vehicle to Grid capability and the actual patterns of drivers are considered. • A novel conceptual model for an electric vehicle management system is proposed. - Abstract: When preparing for the widespread adoption of Electric Vehicles (EVs), an important issue is to use a proper EVs’ charging/discharging scheduling model that is able to simultaneously consider economic and environmental goals as well as technical constraints of distribution networks. This paper proposes a multi-objective operational scheduling method for charging/discharging of EVs in a smart distribution system. The proposed multi-objective framework, based on augmented ε-constraint method, aims at minimizing the total operational costs and emissions. The Vehicle to Grid (V2G) capability as well as the actual patterns of drivers are considered in order to generate the Pareto-optimal solutions. The Benders decomposition technique is used in order to solve the proposed optimization model and to convert the large scale mixed integer nonlinear problem into mixed-integer linear programming and nonlinear programming problems. The effectiveness of the proposed resources scheduling approach is tested on a 33-bus distribution test system over a 24-h period. The results show that the proposed EVs’ charging/discharging method can reduce both of operation cost and air pollutant emissions

Vehicle Routing with Traffic Congestion and Drivers' Driving and Working Rules

NARCIS (Netherlands)

Kok, A.L.; Hans, Elias W.; Schutten, Johannes M.J.; Zijm, Willem H.M.

2010-01-01

For the intensively studied vehicle routing problem (VRP), two real-life restrictions have received only minor attention in the VRP-literature: traffic congestion and driving hours regulations. Traffic congestion causes late arrivals at customers and long travel times resulting in large transport

Lagrangian duality applied to the vehicle routing problem with time windows

DEFF Research Database (Denmark)

Kallehauge, Brian; Larsen, Jesper; Madsen, Oli B.G.

2006-01-01

This paper considers the vehicle routing problem with time windows, where the service of each customer must start within a specified time interval. We consider the Lagrangian relaxation of the constraint set requiring that each customer must be served by exactly one vehicle yielding a constrained...... respectively, which to date are the largest problems ever solved to optimality. We have implemented the LBCP algorithm using the ABACUS open-source framework for solving mixed-integer linear-programs by branch, cut, and price....

The waste collection vehicle routing problem with time windows in a city logistics context

DEFF Research Database (Denmark)

Buhrkal, Katja Frederik; Larsen, Allan; Røpke, Stefan

2012-01-01

Collection of waste is an important logistic activity within any city. In this paper we study how to collect waste in an efficient way. We study the Waste Collection Vehicle Routing Problem with Time Window which is concerned with finding cost optimal routes for garbage trucks such that all garbage...

Self-Organization Scheme for Balanced Routing in Large-Scale Multi-Hop Networks

DEFF Research Database (Denmark)

Badiu, Mihai Alin; Saad, David; Coon, Justin P.

2018-01-01

We propose a self-organization scheme for cost-effective and load-balanced routing in multi-hop networks. To avoid overloading nodes that provide favourable routing conditions, we assign each node with a cost function that penalizes high loads. Thus, finding routes to sink nodes is formulated...

A Cross-Layer Routing Design for Multi-Interface Wireless Mesh Networks

Directory of Open Access Journals (Sweden)

Tzu-Chieh Tsai

2009-01-01

Full Text Available In recent years, Wireless Mesh Networks (WMNs technologies have received significant attentions. WMNs not only accede to the advantages of ad hoc networks but also provide hierarchical multi-interface architecture. Transmission power control and routing path selections are critical issues in the past researches of multihop networks. Variable transmission power levels lead to different network connectivity and interference. Further, routing path selections among different radio interfaces will also produce different intra-/interflow interference. These features tightly affect the network performance. Most of the related works on the routing protocol design do not consider transmission power control and multi-interface environment simultaneously. In this paper, we proposed a cross-layer routing protocol called M2iRi2 which coordinates transmission power control and intra-/interflow interference considerations as routing metrics. Each radio interface calculates the potential tolerable-added transmission interference in the physical layer. When the route discovery starts, the M2iRi2 will adopt the appropriate power level to evaluate each interface quality along paths. The simulation results demonstrate that our design can enhance both network throughput and end-to-end delay.

Analysis of route availability in inter-working multi-hop wireless networks

CSIR Research Space (South Africa)

Salami, O

2009-07-01

Full Text Available In order to link a source-destination node pair in inter-working multi-hop wireless networks, links or routes must first be available. It is only after establishing the availability of links and routes between nodes that factors which affect...

Branch-and-cut algorithms for the split delivery vehicle routing problem

NARCIS (Netherlands)

Archetti, Claudia; Bianchessi, Nicola; Speranza, M. Grazia

2014-01-01

In this paper we present two exact branch-and-cut algorithms for the Split Delivery Vehicle Routing Problem (SDVRP) based on two relaxed formulations that provide lower bounds to the optimum. Procedures to obtain feasible solutions to the SDVRP from a feasible solution to the relaxed formulations

Routing of Electric Vehicles: Case Study of City Distribution in Copenhagen

DEFF Research Database (Denmark)

Linde, Esben; Larsen, Allan; Nørrelund, Anders Vedsted

freight magnitude and the distribution of goods in the old city centre. Based on the survey, analysis of possible UCC locations was carried out using simulation. Distribution from the UCC is assumed to be conducted with electric vehicles (EVs) as they are considered suitable for the overall aim. However...... a tour. Furthermore, intelligent location of these recharging points is considered. The objective is to find a least cost plan for routing and recharging the vehicles so that each customer is serviced by exactly one vehicle within its time windows and the vehicle capacity and driving range constraints...... are satisfied. The EVRPTW is a new problem that only has received little attention in the literature; see for example [2] and [3]. The costs are compared to distribution conducted by conventional vehicles. A heuristic method is developed and tested on the data generated on the basis of real-life collected data...

QoS Routing in Ad-Hoc Networks Using GA and Multi-Objective Optimization

Directory of Open Access Journals (Sweden)

Admir Barolli

2011-01-01

Full Text Available Much work has been done on routing in Ad-hoc networks, but the proposed routing solutions only deal with the best effort data traffic. Connections with Quality of Service (QoS requirements, such as voice channels with delay and bandwidth constraints, are not supported. The QoS routing has been receiving increasingly intensive attention, but searching for the shortest path with many metrics is an NP-complete problem. For this reason, approximated solutions and heuristic algorithms should be developed for multi-path constraints QoS routing. Also, the routing methods should be adaptive, flexible, and intelligent. In this paper, we use Genetic Algorithms (GAs and multi-objective optimization for QoS routing in Ad-hoc Networks. In order to reduce the search space of GA, we implemented a search space reduction algorithm, which reduces the search space for GAMAN (GA-based routing algorithm for Mobile Ad-hoc Networks to find a new route. We evaluate the performance of GAMAN by computer simulations and show that GAMAN has better behaviour than GLBR (Genetic Load Balancing Routing.

Computer-Assisted Periodical Routing and Renewal Audit

Science.gov (United States)

Yerkey, A. Neil

1973-01-01

A computer-assisted periodical control system was designed to reduce clerical time required to maintain records in three areas: renewal audit, routing, and records-keeping. The renewal audit features are unusual and are described in detail. (3 references) (Author/DH)

Bees do not use nearest-neighbour rules for optimization of multi-location routes.

Science.gov (United States)

Lihoreau, Mathieu; Chittka, Lars; Le Comber, Steven C; Raine, Nigel E

2012-02-23

Animals collecting patchily distributed resources are faced with complex multi-location routing problems. Rather than comparing all possible routes, they often find reasonably short solutions by simply moving to the nearest unvisited resources when foraging. Here, we report the travel optimization performance of bumble-bees (Bombus terrestris) foraging in a flight cage containing six artificial flowers arranged such that movements between nearest-neighbour locations would lead to a long suboptimal route. After extensive training (80 foraging bouts and at least 640 flower visits), bees reduced their flight distances and prioritized shortest possible routes, while almost never following nearest-neighbour solutions. We discuss possible strategies used during the establishment of stable multi-location routes (or traplines), and how these could allow bees and other animals to solve complex routing problems through experience, without necessarily requiring a sophisticated cognitive representation of space.

Routing the asteroid surface vehicle with detailed mechanics

Science.gov (United States)

Yu, Yang; Baoyin, He-Xi

2014-06-01

The motion of a surface vehicle on/above an irregular object is investigated for a potential interest in the insitu explorations to asteroids of the solar system. A global valid numeric method, including detailed gravity and geomorphology, is developed to mimic the behaviors of the test particles governed by the orbital equations and surface coupling effects. A general discussion on the surface mechanical environment of a specified asteroid, 1620 Geographos, is presented to make a global evaluation of the surface vehicle's working conditions. We show the connections between the natural trajectories near the ground and differential features of the asteroid surface, which describes both the good and bad of typical terrains from the viewpoint of vehicles' dynamic performances. Monte Carlo simulations are performed to take a further look at the trajectories of particles initializing near the surface. The simulations reveal consistent conclusions with the analysis, i.e., the open-field flat ground and slightly concave basins/valleys are the best choices for the vehicles' dynamical security. The dependence of decending trajectories on the releasing height is studied as an application; the results show that the pole direction (where the centrifugal force is zero) is the most stable direction in which the shift of a natural trajectory will be well limited after landing. We present this work as an example for pre-analysis that provides guidance to engineering design of the exploration site and routing the surface vehicles.

Dynamic Vehicle Routing Problems with Enhanced Ant Colony Optimization

Directory of Open Access Journals (Sweden)

Haitao Xu

2018-01-01

Full Text Available As we all know, there are a great number of optimization problems in the world. One of the relatively complicated and high-level problems is the vehicle routing problem (VRP. Dynamic vehicle routing problem (DVRP is a major variant of VRP, and it is closer to real logistic scene. In DVRP, the customers’ demands appear with time, and the unserved customers’ points must be updated and rearranged while carrying out the programming paths. Owing to the complexity and significance of the problem, DVRP applications have grabbed the attention of researchers in the past two decades. In this paper, we have two main contributions to solving DVRP. Firstly, DVRP is solved with enhanced Ant Colony Optimization (E-ACO, which is the traditional Ant Colony Optimization (ACO fusing improved K-means and crossover operation. K-means can divide the region with the most reasonable distance, while ACO using crossover is applied to extend search space and avoid falling into local optimum prematurely. Secondly, several new evaluation benchmarks are proposed, which can objectively and comprehensively estimate the proposed method. In the experiment, the results for different scale problems are compared to those of previously published papers. Experimental results show that the algorithm is feasible and efficient.

Simulation of product distribution at PT Anugrah Citra Boga by using capacitated vehicle routing problem method

Science.gov (United States)

Lamdjaya, T.; Jobiliong, E.

2017-01-01

PT Anugrah Citra Boga is a food processing industry that produces meatballs as their main product. The distribution system of the products must be considered, because it needs to be more efficient in order to reduce the shipment cost. The purpose of this research is to optimize the distribution time by simulating the distribution channels with capacitated vehicle routing problem method. Firstly, the distribution route is observed in order to calculate the average speed, time capacity and shipping costs. Then build the model using AIMMS software. A few things that are required to simulate the model are customer locations, distances, and the process time. Finally, compare the total distribution cost obtained by the simulation and the historical data. It concludes that the company can reduce the shipping cost around 4.1% or Rp 529,800 per month. By using this model, the utilization rate can be more optimal. The current value for the first vehicle is 104.6% and after the simulation it becomes 88.6%. Meanwhile, the utilization rate of the second vehicle is increase from 59.8% to 74.1%. The simulation model is able to produce the optimal shipping route with time restriction, vehicle capacity, and amount of vehicle.

Node Load Balance Multi-flow Opportunistic Routing in Wireless Mesh Networks

Directory of Open Access Journals (Sweden)

Wang Tao

2014-04-01

Full Text Available Opportunistic routing (OR has been proposed to improve the performance of wireless networks by exploiting the multi-user diversity and broadcast nature of the wireless medium. It involves multiple candidate forwarders to relay packets every hop. The existing OR doesn’t take account of the traffic load and load balance, therefore some nodes may be overloaded while the others may not, leading to network performance decline. In this paper, we focus on opportunities routing selection with node load balance which is described as a convex optimization problem. To solve the problem, by combining primal-dual and sub-gradient methods, a fully distributed Node load balance Multi-flow Opportunistic Routing algorithm (NMOR is proposed. With node load balance constraint, NMOR allocates the flow rate iteratively and the rate allocation decides the candidate forwarder selection of opportunities routing. The simulation results show that NMOR algorithm improves 100 %, 62 % of the aggregative throughput than ETX and EAX, respectively.

Partial path column generation for the vehicle routing problem with time windows

DEFF Research Database (Denmark)

Petersen, Bjørn; Jepsen, Mads Kehlet

2009-01-01

This paper presents a column generation algorithm for the Vehicle Routing Problem with Time Windows (VRPTW). Traditionally, column generation models of the VRPTW have consisted of a Set Partitioning master problem with each column representing a route, i.e., a resource feasible path starting...... and ending at the depot. Elementary routes (no customer visited more than once) have shown superior results on difficult instances (less restrictive capacity and time windows). However, the pricing problems do not scale well when the number of feasible routes increases, i.e., when a route may contain a large...... number of customers. We suggest to relax that ‘each column is a route’ into ‘each column is a part of the giant tour’; a so-called partial path, i.e., not necessarily starting and ending in the depot. This way, the length of the partial path can be bounded and a better control of the size of the solution...

Genetic algorithm with Lin-Kernighan heuristic as a substep of solving the multinomenclature vehicle routing problem

Directory of Open Access Journals (Sweden)

T.A. Yakovleva

2011-05-01

Full Text Available This paper is dealing with the vehicle routing problem, where different types of vehicles are managing to deliver different types of products. Three step heuristic with genetic algorithm is proposed for solving the problem.

Improvement of Network Performance by In-Vehicle Routing Using Floating Car Data

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Gerdien A. Klunder

2017-01-01

Full Text Available This paper describes a study which gives insight into the size of improvement that is possible with individual in-car routing advice based on the actual traffic situation derived from floating car data (FCD. It also gives an idea about the required penetration rate of floating car data needed to achieve a certain degree of improvement. The study uses real loop detector data from the region of Amsterdam collected for over a year, a route generating algorithm for in-car routing advice, and emulated floating car data to generate the routing advice. The case with in-car routing advice has been compared to the base case, where drivers base their routing decisions on average knowledge of travel times in the network. The improvement in total delay using the in-vehicle system is dependent on penetration rate and accuracy of the floating car data and varies from 2.0% to 3.4% for 10% penetration rate. This leads to yearly savings of about 15 million euros if delay is monetarised using standard prices for value of time (VOT.

Dynamic Vehicle Routing Using an Improved Variable Neighborhood Search Algorithm

Directory of Open Access Journals (Sweden)

Yingcheng Xu

2013-01-01

Full Text Available In order to effectively solve the dynamic vehicle routing problem with time windows, the mathematical model is established and an improved variable neighborhood search algorithm is proposed. In the algorithm, allocation customers and planning routes for the initial solution are completed by the clustering method. Hybrid operators of insert and exchange are used to achieve the shaking process, the later optimization process is presented to improve the solution space, and the best-improvement strategy is adopted, which make the algorithm can achieve a better balance in the solution quality and running time. The idea of simulated annealing is introduced to take control of the acceptance of new solutions, and the influences of arrival time, distribution of geographical location, and time window range on route selection are analyzed. In the experiment, the proposed algorithm is applied to solve the different sizes' problems of DVRP. Comparing to other algorithms on the results shows that the algorithm is effective and feasible.

Routing protocol for wireless quantum multi-hop mesh backbone network based on partially entangled GHZ state

Science.gov (United States)

Xiong, Pei-Ying; Yu, Xu-Tao; Zhang, Zai-Chen; Zhan, Hai-Tao; Hua, Jing-Yu

2017-08-01

Quantum multi-hop teleportation is important in the field of quantum communication. In this study, we propose a quantum multi-hop communication model and a quantum routing protocol with multihop teleportation for wireless mesh backbone networks. Based on an analysis of quantum multi-hop protocols, a partially entangled Greenberger-Horne-Zeilinger (GHZ) state is selected as the quantum channel for the proposed protocol. Both quantum and classical wireless channels exist between two neighboring nodes along the route. With the proposed routing protocol, quantum information can be transmitted hop by hop from the source node to the destination node. Based on multi-hop teleportation based on the partially entangled GHZ state, a quantum route established with the minimum number of hops. The difference between our routing protocol and the classical one is that in the former, the processes used to find a quantum route and establish quantum channel entanglement occur simultaneously. The Bell state measurement results of each hop are piggybacked to quantum route finding information. This method reduces the total number of packets and the magnitude of air interface delay. The deduction of the establishment of a quantum channel between source and destination is also presented here. The final success probability of quantum multi-hop teleportation in wireless mesh backbone networks was simulated and analyzed. Our research shows that quantum multi-hop teleportation in wireless mesh backbone networks through a partially entangled GHZ state is feasible.

Evolving intelligent vehicle control using multi-objective NEAT

NARCIS (Netherlands)

Willigen, W.H. van; Haasdijk, E.; Kester, L.J.H.M.

2013-01-01

The research in this paper is inspired by a vision of intelligent vehicles that autonomously move along motorways: they join and leave trains of vehicles (platoons), overtake other vehicles, etc. We propose a multi-objective algorithm based on NEAT and SPEA2 that evolves controllers for such

Optimal Routing for Heterogeneous Fixed Fleets of Multicompartment Vehicles

Directory of Open Access Journals (Sweden)

Qian Wang

2014-01-01

Full Text Available We present a metaheuristic called the reactive guided tabu search (RGTS to solve the heterogeneous fleet multicompartment vehicle routing problem (MCVRP, where a single vehicle is required for cotransporting multiple customer orders. MCVRP is commonly found in delivery of fashion apparel, petroleum distribution, food distribution, and waste collection. In searching the optimum solution of MCVRP, we need to handle a large amount of local optima in the solution spaces. To overcome this problem, we design three guiding mechanisms in which the search history is used to guide the search. The three mechanisms are experimentally demonstrated to be more efficient than the ones which only apply the known distance information. Armed with the guiding mechanisms and the well-known reactive mechanism, the RGTS can produce remarkable solutions in a reasonable computation time.

A novel communication mechanism based on node potential multi-path routing

Science.gov (United States)

Bu, Youjun; Zhang, Chuanhao; Jiang, YiMing; Zhang, Zhen

2016-10-01

With the network scales rapidly and new network applications emerge frequently, bandwidth supply for today's Internet could not catch up with the rapid increasing requirements. Unfortunately, irrational using of network sources makes things worse. Actual network deploys single-next-hop optimization paths for data transmission, but such "best effort" model leads to the imbalance use of network resources and usually leads to local congestion. On the other hand Multi-path routing can use the aggregation bandwidth of multi paths efficiently and improve the robustness of network, security, load balancing and quality of service. As a result, multi-path has attracted much attention in the routing and switching research fields and many important ideas and solutions have been proposed. This paper focuses on implementing the parallel transmission of multi next-hop data, balancing the network traffic and reducing the congestion. It aimed at exploring the key technologies of the multi-path communication network, which could provide a feasible academic support for subsequent applications of multi-path communication networking. It proposed a novel multi-path algorithm based on node potential in the network. And the algorithm can fully use of the network link resource and effectively balance network link resource utilization.

A hybrid meta-heuristic algorithm for the vehicle routing problem with stochastic travel times considering the driver's satisfaction

Science.gov (United States)

Tavakkoli-Moghaddam, Reza; Alinaghian, Mehdi; Salamat-Bakhsh, Alireza; Norouzi, Narges

2012-05-01

A vehicle routing problem is a significant problem that has attracted great attention from researchers in recent years. The main objectives of the vehicle routing problem are to minimize the traveled distance, total traveling time, number of vehicles and cost function of transportation. Reducing these variables leads to decreasing the total cost and increasing the driver's satisfaction level. On the other hand, this satisfaction, which will decrease by increasing the service time, is considered as an important logistic problem for a company. The stochastic time dominated by a probability variable leads to variation of the service time, while it is ignored in classical routing problems. This paper investigates the problem of the increasing service time by using the stochastic time for each tour such that the total traveling time of the vehicles is limited to a specific limit based on a defined probability. Since exact solutions of the vehicle routing problem that belong to the category of NP-hard problems are not practical in a large scale, a hybrid algorithm based on simulated annealing with genetic operators was proposed to obtain an efficient solution with reasonable computational cost and time. Finally, for some small cases, the related results of the proposed algorithm were compared with results obtained by the Lingo 8 software. The obtained results indicate the efficiency of the proposed hybrid simulated annealing algorithm.

Multiobjective Quantum Evolutionary Algorithm for the Vehicle Routing Problem with Customer Satisfaction

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Jingling Zhang

2012-01-01

Full Text Available The multiobjective vehicle routing problem considering customer satisfaction (MVRPCS involves the distribution of orders from several depots to a set of customers over a time window. This paper presents a self-adaptive grid multi-objective quantum evolutionary algorithm (MOQEA for the MVRPCS, which takes into account customer satisfaction as well as travel costs. The degree of customer satisfaction is represented by proposing an improved fuzzy due-time window, and the optimization problem is modeled as a mixed integer linear program. In the MOQEA, nondominated solution set is constructed by the Challenge Cup rules. Moreover, an adaptive grid is designed to achieve the diversity of solution sets; that is, the number of grids in each generation is not fixed but is automatically adjusted based on the distribution of the current generation of nondominated solution set. In the study, the MOQEA is evaluated by applying it to classical benchmark problems. Results of numerical simulation and comparison show that the established model is valid and the MOQEA is effective for MVRPCS.

A Constraint-Based Model for Fast Post-Disaster Emergency Vehicle Routing

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Roberto Amadini

2013-12-01

Full Text Available Disasters like terrorist attacks, earthquakes, hurricanes, and volcano eruptions are usually unpredictable events that affect a high number of people. We propose an approach that could be used as a decision support tool for a post-disaster response that allows the assignment of victims to hospitals and organizes their transportation via emergency vehicles. By exploiting the synergy between Mixed Integer Programming and Constraint Programming techniques, we are able to compute the routing of the vehicles so as to rescue much more victims than both heuristic based and complete approaches in a very reasonable time.

An Efficient Two-Objective Hybrid Local Search Algorithm for Solving the Fuel Consumption Vehicle Routing Problem

OpenAIRE

Rao, Weizhen; Liu, Feng; Wang, Shengbin

2016-01-01

The classical model of vehicle routing problem (VRP) generally minimizes either the total vehicle travelling distance or the total number of dispatched vehicles. Due to the increased importance of environmental sustainability, one variant of VRPs that minimizes the total vehicle fuel consumption has gained much attention. The resulting fuel consumption VRP (FCVRP) becomes increasingly important yet difficult. We present a mixed integer programming model for the FCVRP, and fuel consumption is ...

Inventory slack routing application in emergency logistics and relief distributions.

Science.gov (United States)

Yang, Xianfeng; Hao, Wei; Lu, Yang

2018-01-01

Various natural and manmade disasters during last decades have highlighted the need of further improving on governmental preparedness to emergency events, and a relief supplies distribution problem named Inventory Slack Routing Problem (ISRP) has received increasing attentions. In an ISRP, inventory slack is defined as the duration between reliefs arriving time and estimated inventory stock-out time. Hence, a larger inventory slack could grant more responsive time in facing of various factors (e.g., traffic congestion) that may lead to delivery lateness. In this study, the relief distribution problem is formulated as an optimization model that maximize the minimum slack among all dispensing sites. To efficiently solve this problem, we propose a two-stage approach to tackle the vehicle routing and relief allocation sub-problems. By analyzing the inter-relations between these two sub-problems, a new objective function considering both delivery durations and dispensing rates of demand sites is applied in the first stage to design the vehicle routes. A hierarchical routing approach and a sweep approach are also proposed in this stage. Given the vehicle routing plan, the relief allocation could be easily solved in the second stage. Numerical experiment with a comparison of multi-vehicle Traveling Salesman Problem (TSP) has demonstrated the need of ISRP and the capability of the proposed solution approaches.

A Hybrid Chaos-Particle Swarm Optimization Algorithm for the Vehicle Routing Problem with Time Window

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Qi Hu

2013-04-01

Full Text Available State-of-the-art heuristic algorithms to solve the vehicle routing problem with time windows (VRPTW usually present slow speeds during the early iterations and easily fall into local optimal solutions. Focusing on solving the above problems, this paper analyzes the particle encoding and decoding strategy of the particle swarm optimization algorithm, the construction of the vehicle route and the judgment of the local optimal solution. Based on these, a hybrid chaos-particle swarm optimization algorithm (HPSO is proposed to solve VRPTW. The chaos algorithm is employed to re-initialize the particle swarm. An efficient insertion heuristic algorithm is also proposed to build the valid vehicle route in the particle decoding process. A particle swarm premature convergence judgment mechanism is formulated and combined with the chaos algorithm and Gaussian mutation into HPSO when the particle swarm falls into the local convergence. Extensive experiments are carried out to test the parameter settings in the insertion heuristic algorithm and to evaluate that they are corresponding to the data’s real-distribution in the concrete problem. It is also revealed that the HPSO achieves a better performance than the other state-of-the-art algorithms on solving VRPTW.

Approximation algorithms for deadline-TSP and vehicle routing with time-windows

NARCIS (Netherlands)

Bansal, N.; Blum, A.; Chawla, S.; Meyerson, A.; Babai, L.

2004-01-01

Given a metric space G on n nodes, with a start node r and deadlines D(v) for each vertex v, we consider the Deadline-TSP problem of finding a path starting at r that visits as many nodes as possible by their deadlines. We also consider the more general Vehicle Routing with Time-Windows problem, in

Multiple Charging Station Location-Routing Problem with Time Window of Electric Vehicle

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Wang Li-ying

2015-11-01

Full Text Available This paper presents the electric vehicle (EV multiple charging station location-routing problem with time window to optimize the routing plan of capacitated EVs and the strategy of charging stations. In particular, the strategy of charging stations includes both infrastructure-type selection and station location decisions. The problem accounts for two critical constraints in logistic practice: the vehicle loading capacity and the customer time windows. A hybrid heuristic that incorporates an adaptive variable neighborhood search (AVNS with the tabu search algorithm for intensification was developed to address the problem. The specialized neighborhood structures and the selection methods of charging station used in the shaking step of AVNS were proposed. In contrast to the commercial solver CPLEX, experimental results on small-scale test instances demonstrate that the algorithm can find nearly optimal solutions on small-scale instances. The results on large-scale instances also show the effectiveness of the algorithm.

Vehicle Routing Problems with Fuel Consumption and Stochastic Travel Speeds

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Yanling Feng

2017-01-01

Full Text Available Conventional vehicle routing problems (VRP always assume that the vehicle travel speed is fixed or time-dependent on arcs. However, due to the uncertainty of weather, traffic conditions, and other random factors, it is not appropriate to set travel speeds to fixed constants in advance. Consequently, we propose a mathematic model for calculating expected fuel consumption and fixed vehicle cost where average speed is assumed to obey normal distribution on each arc which is more realistic than the existing model. For small-scaled problems, we make a linear transformation and solve them by existing solver CPLEX, while, for large-scaled problems, an improved simulated annealing (ISA algorithm is constructed. Finally, instances from real road networks of England are performed with the ISA algorithm. Computational results show that our ISA algorithm performs well in a reasonable amount of time. We also find that when taking stochastic speeds into consideration, the fuel consumption is always larger than that with fixed speed model.

Minimum Makespan Multi-vehicle Dial-a-Ride

DEFF Research Database (Denmark)

Gørtz, Inge Li; Nagarajan, Viswanath; Ravi, R.

2009-01-01

be left at intermediate vertices and transported by more than one vehicle, while being moved from source to destination. Approximation algorithms for the single vehicle Dial-a-Ride problem (q = 1) have been considered in [3,10]. Our main results are an O(log3n)-approximation algorithm for preemptive multi...

Vehicle Routing Problem for Fashion Supply Chains with Cross-Docking

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Zhi-Hua Hu

2013-01-01

Full Text Available Cross-docking, as a strategy to reduce lead time and enhance the efficiency of the fashion supply chain, has attracted substantial attention from both the academy and the industry. Cross-docking is a critical part of many fashion and textiles supply chains in practice because it can help to achieve many supply chain strategies such as postponement. We consider a model where there are multiple suppliers and customers in a single cross-docking center. With such a model setting, the issue concerning the coordinated routing between the inbound and outbound routes is much more complex than many traditional vehicle routing problems (VRPs. We formulate the optimal route selection problems from the suppliers to the cross-docking center and from the cross-docking center to the customers as the respective VRPs. Based on the relationships between the suppliers and the customers, we integrate the two VRP models to optimize the overall traveling time, distance, and waiting time at the cross-docking center. In addition, we propose a novel mixed 0/1 integer linear programming model by which the complexity of the problem can be reduced significantly. As demonstrated by the simulation analysis, our proposed model can be solved very efficiently by a commonly used optimization software package.

Formulations and exact algorithms for the vehicle routing problem with time windows

DEFF Research Database (Denmark)

Kallehauge, Brian

2008-01-01

In this paper we review the exact algorithms proposed in the last three decades for the solution of the vehicle routing problem with time windows (VRPTW). The exact algorithms for the VRPTW are in many aspects inherited from work on the traveling salesman problem (TSP). In recognition of this fact...

A Novel Spatial-Temporal Voronoi Diagram-Based Heuristic Approach for Large-Scale Vehicle Routing Optimization with Time Constraints

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Wei Tu

2015-10-01

Full Text Available Vehicle routing optimization (VRO designs the best routes to reduce travel cost, energy consumption, and carbon emission. Due to non-deterministic polynomial-time hard (NP-hard complexity, many VROs involved in real-world applications require too much computing effort. Shortening computing time for VRO is a great challenge for state-of-the-art spatial optimization algorithms. From a spatial-temporal perspective, this paper presents a spatial-temporal Voronoi diagram-based heuristic approach for large-scale vehicle routing problems with time windows (VRPTW. Considering time constraints, a spatial-temporal Voronoi distance is derived from the spatial-temporal Voronoi diagram to find near neighbors in the space-time searching context. A Voronoi distance decay strategy that integrates a time warp operation is proposed to accelerate local search procedures. A spatial-temporal feature-guided search is developed to improve unpromising micro route structures. Experiments on VRPTW benchmarks and real-world instances are conducted to verify performance. The results demonstrate that the proposed approach is competitive with state-of-the-art heuristics and achieves high-quality solutions for large-scale instances of VRPTWs in a short time. This novel approach will contribute to spatial decision support community by developing an effective vehicle routing optimization method for large transportation applications in both public and private sectors.

A memory structure adapted simulated annealing algorithm for a green vehicle routing problem.

Science.gov (United States)

Küçükoğlu, İlker; Ene, Seval; Aksoy, Aslı; Öztürk, Nursel

2015-03-01

Currently, reduction of carbon dioxide (CO2) emissions and fuel consumption has become a critical environmental problem and has attracted the attention of both academia and the industrial sector. Government regulations and customer demands are making environmental responsibility an increasingly important factor in overall supply chain operations. Within these operations, transportation has the most hazardous effects on the environment, i.e., CO2 emissions, fuel consumption, noise and toxic effects on the ecosystem. This study aims to construct vehicle routes with time windows that minimize the total fuel consumption and CO2 emissions. The green vehicle routing problem with time windows (G-VRPTW) is formulated using a mixed integer linear programming model. A memory structure adapted simulated annealing (MSA-SA) meta-heuristic algorithm is constructed due to the high complexity of the proposed problem and long solution times for practical applications. The proposed models are integrated with a fuel consumption and CO2 emissions calculation algorithm that considers the vehicle technical specifications, vehicle load, and transportation distance in a green supply chain environment. The proposed models are validated using well-known instances with different numbers of customers. The computational results indicate that the MSA-SA heuristic is capable of obtaining good G-VRPTW solutions within a reasonable amount of time by providing reductions in fuel consumption and CO2 emissions.

A branch-and-cut algorithm for the Time Window Assignment Vehicle Routing Problem

NARCIS (Netherlands)

K. Dalmeijer (Kevin); R. Spliet (Remy)

2016-01-01

textabstractThis paper presents a branch-and-cut algorithm for the Time Window Assignment Vehicle Routing Problem (TWAVRP), the problem of assigning time windows for delivery before demand volume becomes known. A novel set of valid inequalities, the precedence inequalities, is introduced and

Applications of a saving method with max-min ant system to a vehicle routing problem with time windows and speed limits

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Suphan Sodsoon

2014-06-01

Full Text Available This study aims to solve a Vehicle Routing Problem with Time Windows and Speed Limits (VRPTWSL, which has received considerable attention in recent years. The vehicle routing problem with time windows is an extension of the well-known Vehicle Routing Problem (VRP and involves a fleet of vehicles set of from a depot to serve a number of customers at different geographic locations with various demands within specific time and speed limits before returning to the depot eventually. To solve the problem, an efficient Saving Method-Max Min Ant System (Saving-MMAS with Local Search algorithm is applied. Using minimization of the total transportation costs as the objective of the extension VRPTWSL, a mathematic model is constructed. Finally, the Saving-MMAS algorithms indicated the good quality of the method in this problem.

The life and times of the Savings Method for Vehicle Routing Problems

African Journals Online (AJOL)

Forty ve years ago, an academic and practitioner from the north of England published a method of tackling the vehicle routing problem (VRP) in an American journal. Little could they have realised how the method they devised would still be a signicant part of the research agenda nearly half a century later. Adaptations of ...

The Edge Set Cost of the Vehicle Routing Problem with Time Windows

DEFF Research Database (Denmark)

Reinhardt, Line Blander; Jepsen, Mads Kehlet; Pisinger, David

2016-01-01

. The certifications and investments impose a cost for the company while they also give unlimited usage of a set of roads to all vehicles belonging to the company. This violates the traditional assumption that the path between two destinations is well defined and independent of other choices. Different versions......We consider an important generalization of the vehicle routing problem with time windows in which a fixed cost must be paid for accessing a set of edges. This fixed cost could reflect payment for toll roads, investment in new facilities, the need for certifications, and other costly investments...

Solving a bi-objective mathematical model for location-routing problem with time windows in multi-echelon reverse logistics using metaheuristic procedure

Science.gov (United States)

Ghezavati, V. R.; Beigi, M.

2016-12-01

During the last decade, the stringent pressures from environmental and social requirements have spurred an interest in designing a reverse logistics (RL) network. The success of a logistics system may depend on the decisions of the facilities locations and vehicle routings. The location-routing problem (LRP) simultaneously locates the facilities and designs the travel routes for vehicles among established facilities and existing demand points. In this paper, the location-routing problem with time window (LRPTW) and homogeneous fleet type and designing a multi-echelon, and capacitated reverse logistics network, are considered which may arise in many real-life situations in logistics management. Our proposed RL network consists of hybrid collection/inspection centers, recovery centers and disposal centers. Here, we present a new bi-objective mathematical programming (BOMP) for LRPTW in reverse logistic. Since this type of problem is NP-hard, the non-dominated sorting genetic algorithm II (NSGA-II) is proposed to obtain the Pareto frontier for the given problem. Several numerical examples are presented to illustrate the effectiveness of the proposed model and algorithm. Also, the present work is an effort to effectively implement the ɛ-constraint method in GAMS software for producing the Pareto-optimal solutions in a BOMP. The results of the proposed algorithm have been compared with the ɛ-constraint method. The computational results show that the ɛ-constraint method is able to solve small-size instances to optimality within reasonable computing times, and for medium-to-large-sized problems, the proposed NSGA-II works better than the ɛ-constraint.

Bi-objective optimization for multi-modal transportation routing planning problem based on Pareto optimality

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Yan Sun

2015-09-01

Full Text Available Purpose: The purpose of study is to solve the multi-modal transportation routing planning problem that aims to select an optimal route to move a consignment of goods from its origin to its destination through the multi-modal transportation network. And the optimization is from two viewpoints including cost and time. Design/methodology/approach: In this study, a bi-objective mixed integer linear programming model is proposed to optimize the multi-modal transportation routing planning problem. Minimizing the total transportation cost and the total transportation time are set as the optimization objectives of the model. In order to balance the benefit between the two objectives, Pareto optimality is utilized to solve the model by gaining its Pareto frontier. The Pareto frontier of the model can provide the multi-modal transportation operator (MTO and customers with better decision support and it is gained by the normalized normal constraint method. Then, an experimental case study is designed to verify the feasibility of the model and Pareto optimality by using the mathematical programming software Lingo. Finally, the sensitivity analysis of the demand and supply in the multi-modal transportation organization is performed based on the designed case. Findings: The calculation results indicate that the proposed model and Pareto optimality have good performance in dealing with the bi-objective optimization. The sensitivity analysis also shows the influence of the variation of the demand and supply on the multi-modal transportation organization clearly. Therefore, this method can be further promoted to the practice. Originality/value: A bi-objective mixed integer linear programming model is proposed to optimize the multi-modal transportation routing planning problem. The Pareto frontier based sensitivity analysis of the demand and supply in the multi-modal transportation organization is performed based on the designed case.

The Role of Spatial Ability in the Relationship Between Video Game Experience and Route Effectiveness Among Unmanned Vehicle Operators

Science.gov (United States)

2008-12-01

Effective route planning is essential to the successful operation of unmanned vehicles. Video game experience has been shown to affect route planning...and execution, but why video game experience helps has not been addressed. One answer may be that spatial skills, necessary for route planning and...mediates the relationship between video game experience and route planning. Results indicated that this mediated relationship existed for the UGV

Distributed Control in Multi-Vehicle Systems

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Paul A. Avery

2013-12-01

Full Text Available The Southwest Research Institute (SwRI Mobile Autonomous Robotics Technology Initiative (MARTI program has enabled the development of fully-autonomous passenger-sized commercial vehicles and military tactical vehicles, as well as the development of cooperative vehicle behaviors, such as cooperative sensor sharing and cooperative convoy operations. The program has also developed behaviors to interface intelligent vehicles with intelligent road-side devices. The development of intelligent vehicle behaviors cannot be approached as stand-alone phenomena; rather, they must be understood within a context of the broader traffic system dynamics. The study of other complex systems has shown that system-level behaviors emerge as a result of the spatio-temporal dynamics within a system's constituent parts. The design of such systems must therefore account for both the system-level emergent behavior, as well as behaviors of individuals within the system. It has also become clear over the past several years, for both of these domains, that human trust in the behavior of individual vehicles is paramount to broader technology adoption. This paper examines the interplay between individual vehicle capabilities, vehicle connectivity, and emergent system behaviors, and presents some considerations for a distributed control paradigm in a multi-vehicle system.

LOTIR: A Routing Protocol for Multi-hop V-to-I Communication Using Local Traffic Information

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Kun-chan Lan

2012-08-01

Full Text Available Vehicular Ad Hoc Network (VANET is an emerging technology that can be applied to safety, transport efficiency, or infotainment applications for roads and highways. However, due to its unique features, such as dynamic mobility patterns and uneven distributions of vehicles, VANET faces many challenging research issues for robust data dissemination in the network. Many routing protocols have been proposed for VANET in the past few years, and the idea of utilizing a navigation system to assist the routing protocol for selecting the next best forwarder has become increasingly popular. However, it might not be realistic to assume that every vehicle is equipped with a navigation system. In addition, due to privacy concerns, drivers might not want to reveal their planned routes to other cars. In this work, we propose a new routing protocol, called LOTIR (LOcal Traffic Information Routing, that relies on only local traffic information and does not require the assistance of a navigation system. LOTIR is a DTN-based routing protocol that utilizes the car-following theory and traffic light information to decide the next carrier to forward the data to. We implement LOTIR in NS-2, and our results show that it can achieve similar performance as prior work which depends on the availability of global network topology information.

Ant colony system (ACS with hybrid local search to solve vehicle routing problems

Directory of Open Access Journals (Sweden)

Suphan Sodsoon

2016-02-01

Full Text Available This research applied an Ant Colony System algorithm with a Hybrid Local Search to solve Vehicle Routing Problems (VRP from a single depot when the customers’ requirements are known. VRP is an NP-hard optimization problem and has usually been successfully solved optimum by heuristics. A fleet of vehicles of a specific capacity are used to serve a number of customers at minimum cost, without violating the constraints of vehicle capacity. There are meta-heuristic approaches to solve these problems, such as Simulated Annealing, Genetic Algorithm, Tabu Search and the Ant Colony System algorithm. In this case a hybrid local search was used (Cross-Exchange, Or-Opt and 2-Opt algorithm with an Ant Colony System algorithm. The Experimental Design was tested on 7 various problems from the data set online in the OR-Library. There are five different problems in which customers are randomly distributed with the depot in an approximately central location. The customers were grouped into clusters. The results are evaluated in terms of optimal routes using optimal distances. The experimental results are compared with those obtained from meta-heuristics and they show that the proposed method outperforms six meta-heuristics in the literature.

VANET Routing Protocols: Pros and Cons

OpenAIRE

Paul, Bijan; Ibrahim, Md.; Bikas, Md. Abu Naser

2012-01-01

VANET (Vehicular Ad-hoc Network) is a new technology which has taken enormous attention in the recent years. Due to rapid topology changing and frequent disconnection makes it difficult to design an efficient routing protocol for routing data among vehicles, called V2V or vehicle to vehicle communication and vehicle to road side infrastructure, called V2I. The existing routing protocols for VANET are not efficient to meet every traffic scenarios. Thus design of an efficient routing protocol h...

Research on Parameter Design of Multi - axis Hydrostatic Transmission Vehicle

Directory of Open Access Journals (Sweden)

Zhao Liang

2017-01-01

Full Text Available In order to obtain reasonable parameters in the design of driving system of multi-axis hydrostatic transmission vehicle, the working principle of single-side drive of hydrostatic transmission vehicle is introduced. The matching and control of engine and hydraulic pump are analyzed. According to the driving equation of vehicle, The driving force required for driving system is determined, and the parameters of hydraulic motor, hydraulic pump, system working pressure and braking system are designed and calculated, which provides the parameter design for driving system of multi-axis hydrostatic transmission Reliable theoretical basis.

The vehicle routing game: An application of cost allocation in a gas and oil company

Energy Technology Data Exchange (ETDEWEB)

Engevall, Stefan; Goethe-Lundgren, Maud; Vaerbrand, Peter

2000-12-01

In this article we study a cost allocation problem that arises in a distribution planning situation at the Logistics department at Norsk Hydro Olje AB. The routes from one depot during one day are considered, for which the total distribution cost is to be divided among the customers that are visited. This cost allocation problem is formulated as a vehicle routing game, allowing the use of vehicles with different capacities. Cost allocation methods based on different concepts from cooperative game theory, such as the core and the nucleolus, are discussed. A procedure that can be used to investigate whether the core is empty or not is presented, as well as a procedure to compute the nucleolus. Computational results for the Norsk Hydro case are also presented and discussed.

Multiple Attribute Decision Making Based Relay Vehicle Selection for Electric Vehicle Communication

Directory of Open Access Journals (Sweden)

Zhao Qiang

2015-01-01

Full Text Available Large-scale electric vehicle integration into power grid and charging randomly will cause serious impacts on the normal operation of power grid. Therefore, it is necessary to control the charging behavior of electric vehicle, while information transmission for electric vehicle is significant. Due to the highly mobile characteristics of vehicle, transferring information to power grid directly might be inaccessible. Relay vehicle (RV can be used for supporting multi-hop connection between SV and power grid. This paper proposes a multiple attribute decision making (MADM-based RV selection algorithm, which considers multiple attribute, including data transfer rate, delay, route duration. It takes the characteristics of electric vehicle communication into account, which can provide protection for the communication services of electric vehicle charging and discharging. Numerical results demonstrate that compared to previous algorithm, the proposed algorithm offer better performance in terms of throughput, transmission delay.

Similarity-Based Prediction of Travel Times for Vehicles Traveling on Known Routes

DEFF Research Database (Denmark)

Tiesyte, Dalia; Jensen, Christian Søndergaard

2008-01-01

, historical data in combination with real-time data may be used to predict the future travel times of vehicles more accurately, thus improving the experience of the users who rely on such information. We propose a Nearest-Neighbor Trajectory (NNT) technique that identifies the historical trajectory......The use of centralized, real-time position tracking is proliferating in the areas of logistics and public transportation. Real-time positions can be used to provide up-to-date information to a variety of users, and they can also be accumulated for uses in subsequent data analyses. In particular...... of vehicles that travel along known routes. In empirical studies with real data from buses, we evaluate how well the proposed distance functions are capable of predicting future vehicle movements. Second, we propose a main-memory index structure that enables incremental similarity search and that is capable...

Constraint Programming based Local Search for the Vehicle Routing Problem with Time Windows

OpenAIRE

Sala Reixach, Joan

2012-01-01

El projecte es centra en el "Vehicle Routing Problem with Time Windows". Explora i testeja un mètode basat en una formulació del problema en termes de programació de restriccions. Implementa un mètode de cerca local amb la capacitat de fer grans moviments anomenat "Large Neighbourhood Search".

Metaheuristics applied to vehicle routing. A case study. Parte 1: formulating the problem

Directory of Open Access Journals (Sweden)

Guillermo González Vargas

2006-09-01

Full Text Available This paper deals with VRP (vehicle routing problem mathematical formulation and presents some methodologies used by different authors to solve VRP variation. This paper is presented as the springboard for introducing future papers about a manufacturing company’s location decisions based on the total distance traveled to distribute its product.

The Dynamic Multi-objective Multi-vehicle Covering Tour Problem

Science.gov (United States)

2013-06-01

144 [38] Coello, Carlos A. Coello, Gary B Lamont, and David A Van Veldhuizen . Evolutionary Algorithms for Solving Multi-Objective Problems. Springer...Traveling Repairperson Problem (DTRP) Policies Proposed by Bertsimas and Van Ryzin. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25 3.3...queuing theory perspective. Table 3.2: DTRP Policies Proposed by Bertsimas and Van Ryzin. Name Description First Come First Serve (FCFS) vehicles

Multi-actuators vehicle collision avoidance system - Experimental validation

Science.gov (United States)

Hamid, Umar Zakir Abdul; Zakuan, Fakhrul Razi Ahmad; Akmal Zulkepli, Khairul; Zulfaqar Azmi, Muhammad; Zamzuri, Hairi; Rahman, Mohd Azizi Abdul; Aizzat Zakaria, Muhammad

2018-04-01

The Insurance Institute for Highway Safety (IIHS) of the United States of America in their reports has mentioned that a significant amount of the road mishaps would be preventable if more automated active safety applications are adopted into the vehicle. This includes the incorporation of collision avoidance system. The autonomous intervention by the active steering and braking systems in the hazardous scenario can aid the driver in mitigating the collisions. In this work, a real-time platform of a multi-actuators vehicle collision avoidance system is developed. It is a continuous research scheme to develop a fully autonomous vehicle in Malaysia. The vehicle is a modular platform which can be utilized for different research purposes and is denominated as Intelligent Drive Project (iDrive). The vehicle collision avoidance proposed design is validated in a controlled environment, where the coupled longitudinal and lateral motion control system is expected to provide desired braking and steering actuation in the occurrence of a frontal static obstacle. Results indicate the ability of the platform to yield multi-actuators collision avoidance navigation in the hazardous scenario, thus avoiding the obstacle. The findings of this work are beneficial for the development of a more complex and nonlinear real-time collision avoidance work in the future.

Split delivery vehicle routing problem with time windows: a case study

Science.gov (United States)

Latiffianti, E.; Siswanto, N.; Firmandani, R. A.

2018-04-01

This paper aims to implement an extension of VRP so called split delivery vehicle routing problem (SDVRP) with time windows in a case study involving pickups and deliveries of workers from several points of origin and several destinations. Each origin represents a bus stop and the destination represents either site or office location. An integer linear programming of the SDVRP problem is presented. The solution was generated using three stages of defining the starting points, assigning busses, and solving the SDVRP with time windows using an exact method. Although the overall computational time was relatively lengthy, the results indicated that the produced solution was better than the existing routing and scheduling that the firm used. The produced solution was also capable of reducing fuel cost by 9% that was obtained from shorter total distance travelled by the shuttle buses.

Multi-periodic nanostructures for photon control

DEFF Research Database (Denmark)

Kluge, Christian; Adam, Jost; Barié, Nicole

2014-01-01

We propose multi-periodic nanostructures yielded by superposition of multiple binary gratings for wide control over photon emission in thin-film devices. We present wavelength- and angle-resolved photoluminescence measurements of multi-periodically nanostructured organic light-emitting layers...

Multi-UAV Routing for Area Coverage and Remote Sensing with Minimum Time.

Science.gov (United States)

Avellar, Gustavo S C; Pereira, Guilherme A S; Pimenta, Luciano C A; Iscold, Paulo

2015-11-02

This paper presents a solution for the problem of minimum time coverage of ground areas using a group of unmanned air vehicles (UAVs) equipped with image sensors. The solution is divided into two parts: (i) the task modeling as a graph whose vertices are geographic coordinates determined in such a way that a single UAV would cover the area in minimum time; and (ii) the solution of a mixed integer linear programming problem, formulated according to the graph variables defined in the first part, to route the team of UAVs over the area. The main contribution of the proposed methodology, when compared with the traditional vehicle routing problem's (VRP) solutions, is the fact that our method solves some practical problems only encountered during the execution of the task with actual UAVs. In this line, one of the main contributions of the paper is that the number of UAVs used to cover the area is automatically selected by solving the optimization problem. The number of UAVs is influenced by the vehicles' maximum flight time and by the setup time, which is the time needed to prepare and launch a UAV. To illustrate the methodology, the paper presents experimental results obtained with two hand-launched, fixed-wing UAVs.

New heuristics for the fleet size and mix vehicle routing problem with time windows

NARCIS (Netherlands)

Dullaert, W.; Janssens, Gerrit K.; Sirensen, K.; Vernimmen, Bert

2002-01-01

In the Fleet Size and Mix Vehicle Routing Problem with Time Windows (FSMVRPTW) customers need to be serviced in their time windows at minimal costs by a heterogeneous fleet. In this paper new heuristics for the FSMVRPTW are developed. The performance of the heuristics is shown to be significantly

A branch-and-cut algorithm for the symmetric two-echelon capacitated vehicle routing problem

DEFF Research Database (Denmark)

Jepsen, Mads Kehlet; Spoorendonk, Simon; Røpke, Stefan

2013-01-01

This paper presents an exact method for solving the symmetric two-echelon capacitated vehicle routing problem, a transportation problem concerned with the distribution of goods from a depot to a set of customers through a set of satellite locations. The presented method is based on an edge flow...

Multi-Gateway-Based Energy Holes Avoidance Routing Protocol for WSN

Directory of Open Access Journals (Sweden)

Rohini Sharma

2016-04-01

Full Text Available In wireless sensor networks (WSNs, efficient energy conservation is required to prolong the lifetime of the network. In this work, we have given emphasis on balanced energy consumption and energy holes avoidance. This paper proposes a multi-gateway-based approach to reduce the transmission distance between the sender and the sink node. The area to be monitored is divided into regions and gateway nodes are deployed at optimal positions. We have designed a transmission scheme, in which sensors in the sink region communicate directly to the sink, sensors in the gateway region communicate directly to the gateway, and sensors in the cluster region transmit their data directly to their respective cluster head which transmits data to the gateway in its region. If the distance between a cluster head and the sink is less than the distance between the cluster head and the gateway node, the cluster head transmits data to the sink instead of the gateway node. We have compared the proposed protocol with Low-Energy Adaptive Clustering Hierarchy (LEACH, Gateway Based Energy Aware Multi-Hop Routing (M-GEAR, and Gateway Based Stable Election Protocol (GSEP protocols. The protocol performs better than other protocols in terms of throughput, stability period, lifetime, residual energy, and the packet transmitted to the sink.

Multi-Perspective Vehicle Detection and Tracking

DEFF Research Database (Denmark)

Dueholm, Jacob Velling; Kristoffersen, Miklas Strøm; Satzoda, Ravi K.

2016-01-01

this dataset is introduced along with its challenges and evaluation metrics. A vision-based multi-perspective dataset is presented, containing a full panoramic view from a moving platform driving on U.S. highways capturing 2704x1440 resolution images at 12 frames per second. The dataset serves multiple......The research community has shown significant improvements in both vision-based detection and tracking of vehicles, working towards a high level understanding of on-road maneuvers. Behaviors of surrounding vehicles in a highway environment is found as an interesting starting point, of why...... purposes to be used as traditional detection and tracking, together with tracking of vehicles across perspectives. Each of the four perspectives have been annotated, resulting in more than 4000 bounding boxes in order to evaluate and compare novel methods....

Multi-level Bayesian analyses for single- and multi-vehicle freeway crashes.

Science.gov (United States)

Yu, Rongjie; Abdel-Aty, Mohamed

2013-09-01

This study presents multi-level analyses for single- and multi-vehicle crashes on a mountainous freeway. Data from a 15-mile mountainous freeway section on I-70 were investigated. Both aggregate and disaggregate models for the two crash conditions were developed. Five years of crash data were used in the aggregate investigation, while the disaggregate models utilized one year of crash data along with real-time traffic and weather data. For the aggregate analyses, safety performance functions were developed for the purpose of revealing the contributing factors for each crash type. Two methodologies, a Bayesian bivariate Poisson-lognormal model and a Bayesian hierarchical Poisson model with correlated random effects, were estimated to simultaneously analyze the two crash conditions with consideration of possible correlations. Except for the factors related to geometric characteristics, two exposure parameters (annual average daily traffic and segment length) were included. Two different sets of significant explanatory and exposure variables were identified for the single-vehicle (SV) and multi-vehicle (MV) crashes. It was found that the Bayesian bivariate Poisson-lognormal model is superior to the Bayesian hierarchical Poisson model, the former with a substantially lower DIC and more significant variables. In addition to the aggregate analyses, microscopic real-time crash risk evaluation models were developed for the two crash conditions. Multi-level Bayesian logistic regression models were estimated with the random parameters accounting for seasonal variations, crash-unit-level diversity and segment-level random effects capturing unobserved heterogeneity caused by the geometric characteristics. The model results indicate that the effects of the selected variables on crash occurrence vary across seasons and crash units; and that geometric characteristic variables contribute to the segment variations: the more unobserved heterogeneity have been accounted, the better

Vehicle routing problem with time windows using natural inspired algorithms

Science.gov (United States)

Pratiwi, A. B.; Pratama, A.; Sa’diyah, I.; Suprajitno, H.

2018-03-01

Process of distribution of goods needs a strategy to make the total cost spent for operational activities minimized. But there are several constrains have to be satisfied which are the capacity of the vehicles and the service time of the customers. This Vehicle Routing Problem with Time Windows (VRPTW) gives complex constrains problem. This paper proposes natural inspired algorithms for dealing with constrains of VRPTW which involves Bat Algorithm and Cat Swarm Optimization. Bat Algorithm is being hybrid with Simulated Annealing, the worst solution of Bat Algorithm is replaced by the solution from Simulated Annealing. Algorithm which is based on behavior of cats, Cat Swarm Optimization, is improved using Crow Search Algorithm to make simplier and faster convergence. From the computational result, these algorithms give good performances in finding the minimized total distance. Higher number of population causes better computational performance. The improved Cat Swarm Optimization with Crow Search gives better performance than the hybridization of Bat Algorithm and Simulated Annealing in dealing with big data.

Link and route availability for Inter-working multi-hop wireless networks

CSIR Research Space (South Africa)

Salami, O

2009-09-01

Full Text Available pairs in inter-working multi-hop wireless networks can be evaluated based on the availability and reliability of radio links that form the communication path linking the nodes. This paper presents an analytical study of the link and route availability...

A Rich Vehicle Routing Problem with Multiple Trips and Driver Shifts

OpenAIRE

Arda, Yasemin; Crama, Yves; Kucukaydin, Hande; Talla Nobibon, Fabrice

2012-01-01

This study is concerned with a rich vehicle routing problem (RVRP) encountered at a Belgian transportation company in charge of servicing supermarkets and hypermarkets belonging to a franchise. The studied problem can be classified as a one-to-many-to-one pick-up and delivery problem, where there is a single depot from which all delivery customers are served and to which every pick-up demand must be carried back (Gutiérrez-Jarpa et al., 2010). The delivery and backhaul customers are considere...

An artificial bee colony algorithm for the capacitated vehicle routing problem

DEFF Research Database (Denmark)

Szeto, W.Y.; Wu, Yongzhong; Ho, Sin C.

2011-01-01

This paper introduces an artificial bee colony heuristic for solving the capacitated vehicle routing problem. The artificial bee colony heuristic is a swarm-based heuristic, which mimics the foraging behavior of a honey bee swarm. An enhanced version of the artificial bee colony heuristic is also...... proposed to improve the solution quality of the original version. The performance of the enhanced heuristic is evaluated on two sets of standard benchmark instances, and compared with the original artificial bee colony heuristic. The computational results show that the enhanced heuristic outperforms...

A Food Chain Algorithm for Capacitated Vehicle Routing Problem with Recycling in Reverse Logistics

Science.gov (United States)

Song, Qiang; Gao, Xuexia; Santos, Emmanuel T.

2015-12-01

This paper introduces the capacitated vehicle routing problem with recycling in reverse logistics, and designs a food chain algorithm for it. Some illustrative examples are selected to conduct simulation and comparison. Numerical results show that the performance of the food chain algorithm is better than the genetic algorithm, particle swarm optimization as well as quantum evolutionary algorithm.

Stochastic vehicle routing with recourse

DEFF Research Database (Denmark)

Gørtz, Inge Li; Nagarajan, Viswanath; Saket, Rishi

2012-01-01

instantiations, a recourse route is computed - but costs here become more expensive by a factor λ. We present an O(log2n ·log(nλ))-approximation algorithm for this stochastic routing problem, under arbitrary distributions. The main idea in this result is relating StochVRP to a special case of submodular...

Exact methods for time constrained routing and related scheduling problems

DEFF Research Database (Denmark)

Kohl, Niklas

1995-01-01

of customers. In the VRPTW customers must be serviced within a given time period - a so called time window. The objective can be to minimize operating costs (e.g. distance travelled), fixed costs (e.g. the number of vehicles needed) or a combination of these component costs. During the last decade optimization......This dissertation presents a number of optimization methods for the Vehicle Routing Problem with Time Windows (VRPTW). The VRPTW is a generalization of the well known capacity constrained Vehicle Routing Problem (VRP), where a fleet of vehicles based at a central depot must service a set...... of J?rnsten, Madsen and S?rensen (1986), which has been tested computationally by Halse (1992). Both methods decompose the problem into a series of time and capacity constrained shotest path problems. This yields a tight lower bound on the optimal objective, and the dual gap can often be closed...

Multi-Task Vehicle Detection with Region-of-Interest Voting.

Science.gov (United States)

Chu, Wenqing; Liu, Yao; Shen, Chen; Cai, Deng; Hua, Xian-Sheng

2017-10-12

Vehicle detection is a challenging problem in autonomous driving systems, due to its large structural and appearance variations. In this paper, we propose a novel vehicle detection scheme based on multi-task deep convolutional neural networks (CNN) and region-of-interest (RoI) voting. In the design of CNN architecture, we enrich the supervised information with subcategory, region overlap, bounding-box regression and category of each training RoI as a multi-task learning framework. This design allows the CNN model to share visual knowledge among different vehicle attributes simultaneously, thus detection robustness can be effectively improved. In addition, most existing methods consider each RoI independently, ignoring the clues from its neighboring RoIs. In our approach, we utilize the CNN model to predict the offset direction of each RoI boundary towards the corresponding ground truth. Then each RoI can vote those suitable adjacent bounding boxes which are consistent with this additional information. The voting results are combined with the score of each RoI itself to find a more accurate location from a large number of candidates. Experimental results on the real-world computer vision benchmarks KITTI and the PASCAL2007 vehicle dataset show that our approach achieves superior performance in vehicle detection compared with other existing published works.

A hybrid metaheuristic for the time-dependent vehicle routing problem with hard time windows

Directory of Open Access Journals (Sweden)

N. Rincon-Garcia

2017-01-01

Full Text Available This article paper presents a hybrid metaheuristic algorithm to solve the time-dependent vehicle routing problem with hard time windows. Time-dependent travel times are influenced by different congestion levels experienced throughout the day. Vehicle scheduling without consideration of congestion might lead to underestimation of travel times and consequently missed deliveries. The algorithm presented in this paper makes use of Large Neighbourhood Search approaches and Variable Neighbourhood Search techniques to guide the search. A first stage is specifically designed to reduce the number of vehicles required in a search space by the reduction of penalties generated by time-window violations with Large Neighbourhood Search procedures. A second stage minimises the travel distance and travel time in an ‘always feasible’ search space. Comparison of results with available test instances shows that the proposed algorithm is capable of obtaining a reduction in the number of vehicles (4.15%, travel distance (10.88% and travel time (12.00% compared to previous implementations in reasonable time.

An Ant Colony Optimization and Hybrid Metaheuristics Algorithm to Solve the Split Delivery Vehicle Routing Problem

Science.gov (United States)

2015-01-01

solution approach that combines heuristic search and integer programming. Boudia et al. (2007) solved an SDVRP instance using a memetic algorithm with...Boudia, M., Prins, C., Reghioui, M., 2007. An effective memetic algorithm with population management for the split delivery vehicle routing problem

Multi-agents Based Modelling for Distribution Network Operation with Electric Vehicle Integration

DEFF Research Database (Denmark)

Hu, Junjie; Morais, Hugo; Zong, Yi

2014-01-01

Electric vehicles (EV) can become integral part of a smart grid because instead of just consuming power they are capable of providing valuable services to power systems. To integrate EVs smoothly into the power systems, a multi-agents system (MAS) with hierarchical organization structure...... and its role is to manage the distribution network safely by avoiding grid congestions and using congestion prices to coordinate the energy schedule of VPPs. VPP agents belong to the middle level and their roles are to manage the charge periods of the EVs. EV agents sit in the bottom level...

Transport spatial model for the definition of green routes for city logistics centers

Energy Technology Data Exchange (ETDEWEB)

Pamučar, Dragan, E-mail: dpamucar@gmail.com [University of Defence in Belgrade, Department of Logistics, Pavla Jurisica Sturma 33, 11000 Belgrade (Serbia); Gigović, Ljubomir, E-mail: gigoviclj@gmail.com [University of Defence in Belgrade, Department of Mathematics, Pavla Jurisica Sturma 33, 11000 Belgrade (Serbia); Ćirović, Goran, E-mail: cirovic@sezampro.rs [College of Civil Engineering and Geodesy, The Belgrade University, Hajduk Stankova 2, 11000 Belgrade (Serbia); Regodić, Miodrag, E-mail: mregodic62@gmail.com [University of Defence in Belgrade, Department of Mathematics, Pavla Jurisica Sturma 33, 11000 Belgrade (Serbia)

2016-01-15

This paper presents a transport spatial decision support model (TSDSM) for carrying out the optimization of green routes for city logistics centers. The TSDSM model is based on the integration of the multi-criteria method of Weighted Linear Combination (WLC) and the modified Dijkstra algorithm within a geographic information system (GIS). The GIS is used for processing spatial data. The proposed model makes it possible to plan routes for green vehicles and maximize the positive effects on the environment, which can be seen in the reduction of harmful gas emissions and an increase in the air quality in highly populated areas. The scheduling of delivery vehicles is given as a problem of optimization in terms of the parameters of: the environment, health, use of space and logistics operating costs. Each of these input parameters was thoroughly examined and broken down in the GIS into criteria which further describe them. The model presented here takes into account the fact that logistics operators have a limited number of environmentally friendly (green) vehicles available. The TSDSM was tested on a network of roads with 127 links for the delivery of goods from the city logistics center to the user. The model supports any number of available environmentally friendly or environmentally unfriendly vehicles consistent with the size of the network and the transportation requirements. - Highlights: • Model for routing light delivery vehicles in urban areas. • Optimization of green routes for city logistics centers. • The proposed model maximizes the positive effects on the environment. • The model was tested on a real network.

Transport spatial model for the definition of green routes for city logistics centers

International Nuclear Information System (INIS)

Pamučar, Dragan; Gigović, Ljubomir; Ćirović, Goran; Regodić, Miodrag

2016-01-01

This paper presents a transport spatial decision support model (TSDSM) for carrying out the optimization of green routes for city logistics centers. The TSDSM model is based on the integration of the multi-criteria method of Weighted Linear Combination (WLC) and the modified Dijkstra algorithm within a geographic information system (GIS). The GIS is used for processing spatial data. The proposed model makes it possible to plan routes for green vehicles and maximize the positive effects on the environment, which can be seen in the reduction of harmful gas emissions and an increase in the air quality in highly populated areas. The scheduling of delivery vehicles is given as a problem of optimization in terms of the parameters of: the environment, health, use of space and logistics operating costs. Each of these input parameters was thoroughly examined and broken down in the GIS into criteria which further describe them. The model presented here takes into account the fact that logistics operators have a limited number of environmentally friendly (green) vehicles available. The TSDSM was tested on a network of roads with 127 links for the delivery of goods from the city logistics center to the user. The model supports any number of available environmentally friendly or environmentally unfriendly vehicles consistent with the size of the network and the transportation requirements. - Highlights: • Model for routing light delivery vehicles in urban areas. • Optimization of green routes for city logistics centers. • The proposed model maximizes the positive effects on the environment. • The model was tested on a real network.

Optimal routing of IP packets to multi-homed servers

International Nuclear Information System (INIS)

Swartz, K.L.

1992-08-01

Multi-homing, or direct attachment to multiple networks, offers both performance and availability benefits for important servers on busy networks. Exploiting these benefits to their fullest requires a modicum of routing knowledge in the clients. Careful policy control must also be reflected in the routing used within the network to make best use of specialized and often scarce resources. While relatively straightforward in theory, this problem becomes much more difficult to solve in a real network containing often intractable implementations from a variety of vendors. This paper presents an analysis of the problem and proposes a useful solution for a typical campus network. Application of this solution at the Stanford Linear Accelerator Center is studied and the problems and pitfalls encountered are discussed, as are the workarounds used to make the system work in the real world

An Extension of the Lin-Kernighan-Helsgaun TSP Solver for Constrained Traveling Salesman and Vehicle Routing Problems

DEFF Research Database (Denmark)

Helsgaun, Keld

This report describes the implementation of an extension of the Lin-Kernighan-Helsgaun TSP solver for solving constrained traveling salesman and vehicle routing problems. The extension, which is called LKH-3, is able to solve a variety of well-known problems, including the sequential ordering...... problem (SOP), the traveling repairman problem (TRP), variants of the multiple travel-ing salesman problem (mTSP), as well as vehicle routing problems (VRPs) with capacity, time windows, pickup-and-delivery and distance constraints. The implementation of LKH-3 builds on the idea of transforming...... the problems into standard symmetric traveling salesman problems and handling constraints by means of penalty functions. Extensive testing on benchmark instances from the literature has shown that LKH-3 is effective. Best known solutions are often obtained, and in some cases, new best solutions are found...

A new formulation for the 2-echelon capacitated vehicle routing problem

DEFF Research Database (Denmark)

Jepsen, Mads Kehlet; Røpke, Stefan; Spoorendonk, Simon

The 2-echelon capacitated vehicle routing problem (2E-CVRP) is a transportation and distribution problem where goods are transported from a depot to a set of customers possible via optional satellite facilities. The 2E-CVRP is relevant in city-logistic applications where legal restrictions make...... it infeasible to use large trucks within the center of large cities. We propose a new mathematical formulation for the 2E-CVRP with much fewer variables than the previously proposed but with several constraint sets of exponential size. The strength of the model is implied by the facts that many cutting planes...

A well-scalable metaheuristic for the fleet size and mix vehicle routing problem with time windows

NARCIS (Netherlands)

Bräysy, Olli; Porkka, Pasi P.; Dullaert, Wout; Repoussis, Panagiotis P.; Tarantilis, Christos D.

This paper presents an efficient and well-scalable metaheuristic for fleet size and mix vehicle routing with time windows. The suggested solution method combines the strengths of well-known threshold accepting and guided local search metaheuristics to guide a set of four local search heuristics. The

A simultaneous facility location and vehicle routing problem arising in health care logistics in the Netherlands

NARCIS (Netherlands)

Veenstra, Marjolein; Roodbergen, Kees Jan; Coelho, Leandro C.; Zhu, Stuart X.

2018-01-01

This paper introduces a simultaneous facility location and vehicle routing problem that arises in health care logistics in the Netherlands. In this problem, the delivery of medication from a local pharmacy can occur via lockers, from where patients that are within the coverage distance of a locker

A New Improved Quantum Evolution Algorithm with Local Search Procedure for Capacitated Vehicle Routing Problem

Directory of Open Access Journals (Sweden)

Ligang Cui

2013-01-01

Full Text Available The capacitated vehicle routing problem (CVRP is the most classical vehicle routing problem (VRP; many solution techniques are proposed to find its better answer. In this paper, a new improved quantum evolution algorithm (IQEA with a mixed local search procedure is proposed for solving CVRPs. First, an IQEA with a double chain quantum chromosome, new quantum rotation schemes, and self-adaptive quantum Not gate is constructed to initialize and generate feasible solutions. Then, to further strengthen IQEA's searching ability, three local search procedures 1-1 exchange, 1-0 exchange, and 2-OPT, are adopted. Experiments on a small case have been conducted to analyze the sensitivity of main parameters and compare the performances of the IQEA with different local search strategies. Together with results from the testing of CVRP benchmarks, the superiorities of the proposed algorithm over the PSO, SR-1, and SR-2 have been demonstrated. At last, a profound analysis of the experimental results is presented and some suggestions on future researches are given.

Feasible Initial Population with Genetic Diversity for a Population-Based Algorithm Applied to the Vehicle Routing Problem with Time Windows

Directory of Open Access Journals (Sweden)

Marco Antonio Cruz-Chávez

2016-01-01

Full Text Available A stochastic algorithm for obtaining feasible initial populations to the Vehicle Routing Problem with Time Windows is presented. The theoretical formulation for the Vehicle Routing Problem with Time Windows is explained. The proposed method is primarily divided into a clustering algorithm and a two-phase algorithm. The first step is the application of a modified k-means clustering algorithm which is proposed in this paper. The two-phase algorithm evaluates a partial solution to transform it into a feasible individual. The two-phase algorithm consists of a hybridization of four kinds of insertions which interact randomly to obtain feasible individuals. It has been proven that different kinds of insertions impact the diversity among individuals in initial populations, which is crucial for population-based algorithm behavior. A modification to the Hamming distance method is applied to the populations generated for the Vehicle Routing Problem with Time Windows to evaluate their diversity. Experimental tests were performed based on the Solomon benchmarking. Experimental results show that the proposed method facilitates generation of highly diverse populations, which vary according to the type and distribution of the instances.

Coordinated Platoon Routing in a Metropolitan Network

Energy Technology Data Exchange (ETDEWEB)

Larson, Jeffrey; Munson, Todd; Sokolov, Vadim

2016-10-10

Platooning vehicles—connected and automated vehicles traveling with small intervehicle distances—use less fuel because of reduced aerodynamic drag. Given a network de- fined by vertex and edge sets and a set of vehicles with origin/destination nodes/times, we model and solve the combinatorial optimization problem of coordinated routing of vehicles in a manner that routes them to their destination on time while using the least amount of fuel. Common approaches decompose the platoon coordination and vehicle routing into separate problems. Our model addresses both problems simultaneously to obtain the best solution. We use modern modeling techniques and constraints implied from analyzing the platoon routing problem to address larger numbers of vehicles and larger networks than previously considered. While the numerical method used is unable to certify optimality for candidate solutions to all networks and parameters considered, we obtain excellent solutions in approximately one minute for much larger networks and vehicle sets than previously considered in the literature.

Cost Optimisation in Freight Distribution with Cross-Docking: N-Echelon Location Routing Problem

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Jesus Gonzalez-Feliu

2012-03-01

Full Text Available Freight transportation constitutes one of the main activities that influence the economy and society, as it assures a vital link between suppliers and customers and represents a major source of employment. Multi-echelon distribution is one of the most common strategies adopted by the transportation companies in an aim of cost reduction. Although vehicle routing problems are very common in operational research, they are essentially related to single-echelon cases. This paper presents the main concepts of multi-echelon distribution with cross-docks and a unified notation for the N-echelon location routing problem. A literature review is also presented, in order to list the main problems and methods that can be helpful for scientists and transportation practitioners.

High-Fidelity Computational Aerodynamics of Multi-Rotor Unmanned Aerial Vehicles

Science.gov (United States)

Ventura Diaz, Patricia; Yoon, Seokkwan

2018-01-01

High-fidelity Computational Fluid Dynamics (CFD) simulations have been carried out for several multi-rotor Unmanned Aerial Vehicles (UAVs). Three vehicles have been studied: the classic quadcopter DJI Phantom 3, an unconventional quadcopter specialized for forward flight, the SUI Endurance, and an innovative concept for Urban Air Mobility (UAM), the Elytron 4S UAV. The three-dimensional unsteady Navier-Stokes equations are solved on overset grids using high-order accurate schemes, dual-time stepping, and a hybrid turbulence model. The DJI Phantom 3 is simulated with different rotors and with both a simplified airframe and the real airframe including landing gear and a camera. The effects of weather are studied for the DJI Phantom 3 quadcopter in hover. The SUI En- durance original design is compared in forward flight to a new configuration conceived by the authors, the hybrid configuration, which gives a large improvement in forward thrust. The Elytron 4S UAV is simulated in helicopter mode and in airplane mode. Understanding the complex flows in multi-rotor vehicles will help design quieter, safer, and more efficient future drones and UAM vehicles.

An Evolutionary Mobility Aware Multi-Objective Hybrid Routing Algorithm for Heterogeneous Wireless Sensor Networks

DEFF Research Database (Denmark)

Kulkarni, Nandkumar P.; Prasad, Neeli R.; Prasad, Ramjee

deliberation. To tackle these two problems, Mobile Wireless Sensor Networks (MWSNs) is a better choice. In MWSN, Sensor nodes move freely to a target area without the need for any special infrastructure. Due to mobility, the routing process in MWSN has become more complicated as connections in the network can...... such as Average Energy consumption, Control Overhead, Reaction Time, LQI, and HOP Count. The authors study the influence of energy heterogeneity and mobility of sensor nodes on the performance of EMRP. The Performance of EMRP compared with Simple Hybrid Routing Protocol (SHRP) and Dynamic Multi-Objective Routing...

A Routing Strategy for Non-Cooperation Wireless Multi-Hop Ad Hoc Networks

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Dung T. Tran

2012-01-01

Full Text Available Choosing routes such that the network lifetime is maximized in a wireless network with limited energy resources is a major routing problem in wireless multi-hop ad hoc networks. In this paper, we study the problem where participants are rationally selfish and non-cooperative. By selfish we designate the users who are ready to tamper with their source-routing (senders could choose intermediate nodes in the routing paths or next hop selection strategies in order to increase the total number of packets transmitted, but do not try to harm or drop packets of the other nodes. The problem therefore amounts to a non-cooperative game. In the works [2,6,19,23], the authors show that the game admits Nash equilibria [1]. Along this line, we first show that if the cost function is linear, this game has pure-strategy equilibrium flow even though participants have different demands. However, finding a Nash equilibrium for a normal game is computationally hard [9]. In this work, inspired by mixed-strategy equilibrium, we propose a simple local routing algorithm called MIxed Path Routing protocol (MiPR. Using analysis and simulations, we show that MiPR drives the system to an equilibrium state where selfish participants do not have incentive to deviate. Moreover, MiPR significantly improves the network lifetime as compared to original routing protocols.

Biased random key genetic algorithm with insertion and gender selection for capacitated vehicle routing problem with time windows

Science.gov (United States)

Rochman, Auliya Noor; Prasetyo, Hari; Nugroho, Munajat Tri

2017-06-01

Vehicle Routing Problem (VRP) often occurs when the manufacturers need to distribute their product to some customers/outlets. The distribution process is typically restricted by the capacity of the vehicle and the working hours at the distributor. This type of VRP is also known as Capacitated Vehicle Routing Problem with Time Windows (CVRPTW). A Biased Random Key Genetic Algorithm (BRKGA) was designed and coded in MATLAB to solve the CVRPTW case of soft drink distribution. The standard BRKGA was then modified by applying chromosome insertion into the initial population and defining chromosome gender for parent undergoing crossover operation. The performance of the established algorithms was then compared to a heuristic procedure for solving a soft drink distribution. Some findings are revealed (1) the total distribution cost of BRKGA with insertion (BRKGA-I) results in a cost saving of 39% compared to the total cost of heuristic method, (2) BRKGA with the gender selection (BRKGA-GS) could further improve the performance of the heuristic method. However, the BRKGA-GS tends to yield worse results compared to that obtained from the standard BRKGA.

Distributed Multi-Commodity Network Flow Algorithm for Energy Optimal Routing in Wireless Sensor Networks.

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J. Trdlicka

2010-12-01

Full Text Available This work proposes a distributed algorithm for energy optimal routing in a wireless sensor network. The routing problem is described as a mathematical problem by the minimum-cost multi-commodity network flow problem. Due to the separability of the problem, we use the duality theorem to derive the distributed algorithm. The algorithm computes the energy optimal routing in the network without any central node or knowledge of the whole network structure. Each node only needs to know the flow which is supposed to send or receive and the costs and capacities of the neighboring links. An evaluation of the presented algorithm on benchmarks for the energy optimal data flow routing in sensor networks with up to 100 nodes is presented.

The integrated model for solving the single-period deterministic inventory routing problem

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Rahim, Mohd Kamarul Irwan Abdul; Abidin, Rahimi; Iteng, Rosman; Lamsali, Hendrik

2016-08-01

This paper discusses the problem of efficiently managing inventory and routing problems in a two-level supply chain system. Vendor Managed Inventory (VMI) policy is an integrating decisions between a supplier and his customers. We assumed that the demand at each customer is stationary and the warehouse is implementing a VMI. The objective of this paper is to minimize the inventory and the transportation costs of the customers for a two-level supply chain. The problem is to determine the delivery quantities, delivery times and routes to the customers for the single-period deterministic inventory routing problem (SP-DIRP) system. As a result, a linear mixed-integer program is developed for the solutions of the SP-DIRP problem.

A Two-Phase Heuristic Algorithm for the Common Frequency Routing Problem with Vehicle Type Choice in the Milk Run

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Yu Lin

2015-01-01

Full Text Available High frequency and small lot size are characteristics of milk runs and are often used to implement the just-in-time (JIT strategy in logistical systems. The common frequency problem, which simultaneously involves planning of the route and frequency, has been extensively researched in milk run systems. In addition, vehicle type choice in the milk run system also has a significant influence on the operating cost. Therefore, in this paper, we simultaneously consider vehicle routing planning, frequency planning, and vehicle type choice in order to optimize the sum of the cost of transportation, inventory, and dispatch. To this end, we develop a mathematical model to describe the common frequency problem with vehicle type choice. Since the problem is NP hard, we develop a two-phase heuristic algorithm to solve the model. More specifically, an initial satisfactory solution is first generated through a greedy heuristic algorithm to maximize the ratio of the superior arc frequency to the inferior arc frequency. Following this, a tabu search (TS with limited search scope is used to improve the initial satisfactory solution. Numerical examples with different sizes establish the efficacy of our model and our proposed algorithm.

Solving a bi-objective mathematical programming model for bloodmobiles location routing problem

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Masoud Rabbani

2017-01-01

Full Text Available Perishability of platelets, uncertainty of donors’ arrival and conflicting views in platelet supply chain have made platelet supply chain planning a problematic issue. In this paper, mobile blood collection system for platelet production is investigated. Two mathematical models are presented to cover the bloodmobile collection planning problem. The first model is a multi-objective fuzzy mathematical programming in which the bloodmobiles locations are considered with the aim of maximizing potential amount of blood collection and minimizing the operational cost. The second model is a vehicle routing problem with time windows which studies the shuttles routing problem. To tackle the first model, it is reformulated as a crisp multi objective linear programming model and then solved through a fuzzy multi objective programming approach. Several sensitivity analysis are conducted on important parameters to demonstrate the applicability of the proposed model. The proposed model is then solved by using a tailored Simulated Annealing (SA algorithm. The numerical results demonstrate promising efficiency of the proposed solution method.

Multi-Disciplinary Design Optimization of Hypersonic Air-Breathing Vehicle

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Wu, Peng; Tang, Zhili; Sheng, Jianda

2016-06-01

A 2D hypersonic vehicle shape with an idealized scramjet is designed at a cruise regime: Mach number (Ma) = 8.0, Angle of attack (AOA) = 0 deg and altitude (H) = 30kms. Then a multi-objective design optimization of the 2D vehicle is carried out by using a Pareto Non-dominated Sorting Genetic Algorithm II (NSGA-II). In the optimization process, the flow around the air-breathing vehicle is simulated by inviscid Euler equations using FLUENT software and the combustion in the combustor is modeled by a methodology based on the well known combination effects of area-varying pipe flow and heat transfer pipe flow. Optimization results reveal tradeoffs among total pressure recovery coefficient of forebody, lift to drag ratio of vehicle, specific impulse of scramjet engine and the maximum temperature on the surface of vehicle.

MULTI-FACTOR ANALYSIS FOR SELECTING LUNAR EXPLORATION SOFT LANDING AREA AND THE BEST CRUISE ROUTE

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N. Mou

2018-04-01

Full Text Available Selecting the right soft landing area and planning a reasonable cruise route are the basic tasks of lunar exploration. In this paper, the Von Karman crater in the Antarctic Aitken basin on the back of the moon is used as the study area, and multi-factor analysis is used to evaluate the landing area and cruise route of lunar exploration. The evaluation system mainly includes the factors such as the density of craters, the impact area of craters, the formation of the whole area and the formation of some areas, such as the vertical structure, rock properties and the content of (FeO + TiO2, which can reflect the significance of scientific exploration factor. And the evaluation of scientific exploration is carried out on the basis of safety and feasibility. On the basis of multi-factor superposition analysis, three landing zones A, B and C are selected, and the appropriate cruising route is analyzed through scientific research factors. This study provides a scientific basis for the lunar probe landing and cruise route planning, and it provides technical support for the subsequent lunar exploration.

Multi-Factor Analysis for Selecting Lunar Exploration Soft Landing Area and the best Cruise Route

Science.gov (United States)

Mou, N.; Li, J.; Meng, Z.; Zhang, L.; Liu, W.

2018-04-01

Selecting the right soft landing area and planning a reasonable cruise route are the basic tasks of lunar exploration. In this paper, the Von Karman crater in the Antarctic Aitken basin on the back of the moon is used as the study area, and multi-factor analysis is used to evaluate the landing area and cruise route of lunar exploration. The evaluation system mainly includes the factors such as the density of craters, the impact area of craters, the formation of the whole area and the formation of some areas, such as the vertical structure, rock properties and the content of (FeO + TiO2), which can reflect the significance of scientific exploration factor. And the evaluation of scientific exploration is carried out on the basis of safety and feasibility. On the basis of multi-factor superposition analysis, three landing zones A, B and C are selected, and the appropriate cruising route is analyzed through scientific research factors. This study provides a scientific basis for the lunar probe landing and cruise route planning, and it provides technical support for the subsequent lunar exploration.

Developing an eco-routing application.

Science.gov (United States)

2014-01-01

The study develops eco-routing algorithms and investigates and quantifies the system-wide impacts of implementing an eco-routing system. Two eco-routing algorithms are developed: one based on vehicle sub-populations (ECO-Subpopulation Feedback Assign...

Multi-criteria, personalized route planning using quantifier-guided ordered weighted averaging operators

Science.gov (United States)

Nadi, S.; Delavar, M. R.

2011-06-01

This paper presents a generic model for using different decision strategies in multi-criteria, personalized route planning. Some researchers have considered user preferences in navigation systems. However, these prior studies typically employed a high tradeoff decision strategy, which used a weighted linear aggregation rule, and neglected other decision strategies. The proposed model integrates a pairwise comparison method and quantifier-guided ordered weighted averaging (OWA) aggregation operators to form a personalized route planning method that incorporates different decision strategies. The model can be used to calculate the impedance of each link regarding user preferences in terms of the route criteria, criteria importance and the selected decision strategy. Regarding the decision strategy, the calculated impedance lies between aggregations that use a logical "and" (which requires all the criteria to be satisfied) and a logical "or" (which requires at least one criterion to be satisfied). The calculated impedance also includes taking the average of the criteria scores. The model results in multiple alternative routes, which apply different decision strategies and provide users with the flexibility to select one of them en-route based on the real world situation. The model also defines the robust personalized route under different decision strategies. The influence of different decision strategies on the results are investigated in an illustrative example. This model is implemented in a web-based geographical information system (GIS) for Isfahan in Iran and verified in a tourist routing scenario. The results demonstrated, in real world situations, the validity of the route planning carried out in the model.

Penerapan Konsep Vehicle Routing Problem dalam Kasus Pengangkutan Sampah di Perkotaan

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Harun Al Rasyid Lubis

2016-12-01

Full Text Available Cities in developing countries still operate a traditional waste transport and handling where rubbish were collected at regular intervals by specialized trucks from curb-side collection or transfer point prior to transport them to a final dump site. The problem are worsening as some cities experience exhausted waste collection services because the system is inadequately managed, fiscal capacity to invest in adequate vehicle fleets is lacking and also due to uncontrolled dumpsites location. In this paper problem of waste collection and handling is formulated based on Capacitated Vehicle Routing Problem Time Window Multiple Depo Intermediete Facility (CVRPTWMDIF. Each vehicle was assigned to visit several intermediate transfer points, until the truck loading or volume capacity reached then waste are transported to final landfill or dump site. Finally all trucks will return to a depot at the end of daily operation. Initially the solution of CVRPTWMDIF problem was tested on a simple hypothetical waste handling before being implemented into a real case problem. Solutions found using CVRPTWMDIF compared with the practice of waste transport and handling in the city of Bandung. Based on a common hours of operation and the same number of transport fleets, it was found that CVRPTWMDIF can reduce the volume of waste that is not transported by almost half by the end of the daily operations.

Computational results with a branch and cut code for the capacitated vehicle routing problem

Energy Technology Data Exchange (ETDEWEB)

Augerat, P.; Naddef, D. [Institut National Polytechnique, 38 - Grenoble (France); Belenguer, J.M.; Benavent, E.; Corberan, A. [Valencia Univ. (Spain); Rinaldi, G. [Consiglio Nazionale delle Ricerche, Rome (Italy)

1995-09-01

The Capacitated Vehicle Routing Problem (CVRP) we consider in this paper consists in the optimization of the distribution of goods from a single depot to a given set of customers with known demand using a given number of vehicles of fixed capacity. There are many practical routing applications in the public sector such as school bus routing, pick up and mail delivery, and in the private sector such as the dispatching of delivery trucks. We present a Branch and Cut algorithm to solve the CVRP which is based in the partial polyhedral description of the corresponding polytope. The valid inequalities used in our method can ne found in Cornuejols and Harche (1993), Harche and Rinaldi (1991) and in Augerat and Pochet (1995). We concentrated mainly on the design of separation procedures for several classes of valid inequalities. The capacity constraints (generalized sub-tour eliminations inequalities) happen to play a crucial role in the development of a cutting plane algorithm for the CVRP. A large number of separation heuristics have been implemented and compared for these inequalities. There has been also implemented heuristic separation algorithms for other classes of valid inequalities that also lead to significant improvements: comb and extended comb inequalities, generalized capacity inequalities and hypo-tour inequalities. The resulting cutting plane algorithm has been applied to a set of instances taken from the literature and the lower bounds obtained are better than the ones previously known. Some branching strategies have been implemented to develop a Branch an Cut algorithm that has been able to solve large CVRP instances, some of them which had never been solved before. (authors). 32 refs., 3 figs., 10 tabs.

Improved Fractal Space Filling Curves Hybrid Optimization Algorithm for Vehicle Routing Problem.

Science.gov (United States)

Yue, Yi-xiang; Zhang, Tong; Yue, Qun-xing

2015-01-01

Vehicle Routing Problem (VRP) is one of the key issues in optimization of modern logistics system. In this paper, a modified VRP model with hard time window is established and a Hybrid Optimization Algorithm (HOA) based on Fractal Space Filling Curves (SFC) method and Genetic Algorithm (GA) is introduced. By incorporating the proposed algorithm, SFC method can find an initial and feasible solution very fast; GA is used to improve the initial solution. Thereafter, experimental software was developed and a large number of experimental computations from Solomon's benchmark have been studied. The experimental results demonstrate the feasibility and effectiveness of the HOA.

Wheeled mobility device transportation safety in fixed route and demand-responsive public transit vehicles within the United States.

Science.gov (United States)

Frost, Karen L; van Roosmalen, Linda; Bertocci, Gina; Cross, Douglas J

2012-01-01

An overview of the current status of wheelchair transportation safety in fixed route and demand-responsive, non-rail, public transportation vehicles within the US is presented. A description of each mode of transportation is provided, followed by a discussion of the primary issues affecting safety, accessibility, and usability. Technologies such as lifts, ramps, securement systems, and occupant restraint systems, along with regulations and voluntary industry standards have been implemented with the intent of improving safety and accessibility for individuals who travel while seated in their wheeled mobility device (e.g., wheelchair or scooter). However, across both fixed route and demand-responsive transit systems a myriad of factors such as nonuse and misuse of safety systems, oversized wheeled mobility devices, vehicle space constraints, and inadequate vehicle operator training may place wheeled mobility device (WhMD) users at risk of injury even under non-impact driving conditions. Since WhMD-related incidents also often occur during the boarding and alighting process, the frequency of these events, along with factors associated with these events are described for each transit mode. Recommendations for improving WhMD transportation are discussed given the current state of

An Efficient Two-Objective Hybrid Local Search Algorithm for Solving the Fuel Consumption Vehicle Routing Problem

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Weizhen Rao

2016-01-01

Full Text Available The classical model of vehicle routing problem (VRP generally minimizes either the total vehicle travelling distance or the total number of dispatched vehicles. Due to the increased importance of environmental sustainability, one variant of VRPs that minimizes the total vehicle fuel consumption has gained much attention. The resulting fuel consumption VRP (FCVRP becomes increasingly important yet difficult. We present a mixed integer programming model for the FCVRP, and fuel consumption is measured through the degree of road gradient. Complexity analysis of FCVRP is presented through analogy with the capacitated VRP. To tackle the FCVRP’s computational intractability, we propose an efficient two-objective hybrid local search algorithm (TOHLS. TOHLS is based on a hybrid local search algorithm (HLS that is also used to solve FCVRP. Based on the Golden CVRP benchmarks, 60 FCVRP instances are generated and tested. Finally, the computational results show that the proposed TOHLS significantly outperforms the HLS.

A Column Generation Approach to the Capacitated Vehicle Routing Problem with Stochastic Demands

DEFF Research Database (Denmark)

Christiansen, Christian Holk; Lysgaard, Jens

. The CVRPSD can be formulated as a Set Partitioning Problem. We show that, under the above assumptions on demands, the associated column generation subproblem can be solved using a dynamic programming scheme which is similar to that used in the case of deterministic demands. To evaluate the potential of our......In this article we introduce a new exact solution approach to the Capacitated Vehicle Routing Problem with Stochastic Demands (CVRPSD). In particular, we consider the case where all customer demands are distributed independently and where each customer's demand follows a Poisson distribution...

Multi-objective optimisation with stochastic discrete-event simulation in retail banking: a case study

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E Scholtz

2012-12-01

Full Text Available The cash management of an autoteller machine (ATM is a multi-objective optimisation problem which aims to maximise the service level provided to customers at minimum cost. This paper focus on improved cash management in a section of the South African retail banking industry, for which a decision support system (DSS was developed. This DSS integrates four Operations Research (OR methods: the vehicle routing problem (VRP, the continuous review policy for inventory management, the knapsack problem and stochastic, discrete-event simulation. The DSS was applied to an ATM network in the Eastern Cape, South Africa, to investigate 90 different scenarios. Results show that the application of a formal vehicle routing method consistently yields higher service levels at lower cost when compared to two other routing approaches, in conjunction with selected ATM reorder levels and a knapsack-based notes dispensing algorithm. It is concluded that the use of vehicle routing methods is especially beneficial when the bank has substantial control over transportation cost.

A Genetic Algorithm on Inventory Routing Problem

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Nevin Aydın

2014-03-01

Full Text Available Inventory routing problem can be defined as forming the routes to serve to the retailers from the manufacturer, deciding on the quantity of the shipment to the retailers and deciding on the timing of the replenishments. The difference of inventory routing problems from vehicle routing problems is the consideration of the inventory positions of retailers and supplier, and making the decision accordingly. Inventory routing problems are complex in nature and they can be solved either theoretically or using a heuristics method. Metaheuristics is an emerging class of heuristics that can be applied to combinatorial optimization problems. In this paper, we provide the relationship between vendor-managed inventory and inventory routing problem. The proposed genetic for solving vehicle routing problem is described in detail.

A case study of heterogeneous fleet vehicle routing problem: Touristic distribution application in Alanya

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Kenan Karagül

2014-07-01

Full Text Available In this study, Fleet Size and Mix Vehicle Routing Problem is considered in order to optimize the distribution of the tourists who have traveled between the airport and the hotels in the shortest distance by using the minimum cost. The initial solution space for the related methods are formed as a combination of Savings algorithm, Sweep algorithm and random permutation alignment. Then, two well-known solution methods named as Standard Genetic Algorithms and random search algorithms are used for changing the initial solutions. Computational power of the machine and heuristic algorithms are used instead of human experience and human intuition in order to solve the distribution problem of tourists coming to hotels in Alanya region from Antalya airport. For this case study, daily data of tourist distributions performed by an agency operating in Alanya region are considered. These distributions are then modeled as Vehicle Routing Problem to calculate the solutions for various applications. From the comparisons with the decision of a human expert, it is seen that the proposed methods produce better solutions with respect to human experience and insight. Random search method produces a solution more favorable in terms of time. As a conclusion, it is seen that, owing to the distribution plans offered by the obtained solutions, the agencies may reduce the costs by achieving savings up to 35%.

Vehicle Routing Problem with Time Windows and Simultaneous Delivery and Pick-Up Service Based on MCPSO

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Xiaobing Gan

2012-01-01

Full Text Available This paper considers two additional factors of the widely researched vehicle routing problem with time windows (VRPTW. The two factors, which are very common characteristics in realworld, are uncertain number of vehicles and simultaneous delivery and pick-up service. Using minimization of the total transport costs as the objective of the extension VRPTW, a mathematic model is constructed. To solve the problem, an efficient multiswarm cooperative particle swarm optimization (MCPSO algorithm is applied. And a new encoding method is proposed for the extension VRPTW. Finally, comparing with genetic algorithm (GA and particle swarm optimization (PSO algorithm, the MCPSO algorithm performs best for solving this problem.

Intelligent routing protocol for ad hoc wireless network

Science.gov (United States)

Peng, Chaorong; Chen, Chang Wen

2006-05-01

A novel routing scheme for mobile ad hoc networks (MANETs), which combines hybrid and multi-inter-routing path properties with a distributed topology discovery route mechanism using control agents is proposed in this paper. In recent years, a variety of hybrid routing protocols for Mobile Ad hoc wireless networks (MANETs) have been developed. Which is proactively maintains routing information for a local neighborhood, while reactively acquiring routes to destinations beyond the global. The hybrid protocol reduces routing discovery latency and the end-to-end delay by providing high connectivity without requiring much of the scarce network capacity. On the other side the hybrid routing protocols in MANETs likes Zone Routing Protocol still need route "re-discover" time when a route between zones link break. Sine the topology update information needs to be broadcast routing request on local zone. Due to this delay, the routing protocol may not be applicable for real-time data and multimedia communication. We utilize the advantages of a clustering organization and multi-routing path in routing protocol to achieve several goals at the same time. Firstly, IRP efficiently saves network bandwidth and reduces route reconstruction time when a routing path fails. The IRP protocol does not require global periodic routing advertisements, local control agents will automatically monitor and repair broke links. Secondly, it efficiently reduces congestion and traffic "bottlenecks" for ClusterHeads in clustering network. Thirdly, it reduces significant overheads associated with maintaining clusters. Fourthly, it improves clusters stability due to dynamic topology changing frequently. In this paper, we present the Intelligent Routing Protocol. First, we discuss the problem of routing in ad hoc networks and the motivation of IRP. We describe the hierarchical architecture of IRP. We describe the routing process and illustrate it with an example. Further, we describe the control manage

Design Multi-Sides System Unmanned Surface Vehicle (USV) Rocket

Science.gov (United States)

Syam, Rafiudin; Sutresman, Onny; Mappaita, Abdullah; Amiruddin; Wiranata, Ardi

2018-02-01

This study aims to design and test USV multislide forms. This system is excellent for maneuvering on the x-y-z coordinates. The disadvantage of a single side USV is that it is very difficult to maneuver to achieve very dynamic targets. While for multi sides system easily maneuvered though x-y-z coordinates. In addition to security defense purposes, multi-side system is also good for maritime intelligence, surveillance. In this case, electric deducted fan with Multi-Side system so that the vehicle can still operate even in reverse condition. Multipleside USV experiments have done with good results. In a USV study designed to use two propulsions.

IMHRP: Improved Multi-Hop Routing Protocol for Wireless Sensor Networks

Science.gov (United States)

Huang, Jianhua; Ruan, Danwei; Hong, Yadong; Zhao, Ziming; Zheng, Hong

2017-10-01

Wireless sensor network (WSN) is a self-organizing system formed by a large number of low-cost sensor nodes through wireless communication. Sensor nodes collect environmental information and transmit it to the base station (BS). Sensor nodes usually have very limited battery energy. The batteries cannot be charged or replaced. Therefore, it is necessary to design an energy efficient routing protocol to maximize the network lifetime. This paper presents an improved multi-hop routing protocol (IMHRP) for homogeneous networks. In the IMHRP protocol, based on the distances to the BS, the CH nodes are divided into internal CH nodes and external CH nodes. The set-up phase of the protocol is based on the LEACH protocol and the minimum distance between CH nodes are limited to a special constant distance, so a more uniform distribution of CH nodes is achieved. In the steady-state phase, the routes of different CH nodes are created on the basis of the distances between the CH nodes. The energy efficiency of communication can be maximized. The simulation results show that the proposed algorithm can more effectively reduce the energy consumption of each round and prolong the network lifetime compared with LEACH protocol and MHT protocol.

Development of a Multi-Event Trajectory Optimization Tool for Noise-Optimized Approach Route Design

NARCIS (Netherlands)

Braakenburg, M.L.; Hartjes, S.; Visser, H.G.; Hebly, S.J.

2011-01-01

This paper presents preliminary results from an ongoing research effort towards the development of a multi-event trajectory optimization methodology that allows to synthesize RNAV approach routes that minimize a cumulative measure of noise, taking into account the total noise effect aggregated for

Multi-Period Trading via Convex Optimization

DEFF Research Database (Denmark)

Boyd, Stephen; Busseti, Enzo; Diamond, Steve

2017-01-01

We consider a basic model of multi-period trading, which can be used to evaluate the performance of a trading strategy. We describe a framework for single-period optimization, where the trades in each period are found by solving a convex optimization problem that trades off expected return, risk......, transaction cost and holding cost such as the borrowing cost for shorting assets. We then describe a multi-period version of the trading method, where optimization is used to plan a sequence of trades, with only the first one executed, using estimates of future quantities that are unknown when the trades....... In this paper, we do not address a critical component in a trading algorithm, the predictions or forecasts of future quantities. The methods we describe in this paper can be thought of as good ways to exploit predictions, no matter how they are made. We have also developed a companion open-source software...

A granular tabu search algorithm for a real case study of a vehicle routing problem with a heterogeneous fleet and time windows

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Jose Bernal

2017-10-01

Full Text Available Purpose: We consider a real case study of a vehicle routing problem with a heterogeneous fleet and time windows (HFVRPTW for a franchise company bottling Coca-Cola products in Colombia. This study aims to determine the routes to be performed to fulfill the demand of the customers by using a heterogeneous fleet and considering soft time windows. The objective is to minimize the distance traveled by the performed routes. Design/methodology/approach: We propose a two-phase heuristic algorithm. In the proposed approach, after an initial phase (first phase, a granular tabu search is applied during the improvement phase (second phase. Two additional procedures are considered to help that the algorithm could escape from local optimum, given that during a given number of iterations there has been no improvement. Findings: Computational experiments on real instances show that the proposed algorithm is able to obtain high-quality solutions within a short computing time compared to the results found by the software that the company currently uses to plan the daily routes. Originality/value: We propose a novel metaheuristic algorithm for solving a real routing problem by considering heterogeneous fleet and time windows. The efficiency of the proposed approach has been tested on real instances, and the computational experiments shown its applicability and performance for solving NP-Hard Problems related with routing problems with similar characteristics. The proposed algorithm was able to improve some of the current solutions applied by the company by reducing the route length and the number of vehicles.

Multi-Mission Earth Vehicle Subsonic Dynamic Stability Testing and Analyses

Science.gov (United States)

Glaab, Louis J.; Fremaux, C. Michael

2013-01-01

Multi-Mission Earth Entry Vehicles (MMEEVs) are blunt-body vehicles designed with the purpose of transporting payloads from outer space to the surface of the Earth. To achieve high-reliability and minimum weight, MMEEVs avoid use of limited-reliability systems, such as parachutes, retro-rockets, and reaction control systems and rely on the natural aerodynamic stability of the vehicle throughout the Entry, Descent, and Landing (EDL) phase of flight. The Multi-Mission Systems Analysis for Planetary Entry (M-SAPE) parametric design tool is used to facilitate the design of MMEEVs for an array of missions and develop and visualize the trade space. Testing in NASA Langley?s Vertical Spin Tunnel (VST) was conducted to significantly improve M-SAPE?s subsonic aerodynamic models. Vehicle size and shape can be driven by entry flight path angle and speed, thermal protection system performance, terminal velocity limitations, payload mass and density, among other design parameters. The objectives of the VST testing were to define usable subsonic center of gravity limits, and aerodynamic parameters for 6-degree-of-freedom (6-DOF) simulations, for a range of MMEEV designs. The range of MMEEVs tested was from 1.8m down to 1.2m diameter. A backshell extender provided the ability to test a design with a much larger payload for the 1.2m MMEEV.

Fault-tolerant cooperative output regulation for multi-vehicle systems with sensor faults

Science.gov (United States)

Qin, Liguo; He, Xiao; Zhou, D. H.

2017-10-01

This paper presents a unified framework of fault diagnosis and fault-tolerant cooperative output regulation (FTCOR) for a linear discrete-time multi-vehicle system with sensor faults. The FTCOR control law is designed through three steps. A cooperative output regulation (COR) controller is designed based on the internal mode principle when there are no sensor faults. A sufficient condition on the existence of the COR controller is given based on the discrete-time algebraic Riccati equation (DARE). Then, a decentralised fault diagnosis scheme is designed to cope with sensor faults occurring in followers. A residual generator is developed to detect sensor faults of each follower, and a bank of fault-matching estimators are proposed to isolate and estimate sensor faults of each follower. Unlike the current distributed fault diagnosis for multi-vehicle systems, the presented decentralised fault diagnosis scheme in each vehicle reduces the communication and computation load by only using the information of the vehicle. By combing the sensor fault estimation and the COR control law, an FTCOR controller is proposed. Finally, the simulation results demonstrate the effectiveness of the FTCOR controller.

A MULTI-AGENT SYSTEM FOR FOREST TRANSPORT ACTIVITY PLANNING

Directory of Open Access Journals (Sweden)

Carlos Alberto Araújo Júnior

2017-09-01

Full Text Available This study aims to propose and implement a conceptual model of an intelligent system in a georeferenced environment to determine the design of forest transport fleets. For this, we used a multi-agent systems based tool, which is the subject of studies of distributed artificial intelligence. The proposed model considers the use of plantation mapping (stands and forest roads, as well as information about the different vehicle transport capacities. The system was designed to adapt itself to changes that occur during the forest transport operation process, such as the modification of demanded volume or the inclusion of route restrictions used by the vehicles. For its development, we used the Java programming language associated with the LPSolve library for the optimization calculation, the JADE platform to develop agents, and the ArcGis Runtime to determine the optimal transport routes. Five agents were modelled: the transporter, controller, router, loader and unloader agents. The model is able to determine the amount of trucks among the different vehicles available that meet the demand and availability of routes, with a focus on minimizing the total costs of timber transport. The system can also rearrange itself after the transportation routes change during the process.

Vehicle response-based track geometry assessment using multi-body simulation

Science.gov (United States)

Kraft, Sönke; Causse, Julien; Coudert, Frédéric

2018-02-01

The assessment of the geometry of railway tracks is an indispensable requirement for safe rail traffic. Defects which represent a risk for the safety of the train have to be identified and the necessary measures taken. According to current standards, amplitude thresholds are applied to the track geometry parameters measured by recording cars. This geometry-based assessment has proved its value but suffers from the low correlation between the geometry parameters and the vehicle reactions. Experience shows that some defects leading to critical vehicle reactions are underestimated by this approach. The use of vehicle responses in the track geometry assessment process allows identifying critical defects and improving the maintenance operations. This work presents a vehicle response-based assessment method using multi-body simulation. The choice of the relevant operation conditions and the estimation of the simulation uncertainty are outlined. The defects are identified from exceedances of track geometry and vehicle response parameters. They are then classified using clustering methods and the correlation with vehicle response is analysed. The use of vehicle responses allows the detection of critical defects which are not identified from geometry parameters.

Systems and methods for vehicle speed management

Science.gov (United States)

Sujan, Vivek Anand; Vajapeyazula, Phani; Follen, Kenneth; Wu, An; Forst, Howard Robert

2016-03-01

Controlling a speed of a vehicle based on at least a portion of a route grade and a route distance divided into a plurality of route sections, each including at least one of a section grade and section length. Controlling the speed of the vehicle is further based on determining a cruise control speed mode for the vehicle for each of the plurality of route sections and determining a speed reference command of the vehicle based on at least one of the cruise control speed mode, the section length, the section grade, and a current speed.

An Endosymbiotic Evolutionary Algorithm for the Hub Location-Routing Problem

Directory of Open Access Journals (Sweden)

Ji Ung Sun

2015-01-01

Full Text Available We consider a capacitated hub location-routing problem (HLRP which combines the hub location problem and multihub vehicle routing decisions. The HLRP not only determines the locations of the capacitated p-hubs within a set of potential hubs but also deals with the routes of the vehicles to meet the demands of customers. This problem is formulated as a 0-1 mixed integer programming model with the objective of the minimum total cost including routing cost, fixed hub cost, and fixed vehicle cost. As the HLRP has impractically demanding for the large sized problems, we develop a solution method based on the endosymbiotic evolutionary algorithm (EEA which solves hub location and vehicle routing problem simultaneously. The performance of the proposed algorithm is examined through a comparative study. The experimental results show that the proposed EEA can be a viable solution method for the supply chain network planning.

Single-vehicle and Multi-vehicle Accidents Involving Motorcycles in a Small City in China: Characteristics and Injury Patterns

Directory of Open Access Journals (Sweden)

Lili Xiong

2015-03-01

Full Text Available Introduction: There is a gap that involves examining differences between patients in single-vehicle (SV versus multi-vehicle (MV accidents involving motorcycles in Shantou, China, regarding the injury patterns and mortality the patients sustained. This study aims to address this gap and provide a basis and reference for motorcycle injury prevention. Method: Medical record data was collected between October 2002 and June 2012 on all motorcycle injury patients admitted to a hospital in the city of Shantou of the east Guangdong province in China. Comparative analysis was conducted between patients in SV accidents and patients in MV accidents regarding demographic and clinic characteristics, mortality, and injury patterns. Results: Approximately 48% (n = 1977 of patients were involved in SV accidents and 52% (n = 2119 were involved in MV accidents. The average age was 34 years. Collision of a motorcycle with a heavy vehicle/bus (4% was associated with a 34 times greater risk of death (RR: 34.32|95% CI: 17.43–67.57. Compared to patients involved in MV accidents, those involved in SV accidents were more likely to sustain a skull fracture (RR: 1.47|95% CI: 1.22–1.77, an open head wound (RR: 1.46|95% CI: 1.23–1.74, an intracranial injury (RR: 1.39|95% CI: 1.26–1.53, a superficial head injury (RR: 1.37|95% CI: 1.01–1.86, an injury to an organ (RR: 2.01|95% CI: 1.24–3.26, and a crushing injury (RR: 1.98|95% CI: 1.06–3.70 to the thorax or abdomen. However, they were less likely to sustain a spinal fracture (RR: 0.58|95% CI: 0.39–0.85, a pelvic fracture (RR: 0.22|95% CI: 0.11–0.46, an upper extremity fracture (RR: 0.75|95% CI: 0.59–0.96, or injuries to their lower extremities, except for a dislocation, sprain, or injury to a joint or ligament (RR: 0.82|95% CI: 0.49–1.36. Conclusion: The relative risk of death is higher for patients involved in multi-vehicle accidents than patients in single-vehicle accidents, especially when a

Development of a multi-criteria assessment model for ranking of renewable and non-renewable transportation fuel vehicles

International Nuclear Information System (INIS)

Safaei Mohamadabadi, H.; Tichkowsky, G.; Kumar, A.

2009-01-01

Several factors, including economical, environmental, and social factors, are involved in selection of the best fuel-based vehicles for road transportation. This leads to a multi-criteria selection problem for multi-alternatives. In this study, a multi-criteria assessment model was developed to rank different road transportation fuel-based vehicles (both renewable and non-renewable) using a method called Preference Ranking Organization Method for Enrichment and Evaluations (PROMETHEE). This method combines qualitative and quantitative criteria to rank various alternatives. In this study, vehicles based on gasoline, gasoline-electric (hybrid), E85 ethanol, diesel, B100 biodiesel, and compressed natural gas (CNG) were considered as alternatives. These alternatives were ranked based on five criteria: vehicle cost, fuel cost, distance between refueling stations, number of vehicle options available to the consumer, and greenhouse gas (GHG) emissions per unit distance traveled. In addition, sensitivity analyses were performed to study the impact of changes in various parameters on final ranking. Two base cases and several alternative scenarios were evaluated. In the base case scenario with higher weight on economical parameters, gasoline-based vehicle was ranked higher than other vehicles. In the base case scenario with higher weight on environmental parameters, hybrid vehicle was ranked first followed by biodiesel-based vehicle

Development of a multi-criteria assessment model for ranking of renewable and non-renewable transportation fuel vehicles

Energy Technology Data Exchange (ETDEWEB)

Safaei Mohamadabadi, H.; Tichkowsky, G.; Kumar, A. [Department of Mechanical Engineering, University of Alberta, Edmonton, Alberta (Canada)

2009-01-15

Several factors, including economical, environmental, and social factors, are involved in selection of the best fuel-based vehicles for road transportation. This leads to a multi-criteria selection problem for multi-alternatives. In this study, a multi-criteria assessment model was developed to rank different road transportation fuel-based vehicles (both renewable and non-renewable) using a method called Preference Ranking Organization Method for Enrichment and Evaluations (PROMETHEE). This method combines qualitative and quantitative criteria to rank various alternatives. In this study, vehicles based on gasoline, gasoline-electric (hybrid), E85 ethanol, diesel, B100 biodiesel, and compressed natural gas (CNG) were considered as alternatives. These alternatives were ranked based on five criteria: vehicle cost, fuel cost, distance between refueling stations, number of vehicle options available to the consumer, and greenhouse gas (GHG) emissions per unit distance traveled. In addition, sensitivity analyses were performed to study the impact of changes in various parameters on final ranking. Two base cases and several alternative scenarios were evaluated. In the base case scenario with higher weight on economical parameters, gasoline-based vehicle was ranked higher than other vehicles. In the base case scenario with higher weight on environmental parameters, hybrid vehicle was ranked first followed by biodiesel-based vehicle. (author)

A queueing framework for routing problems with time-dependent travel times

NARCIS (Netherlands)

Woensel, van T.; Kerbache, L.; Peremans, H.; Vandaele, N.J.

2007-01-01

Assigning and scheduling vehicle routes in a dynamic environment is a crucial management problem. Despite numerous publications dealing with efficient scheduling methods for vehicle routing, very few addressed the inherent stochastic and dynamic nature of travel times. In this paper, a vehicle

The impact of short term traffic forecasting on the effectiveness of vehicles routes planning in urban areas

Energy Technology Data Exchange (ETDEWEB)

Kubek, D.

2016-07-01

An impossibility to foresee in advance the accurate traffic parameters in face of dynamism phenomena in complex transportation system is a one of the major source of uncertainty. The paper presents an approach to robust optimization of logistics vehicle routes in urban areas on the basis of estimated short-term traffic time forecasts in a selected area of the urban road network. The forecast values of optimization parameters have been determined using the spectral analysis model, taking into account the forecast uncertainty degree. The robust counterparts approach of uncertain bi-criteria shortest path problem formulation is used to determining the robust routes for logistics vehicles in the urban network. The uncertainty set is created on the basis of forecast travel times in chosen sections, estimated by means of spectral analysis. The advantages and the characteristics are exemplified in the actual Krakow road network. The obtained data have been compared with classic approach wherein it is assumed that the optimization parameters are certain and accurate. The results obtained in the simulation example indicate that use of forecasting techniques with robust optimization models has a positive impact on the quality of final solutions. (Author)

Developing cross entropy genetic algorithm for solving Two-Dimensional Loading Heterogeneous Fleet Vehicle Routing Problem (2L-HFVRP)

Science.gov (United States)

Paramestha, D. L.; Santosa, B.

2018-04-01

Two-dimensional Loading Heterogeneous Fleet Vehicle Routing Problem (2L-HFVRP) is a combination of Heterogeneous Fleet VRP and a packing problem well-known as Two-Dimensional Bin Packing Problem (BPP). 2L-HFVRP is a Heterogeneous Fleet VRP in which these costumer demands are formed by a set of two-dimensional rectangular weighted item. These demands must be served by a heterogeneous fleet of vehicles with a fix and variable cost from the depot. The objective function 2L-HFVRP is to minimize the total transportation cost. All formed routes must be consistent with the capacity and loading process of the vehicle. Sequential and unrestricted scenarios are considered in this paper. We propose a metaheuristic which is a combination of the Genetic Algorithm (GA) and the Cross Entropy (CE) named Cross Entropy Genetic Algorithm (CEGA) to solve the 2L-HFVRP. The mutation concept on GA is used to speed up the algorithm CE to find the optimal solution. The mutation mechanism was based on local improvement (2-opt, 1-1 Exchange, and 1-0 Exchange). The probability transition matrix mechanism on CE is used to avoid getting stuck in the local optimum. The effectiveness of CEGA was tested on benchmark instance based 2L-HFVRP. The result of experiments shows a competitive result compared with the other algorithm.

A granular t abu search algorithm for a real case study of a vehicle routing problem with a heterogeneous fleet and time windows

Energy Technology Data Exchange (ETDEWEB)

Bernal, Jose; Escobar, John Willmer; Linfati, Rodrigo

2017-07-01

We consider a real case study of a vehicle routing problem with a heterogeneous fleet and time windows (HFVRPTW) for a franchise company bottling Coca-Cola products in Colombia. This study aims to determine the routes to be performed to fulfill the demand of the customers by using a heterogeneous fleet and considering soft time windows. The objective is to minimize the distance traveled by the performed routes. Design/methodology/approach: We propose a two-phase heuristic algorithm. In the proposed approach, after an initial phase (first phase), a granular tabu search is applied during the improvement phase (second phase). Two additional procedures are considered to help that the algorithm could escape from local optimum, given that during a given number of iterations there has been no improvement. Findings: Computational experiments on real instances show that the proposed algorithm is able to obtain high-quality solutions within a short computing time compared to the results found by the software that the company currently uses to plan the daily routes. Originality/value: We propose a novel metaheuristic algorithm for solving a real routing problem by considering heterogeneous fleet and time windows. The efficiency of the proposed approach has been tested on real instances, and the computational experiments shown its applicability and performance for solving NP-Hard Problems related with routing problems with similar characteristics. The proposed algorithm was able to improve some of the current solutions applied by the company by reducing the route length and the number of vehicles.

A granular t abu search algorithm for a real case study of a vehicle routing problem with a heterogeneous fleet and time windows

International Nuclear Information System (INIS)

Bernal, Jose; Escobar, John Willmer; Linfati, Rodrigo

2017-01-01

We consider a real case study of a vehicle routing problem with a heterogeneous fleet and time windows (HFVRPTW) for a franchise company bottling Coca-Cola products in Colombia. This study aims to determine the routes to be performed to fulfill the demand of the customers by using a heterogeneous fleet and considering soft time windows. The objective is to minimize the distance traveled by the performed routes. Design/methodology/approach: We propose a two-phase heuristic algorithm. In the proposed approach, after an initial phase (first phase), a granular tabu search is applied during the improvement phase (second phase). Two additional procedures are considered to help that the algorithm could escape from local optimum, given that during a given number of iterations there has been no improvement. Findings: Computational experiments on real instances show that the proposed algorithm is able to obtain high-quality solutions within a short computing time compared to the results found by the software that the company currently uses to plan the daily routes. Originality/value: We propose a novel metaheuristic algorithm for solving a real routing problem by considering heterogeneous fleet and time windows. The efficiency of the proposed approach has been tested on real instances, and the computational experiments shown its applicability and performance for solving NP-Hard Problems related with routing problems with similar characteristics. The proposed algorithm was able to improve some of the current solutions applied by the company by reducing the route length and the number of vehicles.

A Review of Vehicle to Vehicle Communication Protocols for VANETs in the Urban Environment

Directory of Open Access Journals (Sweden)

Irshad Ahmed Abbasi

2018-01-01

Full Text Available Vehicular Ad-hoc Networks (VANETs have been gaining significant attention from the research community due to their increasing importance for building an intelligent transportation system. The characteristics of VANETs, such as high mobility, network partitioning, intermittent connectivity and obstacles in city environments, make routing a challenging task. Due to these characteristics of VANETs, the performance of a routing protocol is degraded. The position-based routing is considered to be the most significant approach in VANETs. In this paper, we present a brief review of most significant position based unicast routing protocols designed for vehicle to vehicle communications in the urban environment. We provide them with their working features for exchanging information between vehicular nodes. We describe their pros and cons. This study also provides a comparison of the vehicle to vehicle communication based routing protocols. The comparative study is based on some significant factors such as mobility, traffic density, forwarding techniques and method of junction selection mechanism, and strategy used to handle a local optimum situation. It also provides the simulation based study of existing dynamic junction selection routing protocols and a static junction selection routing protocol. It provides a profound insight into the routing techniques suggested in this area and the most valuable solutions to advance VANETs. More importantly, it can be used as a source of references to other researchers in finding literature that is relevant to routing in VANETs.

Application of the pothole DAF method to vehicles traversing periodic roadway irregularities

Science.gov (United States)

Pesterev, A. V.; Bergman, L. A.; Tan, C. A.; Yang, B.

2005-01-01

This paper is a sequel to the work discussed in Pesterev et al. (Journal of Sound and Vibration, in press). In that paper, it was suggested that the technique to determine the effect of a local road surface irregularity on the dynamics of a vehicle modelled as a linear multi-degree-of-freedom system relies on the so-called pothole dynamic amplification factor (DAF), which is a complex-valued function specific to the irregularity shape. This paper discusses the companion problem of how to determine the DAF function for an irregularity represented as a superposition of simpler ones. Another purpose of this paper is to demonstrate the application of the pothole DAF functions technique to finding a priori estimates of the effect of irregularities with a repeated structure. Specifically, we solve the problem of finding the conditions under which the dynamic effect of two identical potholes located one after another is greater than that due to the single pothole. We also find the estimate for the number of periods of a periodic irregularity that are sufficient in order to consider the oscillator response as steady state. The discussions are illustrated by numerical examples.

Vehicle-Routing Optimization for Municipal Solid Waste Collection Using Genetic Algorithm: The Case of Southern Nablus City

Science.gov (United States)

Assaf, Ramiz; Saleh, Yahya

2017-09-01

Municipalities are responsible for solid waste collectiont for environmental, social and economic purposes. Practices of municipalities should be effective and efficient, with the objectives of reducing the total incurred costs in the solid waste collection network concurrently achieving the highest service level. This study aims at finding the best routes of solid waste collection network in Nablus city-Palestine. More specifically, the study seeks the optimal route that minimizes the total travelled distance by the trucks and hence the resulted costs. The current situation is evaluated and the problem is modelled as a Vehicle Routing Problem (VRP). The VRP is then optimized via a genetic algorithm. Specifically, compared to the current situation, the trucks total travelled distance was reduced by 66%, whereas the collection time was reduced from 7 hours per truck-trip to 2.3 hours. The findings of this study is useful for all municipality policy makers that are responsible for solid waste collection.

A Combination of Genetic Algorithm and Particle Swarm Optimization for Vehicle Routing Problem with Time Windows.

Science.gov (United States)

Xu, Sheng-Hua; Liu, Ji-Ping; Zhang, Fu-Hao; Wang, Liang; Sun, Li-Jian

2015-08-27

A combination of genetic algorithm and particle swarm optimization (PSO) for vehicle routing problems with time windows (VRPTW) is proposed in this paper. The improvements of the proposed algorithm include: using the particle real number encoding method to decode the route to alleviate the computation burden, applying a linear decreasing function based on the number of the iterations to provide balance between global and local exploration abilities, and integrating with the crossover operator of genetic algorithm to avoid the premature convergence and the local minimum. The experimental results show that the proposed algorithm is not only more efficient and competitive with other published results but can also obtain more optimal solutions for solving the VRPTW issue. One new well-known solution for this benchmark problem is also outlined in the following.

Efficient Secure and Privacy-Preserving Route Reporting Scheme for VANETs

Science.gov (United States)

Zhang, Yuanfei; Pei, Qianwen; Dai, Feifei; Zhang, Lei

2017-10-01

Vehicular ad-hoc network (VANET) is a core component of intelligent traffic management system which could provide various of applications such as accident prediction, route reporting, etc. Due to the problems caused by traffic congestion, route reporting becomes a prospective application which can help a driver to get optimal route to save her travel time. Before enjoying the convenience of route reporting, security and privacy-preserving issues need to be concerned. In this paper, we propose a new secure and privacy-preserving route reporting scheme for VANETs. In our scheme, only an authenticated vehicle can use the route reporting service provided by the traffic management center. Further, a vehicle may receive the response from the traffic management center with low latency and without violating the privacy of the vehicle. Experiment results show that our scheme is much more efficiency than the existing one.

Feasibility of an Extended-Duration Aerial Platform Using Autonomous Multi-Rotor Vehicle Swapping and Battery Management

Science.gov (United States)

2017-12-01

AN EXTENDED-DURATION AERIAL PLATFORM USING AUTONOMOUS MULTI-ROTOR VEHICLE SWAPPING AND BATTERY MANAGEMENT by Alexander G. Williams December...Arlington, VA 22202-4302, and to the Office of Management and Budget, Paperwork Reduction Project (0704-0188) Washington DC 20503. 1. AGENCY USE ONLY...DURATION AERIAL PLATFORM USING AUTONOMOUS MULTI-ROTOR VEHICLE SWAPPING AND BATTERY MANAGEMENT 5. FUNDING NUMBERS 6. AUTHOR(S) Alexander G

A multilevel variable neighborhood search heuristic for a practical vehicle routing and driver scheduling problem

DEFF Research Database (Denmark)

Wen, Min; Krapper, Emil; Larsen, Jesper

2011-01-01

in their fresh meat supply logistics system. The problem consists of a 1‐week planning horizon, heterogeneous vehicles, and drivers with predefined work regulations. These regulations include, among other things, predefined workdays, fixed starting time, maximum weekly working duration, and a break rule......The world's second largest producer of pork, Danish Crown, also provides a fresh meat supply logistics system within Denmark. This is used by the majority of supermarkets in Denmark. This article addresses an integrated vehicle routing and driver scheduling problem arising at Danish Crown....... The objective is to minimize the total delivery cost that is a weighted sum of two kinds of delivery costs. A multilevel variable neighborhood search heuristic is proposed for the problem. In a preprocessing step, the problem size is reduced through an aggregation procedure. Thereafter, the aggregated weekly...

Multi-Vehicle Cooperative Control Research at the NASA Armstrong Flight Research Center, 2000-2014

Science.gov (United States)

Hanson, Curt

2014-01-01

A brief introductory overview of multi-vehicle cooperative control research conducted at the NASA Armstrong Flight Research Center from 2000 - 2014. Both flight research projects and paper studies are included. Since 2000, AFRC has been almost continuously pursuing research in the areas of formation flight for drag reduction and automated cooperative trajectories. An overview of results is given, including flight experiments done on the FA-18 and with the C-17. Other multi-vehicle cooperative research is discussed, including small UAV swarming projects and automated aerial refueling.

Distributed Optimization of Multi Beam Directional Communication Networks

Science.gov (United States)

2017-06-30

Distributed Optimization of Multi-Beam Directional Communication Networks Theodoros Tsiligkaridis MIT Lincoln Laboratory Lexington, MA 02141, USA...based routing. I. INTRODUCTION Missions where multiple communication goals are of in- terest are becoming more prevalent in military applications...Multilayer communications may occur within a coalition; for example, a team consisting of ground vehicles and an airborne set of assets may desire to

Modified artificial bee colony for the vehicle routing problems with time windows.

Science.gov (United States)

Alzaqebah, Malek; Abdullah, Salwani; Jawarneh, Sana

2016-01-01

The natural behaviour of the honeybee has attracted the attention of researchers in recent years and several algorithms have been developed that mimic swarm behaviour to solve optimisation problems. This paper introduces an artificial bee colony (ABC) algorithm for the vehicle routing problem with time windows (VRPTW). A Modified ABC algorithm is proposed to improve the solution quality of the original ABC. The high exploration ability of the ABC slows-down its convergence speed, which may due to the mechanism used by scout bees in replacing abandoned (unimproved) solutions with new ones. In the Modified ABC a list of abandoned solutions is used by the scout bees to memorise the abandoned solutions, then the scout bees select a solution from the list based on roulette wheel selection and replace by a new solution with random routs selected from the best solution. The performance of the Modified ABC is evaluated on Solomon benchmark datasets and compared with the original ABC. The computational results demonstrate that the Modified ABC outperforms the original ABC also produce good solutions when compared with the best-known results in the literature. Computational investigations show that the proposed algorithm is a good and promising approach for the VRPTW.

Exact Solutions to the Symmetric and Asymmetric Vehicle Routing Problem with Simultaneous Delivery and Pick-Up

Directory of Open Access Journals (Sweden)

Julia Rieck

2013-05-01

Full Text Available In reverse logistics networks, products (e.g., bottles or containers have to be transported from a depot to customer locations and, after use, from customer locations back to the depot. In order to operate economically beneficial, companies prefer a simultaneous delivery and pick-up service. The resulting Vehicle Routing Problem with Simultaneous Delivery and Pick-up (VRPSDP is an operational problem, which has to be solved daily by many companies. We present two mixed-integer linear model formulations for the VRPSDP, namely a vehicle-flow and a commodity-flow model. In order to strengthen the models, domain-reducing preprocessing techniques, and effective cutting planes are outlined. Symmetric benchmark instances known from the literature as well as new asymmetric instances derived from real-world problems are solved to optimality using CPLEX 12.1.

Stochastic multi-period multi-product multi-objective Aggregate Production Planning model in multi-echelon supply chain

Directory of Open Access Journals (Sweden)

Kaveh Khalili-Damghani

2017-07-01

Full Text Available In this paper a multi-period multi-product multi-objective aggregate production planning (APP model is proposed for an uncertain multi-echelon supply chain considering financial risk, customer satisfaction, and human resource training. Three conflictive objective functions and several sets of real constraints are considered concurrently in the proposed APP model. Some parameters of the proposed model are assumed to be uncertain and handled through a two-stage stochastic programming (TSSP approach. The proposed TSSP is solved using three multi-objective solution procedures, i.e., the goal attainment technique, the modified ε-constraint method, and STEM method. The whole procedure is applied in an automotive resin and oil supply chain as a real case study wherein the efficacy and applicability of the proposed approaches are illustrated in comparison with existing experimental production planning method.

A Novel Multi-Sensor Environmental Perception Method Using Low-Rank Representation and a Particle Filter for Vehicle Reversing Safety

Directory of Open Access Journals (Sweden)

Zutao Zhang

2016-06-01

Full Text Available Environmental perception and information processing are two key steps of active safety for vehicle reversing. Single-sensor environmental perception cannot meet the need for vehicle reversing safety due to its low reliability. In this paper, we present a novel multi-sensor environmental perception method using low-rank representation and a particle filter for vehicle reversing safety. The proposed system consists of four main steps, namely multi-sensor environmental perception, information fusion, target recognition and tracking using low-rank representation and a particle filter, and vehicle reversing speed control modules. First of all, the multi-sensor environmental perception module, based on a binocular-camera system and ultrasonic range finders, obtains the distance data for obstacles behind the vehicle when the vehicle is reversing. Secondly, the information fusion algorithm using an adaptive Kalman filter is used to process the data obtained with the multi-sensor environmental perception module, which greatly improves the robustness of the sensors. Then the framework of a particle filter and low-rank representation is used to track the main obstacles. The low-rank representation is used to optimize an objective particle template that has the smallest L-1 norm. Finally, the electronic throttle opening and automatic braking is under control of the proposed vehicle reversing control strategy prior to any potential collisions, making the reversing control safer and more reliable. The final system simulation and practical testing results demonstrate the validity of the proposed multi-sensor environmental perception method using low-rank representation and a particle filter for vehicle reversing safety.

Multi-path transportation futures study : vehicle characterization and scenario analyses.

Energy Technology Data Exchange (ETDEWEB)

Plotkin, S. E.; Singh, M. K.; Energy Systems; TA Engineering; ORNL

2009-12-03

Projecting the future role of advanced drivetrains and fuels in the light vehicle market is inherently difficult, given the uncertainty (and likely volatility) of future oil prices, inadequate understanding of likely consumer response to new technologies, the relative infancy of several important new technologies with inevitable future changes in their performance and costs, and the importance - and uncertainty - of future government marketplace interventions (e.g., new regulatory standards or vehicle purchase incentives). This Multi-Path Transportation Futures (MP) Study has attempted to improve our understanding of this future role by examining several scenarios of vehicle costs, fuel prices, government subsidies, and other key factors. These are projections, not forecasts, in that they try to answer a series of 'what if' questions without assigning probabilities to most of the basic assumptions.

Optimization of an implicit constrained multi-physics system for motor wheels of electric vehicle

International Nuclear Information System (INIS)

Lei, Fei; Du, Bin; Liu, Xin; Xie, Xiaoping; Chai, Tian

2016-01-01

In this paper, implicit constrained multi-physics model of a motor wheel for an electric vehicle is built and then optimized. A novel optimization approach is proposed to solve the compliance problem between implicit constraints and stochastic global optimization. Firstly, multi-physics model of motor wheel is built from the theories of structural mechanics, electromagnetism and thermal physics. Then, implicit constraints are applied from the vehicle performances and magnetic characteristics. Implicit constrained optimization is carried out by a series of unconstrained optimization and verifications. In practice, sequentially updated subspaces are designed to completely substitute the original design space in local areas. In each subspace, a solution is obtained and is then verified by the implicit constraints. Optimal solutions which satisfy the implicit constraints are accepted as final candidates. The final global optimal solution is optimized from those candidates. Discussions are carried out to discover the differences between optimal solutions with unconstrained problem and different implicit constrained problems. Results show that the implicit constraints have significant influences on the optimal solution and the proposed approach is effective in finding the optimals. - Highlights: • An implicit constrained multi-physics model is built for sizing a motor wheel. • Vehicle dynamic performances are applied as implicit constraints for nonlinear system. • An efficient novel optimization is proposed to explore the constrained design space. • The motor wheel is optimized to achieve maximum efficiency on vehicle dynamics. • Influences of implicit constraints on vehicle performances are compared and analyzed.

MULTI PERIOD SHOCKS ROLES ON GOVERNMENT SPENDING IN INDONESIA

Directory of Open Access Journals (Sweden)

Jaka Sriyana

2011-09-01

Full Text Available This paper proposes an alternative dynamic model of government spending in Indonesia. The model is based on short term disequilibrium assumption, in which multi period of shocks variables may play an important role. This research applies a loss function approach and uses optimum shock variables as the determinant for government spending during 1970-2010. The result shows that real GDP, population, and multi period shock of government spending are statistically significant. It provides evidence of the impact of multi period shocks to the realization of government spending. It implies that government faces a serious disequilibrium in determining their spending both in short and long terms.Keywords: Fiscal, government spending, deficit budget, shockJEL classification numbers: H53, H62, C22

A heuristic algorithm for a multi-product four-layer capacitated location-routing problem

Directory of Open Access Journals (Sweden)

Mohsen Hamidi

2014-01-01

Full Text Available The purpose of this study is to solve a complex multi-product four-layer capacitated location-routing problem (LRP in which two specific constraints are taken into account: 1 plants have limited production capacity, and 2 central depots have limited capacity for storing and transshipping products. The LRP represents a multi-product four-layer distribution network that consists of plants, central depots, regional depots, and customers. A heuristic algorithm is developed to solve the four-layer LRP. The heuristic uses GRASP (Greedy Randomized Adaptive Search Procedure and two probabilistic tabu search strategies of intensification and diversification to tackle the problem. Results show that the heuristic solves the problem effectively.

Integrated planning of electric vehicles routing and charging stations location considering transportation networks and power distribution systems

Directory of Open Access Journals (Sweden)

Andrés Arias

2018-09-01

Full Text Available Electric Vehicles (EVs represent a significant option that contributes to improve the mobility and reduce the pollution, leaving a future expectation in the merchandise transportation sector, which has been demonstrated with pilot projects of companies operating EVs for products delivering. In this work a new approach of EVs for merchandise transportation considering the location of Electric Vehicle Charging Stations (EVCSs and the impact on the Power Distribution System (PDS is addressed. This integrated planning is formulated through a mixed integer non-linear mathematical model. Test systems of different sizes are designed to evaluate the model performance, considering the transportation network and PDS. The results show a trade-off between EVs routing, PDS energy losses and EVCSs location.

Resonant Quasi-Optical Systems with Multi-Row Periodic Structures

DEFF Research Database (Denmark)

Oleksandr, Rybalko; Rybalko, Yu A.; Buriak, I. A.

2017-01-01

Selective properties of resonant quasi-optical systems with periodical multi-row structures in millimeter wavelength range are described. The possibility of selection fluctuations in the volume of open resonator using double-row periodic elements was shown in the experiment at 70-80 GHz. Advantages...... and possibility of control the energy characteristics of such structures are also described. The obtained experimental data is used to confirm the results of computational analysis previously described in the literature. Implementation of resonant quasi-optical systems with multi-row periodic structures...

Real-Time Multi-Target Localization from Unmanned Aerial Vehicles

Directory of Open Access Journals (Sweden)

Xuan Wang

2016-12-01

Full Text Available In order to improve the reconnaissance efficiency of unmanned aerial vehicle (UAV electro-optical stabilized imaging systems, a real-time multi-target localization scheme based on an UAV electro-optical stabilized imaging system is proposed. First, a target location model is studied. Then, the geodetic coordinates of multi-targets are calculated using the homogeneous coordinate transformation. On the basis of this, two methods which can improve the accuracy of the multi-target localization are proposed: (1 the real-time zoom lens distortion correction method; (2 a recursive least squares (RLS filtering method based on UAV dead reckoning. The multi-target localization error model is established using Monte Carlo theory. In an actual flight, the UAV flight altitude is 1140 m. The multi-target localization results are within the range of allowable error. After we use a lens distortion correction method in a single image, the circular error probability (CEP of the multi-target localization is reduced by 7%, and 50 targets can be located at the same time. The RLS algorithm can adaptively estimate the location data based on multiple images. Compared with multi-target localization based on a single image, CEP of the multi-target localization using RLS is reduced by 25%. The proposed method can be implemented on a small circuit board to operate in real time. This research is expected to significantly benefit small UAVs which need multi-target geo-location functions.

Natural gas application in light- and heavy-duty vehicles in Brazil: panorama, technological routes and perspectives

Energy Technology Data Exchange (ETDEWEB)

Machado, Guilherme Bastos, Cordeiro de Melo, Tadeu Cavalcante; Leao, Raphael Riemke de Campos Cesar; Iaccarino, Fernando Aniello; Figueiredo Moreira, Marcia

2007-07-01

The Brazilian CNG light-duty vehicle fleet has currently reached more than 1,300,000 units. This growth increased in the late 1990's, when CNG was approved for use in passenger cars. In 2001, the IBAMA (Brazilian Institute for Environment and Natural Renewable Resources), concerned with this uncontrolled growth, published CONAMA (National Environmental Council, controlled by IBAMA) resolution 291, which establishes rules for CNG conversion kit environmental certification.This paper discusses the technological challenges for CNG-converted vehicles to comply with PROCONVE (Brazilian Program for Automotive Air Pollution Control) emission limits. In the 1980's, because of the oil crisis, Natural Gas (NG) emerged as a fuel with great potential to replace Diesel in heavy-duty vehicles. Some experiences were conducted for partial conversions from Diesel to NG (Diesel-gas). Other experiences using NG Otto Cycle buses were conducted in some cities, but have not expanded. Another technological route called 'Ottolization' (Diesel to Otto cycle convertion) appeared recently. Population increase and the great growth in vehicle fleet promote a constant concern with automotive emissions. More restrictive emission limits, high international oil prices, and the strategic interest in replacing Diesel imports, altogether form an interesting scenario for CNG propagation to public transportation in the main Brazilian metropolises.

A Modular Swarm Optimization Framework Enabling Multi-Vehicle Coordinated Path Planning, Phase I

Data.gov (United States)

National Aeronautics and Space Administration — The advancement of Unmanned Aerial Systems (UAS) with computing power and communications hardware has enabled an increased capability set for multi-vehicle...

A new algorithm for solving the inventory routing problem with direct shipment

Directory of Open Access Journals (Sweden)

Ali Hossein Mirzaei

2012-02-01

Full Text Available   In this paper a multi-commodity multi-period inventory routing problem in a two-echelon supply chain consisting of a manufacturer and a set of retailers has been studied. In addition to inventory management and distribution planning, production planning has also been considered in the above problem. The objective is to minimize total system cost that consists of production setup, inventory holding and distribution costs. The commodities are delivered to the retailers by an identical fleet of limited capacity vehicles through direct shipment strategy. Also it is assumed that production and storage capacity is limited and stockout is not allowed. Since similar problems without distribution planning are known as NP-hard, this is also an NP-hard problem. Therefore, in this paper, a new improved particle swarm optimization algorithm has been developed consisting of two distinguished phases for problem solving. First, the values of binary variables are determined using the proposed algorithm and then, the continuous variables are calculated by solving a linear programming model. Performance of the proposed algorithm has been compared with genetic and original particle swarm optimization algorithms using various samples of random problems. The findings imply significant performance of the proposed algorithm.         

Predicting Energy Consumption for Potential Effective Use in Hybrid Vehicle Powertrain Management Using Driver Prediction

Science.gov (United States)

Magnuson, Brian

A proof-of-concept software-in-the-loop study is performed to assess the accuracy of predicted net and charge-gaining energy consumption for potential effective use in optimizing powertrain management of hybrid vehicles. With promising results of improving fuel efficiency of a thermostatic control strategy for a series, plug-ing, hybrid-electric vehicle by 8.24%, the route and speed prediction machine learning algorithms are redesigned and implemented for real- world testing in a stand-alone C++ code-base to ingest map data, learn and predict driver habits, and store driver data for fast startup and shutdown of the controller or computer used to execute the compiled algorithm. Speed prediction is performed using a multi-layer, multi-input, multi- output neural network using feed-forward prediction and gradient descent through back- propagation training. Route prediction utilizes a Hidden Markov Model with a recurrent forward algorithm for prediction and multi-dimensional hash maps to store state and state distribution constraining associations between atomic road segments and end destinations. Predicted energy is calculated using the predicted time-series speed and elevation profile over the predicted route and the road-load equation. Testing of the code-base is performed over a known road network spanning 24x35 blocks on the south hill of Spokane, Washington. A large set of training routes are traversed once to add randomness to the route prediction algorithm, and a subset of the training routes, testing routes, are traversed to assess the accuracy of the net and charge-gaining predicted energy consumption. Each test route is traveled a random number of times with varying speed conditions from traffic and pedestrians to add randomness to speed prediction. Prediction data is stored and analyzed in a post process Matlab script. The aggregated results and analysis of all traversals of all test routes reflect the performance of the Driver Prediction algorithm. The

A New TS Algorithm for Solving Low-Carbon Logistics Vehicle Routing Problem with Split Deliveries by Backpack—From a Green Operation Perspective

Science.gov (United States)

Fu, Zhuo; Wang, Jiangtao

2018-01-01

In order to promote the development of low-carbon logistics and economize logistics distribution costs, the vehicle routing problem with split deliveries by backpack is studied. With the help of the model of classical capacitated vehicle routing problem, in this study, a form of discrete split deliveries was designed in which the customer demand can be split only by backpack. A double-objective mathematical model and the corresponding adaptive tabu search (TS) algorithm were constructed for solving this problem. By embedding the adaptive penalty mechanism, and adopting the random neighborhood selection strategy and reinitialization principle, the global optimization ability of the new algorithm was enhanced. Comparisons with the results in the literature show the effectiveness of the proposed algorithm. The proposed method can save the costs of low-carbon logistics and reduce carbon emissions, which is conducive to the sustainable development of low-carbon logistics. PMID:29747469

A New TS Algorithm for Solving Low-Carbon Logistics Vehicle Routing Problem with Split Deliveries by Backpack-From a Green Operation Perspective.

Science.gov (United States)

Xia, Yangkun; Fu, Zhuo; Tsai, Sang-Bing; Wang, Jiangtao

2018-05-10

In order to promote the development of low-carbon logistics and economize logistics distribution costs, the vehicle routing problem with split deliveries by backpack is studied. With the help of the model of classical capacitated vehicle routing problem, in this study, a form of discrete split deliveries was designed in which the customer demand can be split only by backpack. A double-objective mathematical model and the corresponding adaptive tabu search (TS) algorithm were constructed for solving this problem. By embedding the adaptive penalty mechanism, and adopting the random neighborhood selection strategy and reinitialization principle, the global optimization ability of the new algorithm was enhanced. Comparisons with the results in the literature show the effectiveness of the proposed algorithm. The proposed method can save the costs of low-carbon logistics and reduce carbon emissions, which is conducive to the sustainable development of low-carbon logistics.

A Multi-Vehicles, Wireless Testbed for Networked Control, Communications and Computing

Science.gov (United States)

Murray, Richard; Doyle, John; Effros, Michelle; Hickey, Jason; Low, Steven

2002-03-01

We have constructed a testbed consisting of 4 mobile vehicles (with 4 additional vehicles being completed), each with embedded computing and communications capability for use in testing new approaches for command and control across dynamic networks. The system is being used or is planned to be used for testing of a variety of communications-related technologies, including distributed command and control algorithms, dynamically reconfigurable network topologies, source coding for real-time transmission of data in lossy environments, and multi-network communications. A unique feature of the testbed is the use of vehicles that have second order dynamics. Requiring real-time feedback algorithms to stabilize the system while performing cooperative tasks. The testbed was constructed in the Caltech Vehicles Laboratory and consists of individual vehicles with PC-based computation and controls, and multiple communications devices (802.11 wireless Ethernet, Bluetooth, and infrared). The vehicles are freely moving, wheeled platforms propelled by high performance dotted fairs. The room contains an access points for an 802.11 network, overhead visual sensing (to allow emulation of CI'S signal processing), a centralized computer for emulating certain distributed computations, and network gateways to control and manipulate communications traffic.

Capacitated arc routing problem and its extensions in waste collection

International Nuclear Information System (INIS)

Fadzli, Mohammad; Najwa, Nurul; Luis, Martino

2015-01-01

Capacitated arc routing problem (CARP) is the youngest generation of graph theory that focuses on solving the edge/arc routing for optimality. Since many years, operational research devoted to CARP counterpart, known as vehicle routing problem (VRP), which does not fit to several real cases such like waste collection problem and road maintenance. In this paper, we highlighted several extensions of capacitated arc routing problem (CARP) that represents the real-life problem of vehicle operation in waste collection. By purpose, CARP is designed to find a set of routes for vehicles that satisfies all pre-setting constraints in such that all vehicles must start and end at a depot, service a set of demands on edges (or arcs) exactly once without exceeding the capacity, thus the total fleet cost is minimized. We also addressed the differentiation between CARP and VRP in waste collection. Several issues have been discussed including stochastic demands and time window problems in order to show the complexity and importance of CARP in the related industry. A mathematical model of CARP and its new version is presented by considering several factors such like delivery cost, lateness penalty and delivery time

Capacitated arc routing problem and its extensions in waste collection

Energy Technology Data Exchange (ETDEWEB)

Fadzli, Mohammad; Najwa, Nurul [Institut Matematik Kejuruteraan, Universiti Malaysia Perlis, Kampus Pauh Putra, 02600 Arau, Perlis (Malaysia); Luis, Martino [Othman Yeop Abdullah Graduate School of Business, Universiti Utara Malaysia, 06010 Sintok, Kedah (Malaysia)

2015-05-15

Capacitated arc routing problem (CARP) is the youngest generation of graph theory that focuses on solving the edge/arc routing for optimality. Since many years, operational research devoted to CARP counterpart, known as vehicle routing problem (VRP), which does not fit to several real cases such like waste collection problem and road maintenance. In this paper, we highlighted several extensions of capacitated arc routing problem (CARP) that represents the real-life problem of vehicle operation in waste collection. By purpose, CARP is designed to find a set of routes for vehicles that satisfies all pre-setting constraints in such that all vehicles must start and end at a depot, service a set of demands on edges (or arcs) exactly once without exceeding the capacity, thus the total fleet cost is minimized. We also addressed the differentiation between CARP and VRP in waste collection. Several issues have been discussed including stochastic demands and time window problems in order to show the complexity and importance of CARP in the related industry. A mathematical model of CARP and its new version is presented by considering several factors such like delivery cost, lateness penalty and delivery time.

Subset-row inequalities applied to the vehicle routing problem with time windows

DEFF Research Database (Denmark)

Jepsen, Mads Kehlet; Petersen, Bjørn; Spoorendonk, Simon

2008-01-01

constraints as the pricing problem. We introduce the subset-row inequalities, which are Chvatal-Gomory rank-1 cuts based on a subset of the constraints in the master problem. Applying a subset-row inequality in the master problem increases the complexity of the label-setting algorithm used to solve......This paper presents a branch-and-cut-and-price algorithm for the vehicle-routing problem with time windows. The standard Dantzig-Wolfe decomposition of the arc flow formulation leads to a set-partitioning problem as the master problem and an elementary shortest-path problem with resource...... the pricing problem because an additional resource is added for each inequality. We propose a modified dominance criterion that makes it possible to dominate more labels by exploiting the step-like structure of the objective function of the pricing problem. Computational experiments have been performed...

A Novel Discrete Differential Evolution Algorithm for the Vehicle Routing Problem in B2C E-Commerce

Science.gov (United States)

Xia, Chao; Sheng, Ying; Jiang, Zhong-Zhong; Tan, Chunqiao; Huang, Min; He, Yuanjian

2015-12-01

In this paper, a novel discrete differential evolution (DDE) algorithm is proposed to solve the vehicle routing problems (VRP) in B2C e-commerce, in which VRP is modeled by the incomplete graph based on the actual urban road system. First, a variant of classical VRP is described and a mathematical programming model for the variant is given. Second, the DDE is presented, where individuals are represented as the sequential encoding scheme, and a novel reparation operator is employed to repair the infeasible solutions. Furthermore, a FLOYD operator for dealing with the shortest route is embedded in the proposed DDE. Finally, an extensive computational study is carried out in comparison with the predatory search algorithm and genetic algorithm, and the results show that the proposed DDE is an effective algorithm for VRP in B2C e-commerce.

mDARAL: A Multi-Radio Version for the DARAL Routing Algorithm.

Science.gov (United States)

Estévez, Francisco José; Castillo-Secilla, José María; González, Jesús; Olivares, Joaquín; Glösekötter, Peter

2017-02-09

Smart Cities are called to change the daily life of human beings. This concept permits improving the efficiency of our cities in several areas such as the use of water, energy consumption, waste treatment, and mobility both for people as well as vehicles throughout the city. This represents an interconnected scenario in which thousands of embedded devices need to work in a collaborative way both for sensing and modifying the environment properly. Under this scenario, the majority of devices will use wireless protocols for communicating among them, representing a challenge for optimizing the use of the electromagnetic spectrum. When the density of deployed nodes increases, the competition for using the physical medium becomes harder and, in consequence, traffic collisions will be higher, affecting data-rates in the communication process. This work presents mDARAL , a multi-radio routing algorithm based on the Dynamic and Adaptive Radio Algorithm ( DARAL ), which has the capability of isolating groups of nodes into sub-networks. The nodes of each sub-network will communicate among them using a dedicated radio frequency, thus isolating the use of the radio channel to a reduced number of nodes. Each sub-network will have a master node with two physical radios, one for communicating with its neighbours and the other for being the contact point among its group and other sub-networks. The communication among sub-networks is done through master nodes in a dedicated radio frequency. The algorithm works to maximize the overall performance of the network through the distribution of the traffic messages into unoccupied frequencies. The obtained results show that mDARAL achieves great improvement in terms of the number of control messages necessary to connect a node to the network, convergence time and energy consumption during the connection phase compared to DARAL .

mDARAL: A Multi-Radio Version for the DARAL Routing Algorithm

Directory of Open Access Journals (Sweden)

Francisco José Estévez

2017-02-01

Full Text Available Smart Cities are called to change the daily life of human beings. This concept permits improving the efficiency of our cities in several areas such as the use of water, energy consumption, waste treatment, and mobility both for people as well as vehicles throughout the city. This represents an interconnected scenario in which thousands of embedded devices need to work in a collaborative way both for sensing and modifying the environment properly. Under this scenario, the majority of devices will use wireless protocols for communicating among them, representing a challenge for optimizing the use of the electromagnetic spectrum. When the density of deployed nodes increases, the competition for using the physical medium becomes harder and, in consequence, traffic collisions will be higher, affecting data-rates in the communication process. This work presents mDARAL, a multi-radio routing algorithm based on the Dynamic and Adaptive Radio Algorithm (DARAL, which has the capability of isolating groups of nodes into sub-networks. The nodes of each sub-network will communicate among them using a dedicated radio frequency, thus isolating the use of the radio channel to a reduced number of nodes. Each sub-network will have a master node with two physical radios, one for communicating with its neighbours and the other for being the contact point among its group and other sub-networks. The communication among sub-networks is done through master nodes in a dedicated radio frequency. The algorithm works to maximize the overall performance of the network through the distribution of the traffic messages into unoccupied frequencies. The obtained results show that mDARAL achieves great improvement in terms of the number of control messages necessary to connect a node to the network, convergence time and energy consumption during the connection phase compared to DARAL.

An adversarial queueing model for online server routing

NARCIS (Netherlands)

Bonifaci, V.

2007-01-01

In an online server routing problem, a vehicle or server moves in a network in order to process incoming requests at the nodes. Online server routing problems have been thoroughly studied using competitive analysis. We propose a new model for online server routing, based on adversarial queueing

On Optimizing Steering Performance of Multi-axle Vehicle Based on Driving Force Control

Directory of Open Access Journals (Sweden)

Wu Zhicheng

2017-01-01

Full Text Available The steering performance of multi-axle vehicle with independent driving system is affected by the distribution of the wheel driving force. A nonlinear vehicle dynamics model including magic formula tire model for describing 11 DoF four-axle vehicle with dual-front-axle-steering (DFAS system was presented. The influence of different driving force distribution scheme on the steering performance of the vehicle was analyzed. A control strategy for improving the steady response and transient response of the vehicle steering is proposed. The results show: For the steady response, setting different drive force for internal and external wheels according to the actual steering characteristics of the vehicle can effectively improve its steering characteristics; For the transient response, adopting the zero sideslip angle control strategy and using the PID control algorithm to control the driving force of the outside wheel of tear-two-axle, under angle step input, the vehicle sideslip angle can quickly stabilize to 0 and yaw rate also significantly decreases.

Satellite network robust QoS-aware routing

CERN Document Server

Long, Fei

2014-01-01

Satellite Network Robust QoS-aware Routing presents a novel routing strategy for satellite networks. This strategy is useful for the design of multi-layered satellite networks as it can greatly reduce the number of time slots in one system cycle. The traffic prediction and engineering approaches make the system robust so that the traffic spikes can be handled effectively. The multi-QoS optimization routing algorithm can satisfy various potential user requirements. Clear and sufficient illustrations are also presented in the book. As the chapters cover the above topics independently, readers from different research backgrounds in constellation design, multi-QoS routing, and traffic engineering can benefit from the book.   Fei Long is a senior engineer at Beijing R&D Center of 54th Research Institute of China Electronics Technology Group Corporation.

A hybrid multi-objective imperialist competitive algorithm and Monte Carlo method for robust safety design of a rail vehicle

Science.gov (United States)

Nejlaoui, Mohamed; Houidi, Ajmi; Affi, Zouhaier; Romdhane, Lotfi

2017-10-01

This paper deals with the robust safety design optimization of a rail vehicle system moving in short radius curved tracks. A combined multi-objective imperialist competitive algorithm and Monte Carlo method is developed and used for the robust multi-objective optimization of the rail vehicle system. This robust optimization of rail vehicle safety considers simultaneously the derailment angle and its standard deviation where the design parameters uncertainties are considered. The obtained results showed that the robust design reduces significantly the sensitivity of the rail vehicle safety to the design parameters uncertainties compared to the determinist one and to the literature results.

A multi-body vehicle for moving inside cluttered nuclear environment

International Nuclear Information System (INIS)

Littmann, F.; Chameaud, H.

1994-01-01

The paper presents the result of the TALOS (Technologies for Advanced locomotion Systems) programme. The general aim of the TALOS was to prove the feasibility of multi-body articulated vehicles for intervention missions in nuclear plant were high payload volume and mass are required, combined with great geometrical and obstacles constraints. This programme was based on one hand on the TLV (Train Like Vehicle) concept, developed by CEA ( Atomic Energy Commission) and on the other hand on the KfK experience on locomotion. The main difficulties of this programme were to find the mechanical linkage concept and the locomotion concept, and also to build an integrated mockup with linkage and locomotion concepts. (TEC). 4 refs., 5 figs

A multi-body vehicle for moving inside cluttered nuclear environment

Energy Technology Data Exchange (ETDEWEB)

Littmann, F.; Chameaud, H. [CEA Centre d`Etudes de Saclay, 91 - Gif-sur-Yvette (France). Dept. des Procedes et Systemes Avances; Dorn, J. [Kernforschungszentrum Karlsruhe GmbH (Germany)

1994-12-31

The paper presents the result of the TALOS (Technologies for Advanced locomotion Systems) programme. The general aim of the TALOS was to prove the feasibility of multi-body articulated vehicles for intervention missions in nuclear plant were high payload volume and mass are required, combined with great geometrical and obstacles constraints. This programme was based on one hand on the TLV (Train Like Vehicle) concept, developed by CEA ( Atomic Energy Commission) and on the other hand on the KfK experience on locomotion. The main difficulties of this programme were to find the mechanical linkage concept and the locomotion concept, and also to build an integrated mockup with linkage and locomotion concepts. (TEC). 4 refs., 5 figs.

Interface Assignment-Based AODV Routing Protocol to Improve Reliability in Multi-Interface Multichannel Wireless Mesh Networks

Directory of Open Access Journals (Sweden)

Won-Suk Kim

2015-01-01

Full Text Available The utilization of wireless mesh networks (WMNs has greatly increased, and the multi-interface multichannel (MIMC technic has been widely used for the backbone network. Unfortunately, the ad hoc on-demand distance vector (AODV routing protocol defined in the IEEE 802.11s standard was designed for WMNs using the single-interface single-channel technic. So, we define a problem that happens when the legacy AODV is used in MIMC WMNs and propose an interface assignment-based AODV (IA-AODV in order to resolve that problem. IA-AODV, which is based on multitarget path request, consists of the PREQ prediction scheme, the PREQ loss recovery scheme, and the PREQ sender assignment scheme. A detailed operation according to various network conditions and services is introduced, and the routing efficiency and network reliability of a network using IA-AODV are analyzed over the presented system model. Finally, after a real-world test-bed for MIMC WMNs using the IA-AODV routing protocol is implemented, the various indicators of the network are evaluated through experiments. When the proposed routing protocol is compared with the existing AODV routing protocol, it performs the path update using only 14.33% of the management frames, completely removes the routing malfunction, and reduces the UDP packet loss ratio by 0.0012%.

Impact Foam Testing for Multi-Mission Earth Entry Vehicle Applications

Science.gov (United States)

Glaab, Louis J.; Agrawal, Paul; Hawbaker, James

2013-01-01

Multi-Mission Earth Entry Vehicles (MMEEVs) are blunt-body vehicles designed with the purpose of transporting payloads from outer space to the surface of the Earth. To achieve high-reliability and minimum weight, MMEEVs avoid use of limited-reliability systems, such as parachutes and retro-rockets, instead using built-in impact attenuators to absorb energy remaining at impact to meet landing loads requirements. The Multi-Mission Systems Analysis for Planetary Entry (M-SAPE) parametric design tool is used to facilitate the design of MMEEVs and develop the trade space. Testing was conducted to characterize the material properties of several candidate impact foam attenuators to enhance M-SAPE analysis. In the current effort, two different Rohacell foams were tested to determine their thermal conductivity in support of MMEEV design applications. These applications include thermal insulation during atmospheric entry, impact attenuation, and post-impact thermal insulation in support of thermal soak analysis. Results indicate that for these closed-cell foams, the effect of impact is limited on thermal conductivity due to the venting of the virgin material gas and subsequent ambient air replacement. Results also indicate that the effect of foam temperature is significant compared to data suggested by manufacturer's specifications.

Real-Time Vehicle Routing for Repairing Damaged Infrastructures Due to Natural Disasters

Directory of Open Access Journals (Sweden)

Huey-Kuo Chen

2011-01-01

Full Text Available We address the task of repairing damaged infrastructures as a series of multidepot vehicle-routing problems with time windows in a time-rolling frame. The network size of the tackled problems changes from time to time, as new disaster nodes will be added to and serviced disaster nodes will be deleted from the current network. In addition, an inaccessible disaster node would become accessible when one of its adjacent disaster nodes has been repaired. By the “take-and-conquer” strategy, the repair sequence of the disaster nodes in the affected area can be suitably scheduled. Thirteen instances were tested with our proposed heuristic, that is, Chen et al.'s approach. For comparison, Hsueh et al.'s approach (2008 with necessary modification was also tested. The results show that Chen et al.'s approach performs slightly better for larger size networks in terms of objective value.

Underwater Multi-Vehicle Trajectory Alignment and Mapping Using Acoustic and Optical Constraints

Directory of Open Access Journals (Sweden)

Ricard Campos

2016-03-01

Full Text Available Multi-robot formations are an important advance in recent robotic developments, as they allow a group of robots to merge their capacities and perform surveys in a more convenient way. With the aim of keeping the costs and acoustic communications to a minimum, cooperative navigation of multiple underwater vehicles is usually performed at the control level. In order to maintain the desired formation, individual robots just react to simple control directives extracted from range measurements or ultra-short baseline (USBL systems. Thus, the robots are unaware of their global positioning, which presents a problem for the further processing of the collected data. The aim of this paper is two-fold. First, we present a global alignment method to correct the dead reckoning trajectories of multiple vehicles to resemble the paths followed during the mission using the acoustic messages passed between vehicles. Second, we focus on the optical mapping application of these types of formations and extend the optimization framework to allow for multi-vehicle geo-referenced optical 3D mapping using monocular cameras. The inclusion of optical constraints is not performed using the common bundle adjustment techniques, but in a form improving the computational efficiency of the resulting optimization problem and presenting a generic process to fuse optical reconstructions with navigation data. We show the performance of the proposed method on real datasets collected within the Morph EU-FP7 project.

A proposal to improve e-waste collection efficiency in urban mining: Container loading and vehicle routing problems - A case study of Poland.

Science.gov (United States)

Nowakowski, Piotr

2017-02-01

Waste electrical and electronic equipment (WEEE), also known as e-waste, is one of the most important waste streams with high recycling potential. Materials used in these products are valuable, but some of them are hazardous. The urban mining approach attempts to recycle as many materials as possible, so efficiency in collection is vital. There are two main methods used to collect WEEE: stationary and mobile, each with different variants. The responsibility of WEEE organizations and waste collection companies is to assure all resources required for these activities - bins, containers, collection vehicles and staff - are available, taking into account cost minimization. Therefore, it is necessary to correctly determine the capacity of containers and number of collection vehicles for an area where WEEE need to be collected. There are two main problems encountered in collection, storage and transportation of WEEE: container loading problems and vehicle routing problems. In this study, an adaptation of these two models for packing and collecting WEEE is proposed, along with a practical implementation plan designed to be useful for collection companies' guidelines for container loading and route optimization. The solutions are presented in the case studies of real-world conditions for WEEE collection companies in Poland. Copyright © 2016 Elsevier Ltd. All rights reserved.

Multi-Periodic Photonic Crystal Out-Coupling Layers for Flexible OLEDs

DEFF Research Database (Denmark)

Kluge, Christian; Pradana, Arfat; Adam, Jost

2014-01-01

Waveguide mode extraction with multi-periodic photonic crystals is studied in experiment and finite-difference time-domain (FDTD) simulations. Flexible nanostructured organic light-emitting diodes (OLEDs) are fabricated by UV nanoimprint lithography.......Waveguide mode extraction with multi-periodic photonic crystals is studied in experiment and finite-difference time-domain (FDTD) simulations. Flexible nanostructured organic light-emitting diodes (OLEDs) are fabricated by UV nanoimprint lithography....

Using the hybrid fuzzy goal programming model and hybrid genetic algorithm to solve a multi-objective location routing problem for infectious waste disposaL

Energy Technology Data Exchange (ETDEWEB)

Wichapa, Narong; Khokhajaikiat, Porntep

2017-07-01

Disposal of infectious waste remains one of the most serious problems in the social and environmental domains of almost every nation. Selection of new suitable locations and finding the optimal set of transport routes to transport infectious waste, namely location routing problem for infectious waste disposal, is one of the major problems in hazardous waste management. Design/methodology/approach: Due to the complexity of this problem, location routing problem for a case study, forty hospitals and three candidate municipalities in sub-Northeastern Thailand, was divided into two phases. The first phase is to choose suitable municipalities using hybrid fuzzy goal programming model which hybridizes the fuzzy analytic hierarchy process and fuzzy goal programming. The second phase is to find the optimal routes for each selected municipality using hybrid genetic algorithm which hybridizes the genetic algorithm and local searches including 2-Opt-move, Insertion-move and ?-interchange-move. Findings: The results indicate that the hybrid fuzzy goal programming model can guide the selection of new suitable municipalities, and the hybrid genetic algorithm can provide the optimal routes for a fleet of vehicles effectively. Originality/value: The novelty of the proposed methodologies, hybrid fuzzy goal programming model, is the simultaneous combination of both intangible and tangible factors in order to choose new suitable locations, and the hybrid genetic algorithm can be used to determine the optimal routes which provide a minimum number of vehicles and minimum transportation cost under the actual situation, efficiently.

Using the hybrid fuzzy goal programming model and hybrid genetic algorithm to solve a multi-objective location routing problem for infectious waste disposaL

International Nuclear Information System (INIS)

Wichapa, Narong; Khokhajaikiat, Porntep

2017-01-01

Disposal of infectious waste remains one of the most serious problems in the social and environmental domains of almost every nation. Selection of new suitable locations and finding the optimal set of transport routes to transport infectious waste, namely location routing problem for infectious waste disposal, is one of the major problems in hazardous waste management. Design/methodology/approach: Due to the complexity of this problem, location routing problem for a case study, forty hospitals and three candidate municipalities in sub-Northeastern Thailand, was divided into two phases. The first phase is to choose suitable municipalities using hybrid fuzzy goal programming model which hybridizes the fuzzy analytic hierarchy process and fuzzy goal programming. The second phase is to find the optimal routes for each selected municipality using hybrid genetic algorithm which hybridizes the genetic algorithm and local searches including 2-Opt-move, Insertion-move and ?-interchange-move. Findings: The results indicate that the hybrid fuzzy goal programming model can guide the selection of new suitable municipalities, and the hybrid genetic algorithm can provide the optimal routes for a fleet of vehicles effectively. Originality/value: The novelty of the proposed methodologies, hybrid fuzzy goal programming model, is the simultaneous combination of both intangible and tangible factors in order to choose new suitable locations, and the hybrid genetic algorithm can be used to determine the optimal routes which provide a minimum number of vehicles and minimum transportation cost under the actual situation, efficiently.

Multi-Sensor Information Fusion for Optimizing Electric Bicycle Routes Using a Swarm Intelligence Algorithm

Directory of Open Access Journals (Sweden)

Daniel H. De La Iglesia

2017-10-01

Full Text Available The use of electric bikes (e-bikes has grown in popularity, especially in large cities where overcrowding and traffic congestion are common. This paper proposes an intelligent engine management system for e-bikes which uses the information collected from sensors to optimize battery energy and time. The intelligent engine management system consists of a built-in network of sensors in the e-bike, which is used for multi-sensor data fusion; the collected data is analysed and fused and on the basis of this information the system can provide the user with optimal and personalized assistance. The user is given recommendations related to battery consumption, sensors, and other parameters associated with the route travelled, such as duration, speed, or variation in altitude. To provide a user with these recommendations, artificial neural networks are used to estimate speed and consumption for each of the segments of a route. These estimates are incorporated into evolutionary algorithms in order to make the optimizations. A comparative analysis of the results obtained has been conducted for when routes were travelled with and without the optimization system. From the experiments, it is evident that the use of an engine management system results in significant energy and time savings. Moreover, user satisfaction increases as the level of assistance adapts to user behavior and the characteristics of the route.

Multi-Sensor Information Fusion for Optimizing Electric Bicycle Routes Using a Swarm Intelligence Algorithm

Science.gov (United States)

Villarubia, Gabriel; De Paz, Juan F.; Bajo, Javier

2017-01-01

The use of electric bikes (e-bikes) has grown in popularity, especially in large cities where overcrowding and traffic congestion are common. This paper proposes an intelligent engine management system for e-bikes which uses the information collected from sensors to optimize battery energy and time. The intelligent engine management system consists of a built-in network of sensors in the e-bike, which is used for multi-sensor data fusion; the collected data is analysed and fused and on the basis of this information the system can provide the user with optimal and personalized assistance. The user is given recommendations related to battery consumption, sensors, and other parameters associated with the route travelled, such as duration, speed, or variation in altitude. To provide a user with these recommendations, artificial neural networks are used to estimate speed and consumption for each of the segments of a route. These estimates are incorporated into evolutionary algorithms in order to make the optimizations. A comparative analysis of the results obtained has been conducted for when routes were travelled with and without the optimization system. From the experiments, it is evident that the use of an engine management system results in significant energy and time savings. Moreover, user satisfaction increases as the level of assistance adapts to user behavior and the characteristics of the route. PMID:29088087

Multi-Sensor Information Fusion for Optimizing Electric Bicycle Routes Using a Swarm Intelligence Algorithm.

Science.gov (United States)

De La Iglesia, Daniel H; Villarrubia, Gabriel; De Paz, Juan F; Bajo, Javier

2017-10-31

The use of electric bikes (e-bikes) has grown in popularity, especially in large cities where overcrowding and traffic congestion are common. This paper proposes an intelligent engine management system for e-bikes which uses the information collected from sensors to optimize battery energy and time. The intelligent engine management system consists of a built-in network of sensors in the e-bike, which is used for multi-sensor data fusion; the collected data is analysed and fused and on the basis of this information the system can provide the user with optimal and personalized assistance. The user is given recommendations related to battery consumption, sensors, and other parameters associated with the route travelled, such as duration, speed, or variation in altitude. To provide a user with these recommendations, artificial neural networks are used to estimate speed and consumption for each of the segments of a route. These estimates are incorporated into evolutionary algorithms in order to make the optimizations. A comparative analysis of the results obtained has been conducted for when routes were travelled with and without the optimization system. From the experiments, it is evident that the use of an engine management system results in significant energy and time savings. Moreover, user satisfaction increases as the level of assistance adapts to user behavior and the characteristics of the route.

Period-dependent source rupture behavior of the 2011 Tohoku earthquake estimated by multi period-band Bayesian waveform inversion

Science.gov (United States)

Kubo, H.; Asano, K.; Iwata, T.; Aoi, S.

2014-12-01

Previous studies for the period-dependent source characteristics of the 2011 Tohoku earthquake (e.g., Koper et al., 2011; Lay et al., 2012) were based on the short and long period source models using different method. Kubo et al. (2013) obtained source models of the 2011 Tohoku earthquake using multi period-bands waveform data by a common inversion method and discussed its period-dependent source characteristics. In this study, to achieve more in detail spatiotemporal source rupture behavior of this event, we introduce a new fault surface model having finer sub-fault size and estimate the source models in multi period-bands using a Bayesian inversion method combined with a multi-time-window method. Three components of velocity waveforms at 25 stations of K-NET, KiK-net, and F-net of NIED are used in this analysis. The target period band is 10-100 s. We divide this period band into three period bands (10-25 s, 25-50 s, and 50-100 s) and estimate a kinematic source model in each period band using a Bayesian inversion method with MCMC sampling (e.g., Fukuda & Johnson, 2008; Minson et al., 2013, 2014). The parameterization of spatiotemporal slip distribution follows the multi-time-window method (Hartzell & Heaton, 1983). The Green's functions are calculated by the 3D FDM (GMS; Aoi & Fujiwara, 1999) using a 3D velocity structure model (JIVSM; Koketsu et al., 2012). The assumed fault surface model is based on the Pacific plate boundary of JIVSM and is divided into 384 subfaults of about 16 * 16 km^2. The estimated source models in multi period-bands show the following source image: (1) First deep rupture off Miyagi at 0-60 s toward down-dip mostly radiating relatively short period (10-25 s) seismic waves. (2) Shallow rupture off Miyagi at 45-90 s toward up-dip with long duration radiating long period (50-100 s) seismic wave. (3) Second deep rupture off Miyagi at 60-105 s toward down-dip radiating longer period seismic waves then that of the first deep rupture. (4) Deep

Benefits Analysis of Multi-Center Dynamic Weather Routes

Science.gov (United States)

Sheth, Kapil; McNally, David; Morando, Alexander; Clymer, Alexis; Lock, Jennifer; Petersen, Julien

2014-01-01

Dynamic weather routes are flight plan corrections that can provide airborne flights more than user-specified minutes of flying-time savings, compared to their current flight plan. These routes are computed from the aircraft's current location to a flight plan fix downstream (within a predefined limit region), while avoiding forecasted convective weather regions. The Dynamic Weather Routes automation has been continuously running with live air traffic data for a field evaluation at the American Airlines Integrated Operations Center in Fort Worth, TX since July 31, 2012, where flights within the Fort Worth Air Route Traffic Control Center are evaluated for time savings. This paper extends the methodology to all Centers in United States and presents benefits analysis of Dynamic Weather Routes automation, if it was implemented in multiple airspace Centers individually and concurrently. The current computation of dynamic weather routes requires a limit rectangle so that a downstream capture fix can be selected, preventing very large route changes spanning several Centers. In this paper, first, a method of computing a limit polygon (as opposed to a rectangle used for Fort Worth Center) is described for each of the 20 Centers in the National Airspace System. The Future ATM Concepts Evaluation Tool, a nationwide simulation and analysis tool, is used for this purpose. After a comparison of results with the Center-based Dynamic Weather Routes automation in Fort Worth Center, results are presented for 11 Centers in the contiguous United States. These Centers are generally most impacted by convective weather. A breakdown of individual Center and airline savings is presented and the results indicate an overall average savings of about 10 minutes of flying time are obtained per flight.

A Time-Slotted On-Demand Routing Protocol for Mobile Ad Hoc Unmanned Vehicle Systems

Energy Technology Data Exchange (ETDEWEB)

Hope Forsmann; Robert Hiromoto; John Svoboda

2007-04-01

The popularity of UAVs has increased dramatically because of their successful deployment in military operations, their ability to preserve human life, and the continual improvements in wireless communication that serves to increase their capabilities. We believe the usefulness of UAVs would be dramatically increased if formation flight were added to the list of capabilities. Currently, sustained formation flight with a cluster of UAVs has only been achieved with two nodes by the Multi-UAV Testbed at the Massachusetts Institute of Technology. (Park, 2004) Formation flight is a complex operation requiring the ability to adjust the flight patterns on the fly and correct for wind gusts, terrain, and differences in node equipment. All of which increases the amount of inner node communication. Since one of the problems with MANET communication is network congestion, we believe a first step towards formation flight can be made through improved inner node communication. We have investigated current communication routing protocols and developed an altered hybrid routing protocol in order to provide communication with less network congestion.

Neighboring and Connectivity-Aware Routing in VANETs

Directory of Open Access Journals (Sweden)

Huma Ghafoor

2014-01-01

Full Text Available A novel position-based routing protocol anchor-based connectivity-aware routing (ACAR for vehicular ad hoc networks (VANETs is proposed in this paper to ensure connectivity of routes with more successfully delivered packets. Both buses and cars are considered as vehicular nodes running in both clockwise and anticlockwise directions in a city scenario. Both directions are taken into account for faster communication. ACAR is a hybrid protocol, using both the greedy forwarding approach and the store-carry-and-forward approach to minimize the packet drop rate on the basis of certain assumptions. Our solution to situations that occur when the network is sparse and when any (source or intermediate node has left its initial position makes this protocol different from those existing in the literature. We consider only vehicle-to-vehicle (V2V communication in which both the source and destination nodes are moving vehicles. Also, no road-side units are considered. Finally, we compare our protocol with A-STAR (a plausible connectivity-aware routing protocol for city environments, and simulation results in NS-2 show improvement in the number of packets delivered to the destination using fewer hops. Also, we show that ACAR has more successfully-delivered long-distance packets with reasonable packet delay than A-STAR.

Vehicle Routing with Three-dimensional Container Loading Constraints—Comparison of Nested and Joint Algorithms

Science.gov (United States)

Koloch, Grzegorz; Kaminski, Bogumil

2010-10-01

In the paper we examine a modification of the classical Vehicle Routing Problem (VRP) in which shapes of transported cargo are accounted for. This problem, known as a three-dimensional VRP with loading constraints (3D-VRP), is appropriate when transported commodities are not perfectly divisible, but they have fixed and heterogeneous dimensions. In the paper restrictions on allowable cargo positionings are also considered. These restrictions are derived from business practice and they extended the baseline 3D-VRP formulation as considered by Koloch and Kaminski (2010). In particular, we investigate how additional restrictions influence relative performance of two proposed optimization algorithms: the nested and the joint one. Performance of both methods is compared on artificial problems and on a big-scale real life case study.

A lower bound for the node, edge, and arc routing problem

DEFF Research Database (Denmark)

Bach, Lukas; Hasle, Geir; Wøhlk, Sanne

2013-01-01

The Node, Edge, and Arc Routing Problem (NEARP) was defined by Prins and Bouchenoua in 2004, although similar problems have been studied before. This problem, also called the Mixed Capacitated General Routing Problem (MCGRP), generalizes the classical Capacitated Vehicle Routing Problem (CVRP......), the Capacitated Arc Routing Problem (CARP), and the General Routing Problem. It captures important aspects of real-life routing problems that were not adequately modeled in previous Vehicle Routing Problem (VRP) variants. The authors also proposed a memetic algorithm procedure and defined a set of test instances...... called the CBMix benchmark. The NEARP definition and investigation contribute to the development of rich VRPs. In this paper we present the first lower bound procedure for the NEARP. It is a further development of lower bounds for the CARP. We also define two novel sets of test instances to complement...

Centralized Routing and Scheduling Using Multi-Channel System Single Transceiver in 802.16d

Science.gov (United States)

Al-Hemyari, A.; Noordin, N. K.; Ng, Chee Kyun; Ismail, A.; Khatun, S.

This paper proposes a cross-layer optimized strategy that reduces the effect of interferences from neighboring nodes within a mesh networks. This cross-layer design relies on the routing information in network layer and the scheduling table in medium access control (MAC) layer. A proposed routing algorithm in network layer is exploited to find the best route for all subscriber stations (SS). Also, a proposed centralized scheduling algorithm in MAC layer is exploited to assign a time slot for each possible node transmission. The cross-layer optimized strategy is using multi-channel single transceiver and single channel single transceiver systems for WiMAX mesh networks (WMNs). Each node in WMN has a transceiver that can be tuned to any available channel for eliminating the secondary interference. Among the considered parameters in the performance analysis are interference from the neighboring nodes, hop count to the base station (BS), number of children per node, slot reuse, load balancing, quality of services (QoS), and node identifier (ID). Results show that the proposed algorithms significantly improve the system performance in terms of length of scheduling, channel utilization ratio (CUR), system throughput, and average end to end transmission delay.

36 CFR 4.10 - Travel on park roads and designated routes.

Science.gov (United States)

2010-07-01

... 36 Parks, Forests, and Public Property 1 2010-07-01 2010-07-01 false Travel on park roads and... THE INTERIOR VEHICLES AND TRAFFIC SAFETY § 4.10 Travel on park roads and designated routes. (a) Operating a motor vehicle is prohibited except on park roads, in parking areas and on routes and areas...

Optimization of Parking Public Transport Vehicles in Ostrava

Directory of Open Access Journals (Sweden)

Dušan Teichmann

2015-03-01

Full Text Available A typical trait of public transport is a spatially scattered demand. A route net that is operated by a carrier (or several carriers has to be adapted to the demand. Public transport vehicles that are not used during a period of a day are usually parked in defined parking lots that have a given capacity. When the vehicle goes from the place where its schedule ends (usually a terminus of the last connection served by the vehicle to the place where the vehicle should be parked, a non-productive journey occurs. The same occurs at the beginning of the vehicle schedule as well. The main goal of the paper is to present a mathematical model that enables minimization of the total length of all the non-productive journeys. Functionality of the proposed mathematical model was tested in the conditions of a real bus public transport network.

Indoor Surveillance Security Robot with a Self-Propelled Patrolling Vehicle

Directory of Open Access Journals (Sweden)

Hou-Tsan Lee

2011-01-01

Full Text Available Self-propelled patrolling vehicles can patrol periodically in the designed area to ensure the safety like men do. The proposed vehicle cannot only save manpower, but also ensure the performance without mistakes caused by man. It is different from the traditional patrolling system which is limited by the manpower and the fixed camera positions. To improve such situation, this paper proposes a self-propelled patrolling vehicle which can move automatically to a wider range and record the monitored image by IPCAM within a predefined patrolling route. Besides, the user can use the mobile device or website to connect to the vehicle at anytime and anywhere and control it to move to the position to get the indoor image user wants. The position of self-propelled vehicles can be detected by the RFID reader as a feedback and be shown on the PC screen and smart phone. The recorded images can be also transmitted back to the server via WiFi system for face tracking and discriminating analysis. On the other hand, the self-propelled vehicle patrolling routes can be modified by the Android smart-phone remote-control module. When some defined events occur, the build-in MSN module will notice users by sending messages to PC and smart phone. Experimental results are given in the paper to validate its performance.

Reserving Charging Decision-Making Model and Route Plan for Electric Vehicles Considering Information of Traffic and Charging Station

Directory of Open Access Journals (Sweden)

Haoming Liu

2018-04-01

Full Text Available With the advance of battery energy technology, electric vehicles (EV are catching more and more attention. One of the influencing factors of electric vehicles large-scale application is the availability of charging stations and convenience of charging. It is important to investigate how to make reserving charging strategies and ensure electric vehicles are charged with shorter time and lower charging expense whenever charging request is proposed. This paper proposes a reserving charging decision-making model for electric vehicles that move to certain destinations and need charging services in consideration of traffic conditions and available charging resources at the charging stations. Besides, the interactive mechanism is described to show how the reserving charging system works, as well as the rolling records-based credit mechanism where extra charges from EV is considered to hedge default behavior. With the objectives of minimizing driving time and minimizing charging expenses, an optimization model with two objective functions is formulated. Then the optimizations are solved by a K shortest paths algorithm based on a weighted directed graph, where the time and distance factors are respectively treated as weights of corresponding edges of transportation networks. Case studies show the effectiveness and validity of the proposed route plan and reserving charging decision-making model.

36 CFR 1004.10 - Travel on Presidio Trust roads and designated routes.

Science.gov (United States)

2010-07-01

... roads and designated routes. 1004.10 Section 1004.10 Parks, Forests, and Public Property PRESIDIO TRUST VEHICLES AND TRAFFIC SAFETY § 1004.10 Travel on Presidio Trust roads and designated routes. (a) Operating a motor vehicle is prohibited except on Presidio Trust roads and in parking areas. (b) The following are...

Modelo matemático Two-echelon Capacitated Vehicle Routing Problem para a logística de distribuição de encomendas

Directory of Open Access Journals (Sweden)

Karina Pedrini Fraga

2016-12-01

Full Text Available Many cities are facing difficulties in urban mobility and therefore are imposing restrictions on the movement of larger trucks. Thus, logistics companies developed a two level logistics strategy based on Urban Distribution Centers (CDU that receives larger trucks and split the cargo to put in small trucks to distribute to customers. To support this type of logistics planning, this paper presents an adaptation of a mathematical model based on the Two-echelon capacitated Vehicle Routing Problem (2E-CVRP to plan the routes from the central depot to the satelites and from these to the clients. The model was applied to the logistics of Correios in the metropolitan area of the Espírito Santo, Brazil, and instances with up to 4 CDU and 25 clients were tested using CPLEX solver 12.6 obtaining routes for deliveries at both levels.

Multi-Periodic Photonic Hyper-Crystals: Volume Plasmon Polaritons and the Purcell Effect

DEFF Research Database (Denmark)

Babicheva, Viktoriia; Iorsh, I. V.; Orlov, A. A.

2014-01-01

We theoretically demonstrate superior degree of control over volume plasmon polariton propagation and the Purcell effect in multi-period (4-layer unit cell) plasmonic multilayers, which can be viewed as multiscale hyperbolic metamaterials or multi-periodic photonic hyper-crystals. © 2014 OSA....

Multi-Objective Trajectory Optimization of a Hypersonic Reconnaissance Vehicle with Temperature Constraints

Science.gov (United States)

Masternak, Tadeusz J.

This research determines temperature-constrained optimal trajectories for a scramjet-based hypersonic reconnaissance vehicle by developing an optimal control formulation and solving it using a variable order Gauss-Radau quadrature collocation method with a Non-Linear Programming (NLP) solver. The vehicle is assumed to be an air-breathing reconnaissance aircraft that has specified takeoff/landing locations, airborne refueling constraints, specified no-fly zones, and specified targets for sensor data collections. A three degree of freedom scramjet aircraft model is adapted from previous work and includes flight dynamics, aerodynamics, and thermal constraints. Vehicle control is accomplished by controlling angle of attack, roll angle, and propellant mass flow rate. This model is incorporated into an optimal control formulation that includes constraints on both the vehicle and mission parameters, such as avoidance of no-fly zones and coverage of high-value targets. To solve the optimal control formulation, a MATLAB-based package called General Pseudospectral Optimal Control Software (GPOPS-II) is used, which transcribes continuous time optimal control problems into an NLP problem. In addition, since a mission profile can have varying vehicle dynamics and en-route imposed constraints, the optimal control problem formulation can be broken up into several "phases" with differing dynamics and/or varying initial/final constraints. Optimal trajectories are developed using several different performance costs in the optimal control formulation: minimum time, minimum time with control penalties, and maximum range. The resulting analysis demonstrates that optimal trajectories that meet specified mission parameters and constraints can be quickly determined and used for larger-scale operational and campaign planning and execution.

Modeling and Optimization of Inventory-Distribution Routing Problem for Agriculture Products Supply Chain

Directory of Open Access Journals (Sweden)

Li Liao

2013-01-01

Full Text Available Mathematical models of inventory-distribution routing problem for two-echelon agriculture products distribution network are established, which are based on two management modes, franchise chain and regular chain, one-to-many, interval periodic order, demand depending on inventory, deteriorating treatment cost of agriculture products, start-up costs of vehicles and so forth. Then, a heuristic adaptive genetic algorithm is presented for the model of franchise chain. For the regular chain model, a two-layer genetic algorithm based on oddment modification is proposed, in which the upper layer is to determine the distribution period and quantity and the lower layer is to seek the optimal order cycle, quantity, distribution routes, and the rational oddment modification number for the distributor. By simulation experiments, the validity of the algorithms is demonstrated, and the two management modes are compared.

A class of multi-period semi-variance portfolio for petroleum exploration and development

Science.gov (United States)

Guo, Qiulin; Li, Jianzhong; Zou, Caineng; Guo, Yujuan; Yan, Wei

2012-10-01

Variance is substituted by semi-variance in Markowitz's portfolio selection model. For dynamic valuation on exploration and development projects, one period portfolio selection is extended to multi-period. In this article, a class of multi-period semi-variance exploration and development portfolio model is formulated originally. Besides, a hybrid genetic algorithm, which makes use of the position displacement strategy of the particle swarm optimiser as a mutation operation, is applied to solve the multi-period semi-variance model. For this class of portfolio model, numerical results show that the mode is effective and feasible.

Modeling and Optimization of Inventory-Distribution Routing Problem for Agriculture Products Supply Chain

OpenAIRE

Liao, Li; Li, Jianfeng; Wu, Yaohua

2013-01-01

Mathematical models of inventory-distribution routing problem for two-echelon agriculture products distribution network are established, which are based on two management modes, franchise chain and regular chain, one-to-many, interval periodic order, demand depending on inventory, deteriorating treatment cost of agriculture products, start-up costs of vehicles and so forth. Then, a heuristic adaptive genetic algorithm is presented for the model of franchise chain. For the regular chain model,...

An Improved Multi-Objective Programming with Augmented ε-Constraint Method for Hazardous Waste Location-Routing Problems.

Science.gov (United States)

Yu, Hao; Solvang, Wei Deng

2016-05-31

Hazardous waste location-routing problems are of importance due to the potential risk for nearby residents and the environment. In this paper, an improved mathematical formulation is developed based upon a multi-objective mixed integer programming approach. The model aims at assisting decision makers in selecting locations for different facilities including treatment plants, recycling plants and disposal sites, providing appropriate technologies for hazardous waste treatment, and routing transportation. In the model, two critical factors are taken into account: system operating costs and risk imposed on local residents, and a compensation factor is introduced to the risk objective function in order to account for the fact that the risk level imposed by one type of hazardous waste or treatment technology may significantly vary from that of other types. Besides, the policy instruments for promoting waste recycling are considered, and their influence on the costs and risk of hazardous waste management is also discussed. The model is coded and calculated in Lingo optimization solver, and the augmented ε-constraint method is employed to generate the Pareto optimal curve of the multi-objective optimization problem. The trade-off between different objectives is illustrated in the numerical experiment.

An Improved Multi-Objective Programming with Augmented ε-Constraint Method for Hazardous Waste Location-Routing Problems

Directory of Open Access Journals (Sweden)

Hao Yu

2016-05-01

Full Text Available Hazardous waste location-routing problems are of importance due to the potential risk for nearby residents and the environment. In this paper, an improved mathematical formulation is developed based upon a multi-objective mixed integer programming approach. The model aims at assisting decision makers in selecting locations for different facilities including treatment plants, recycling plants and disposal sites, providing appropriate technologies for hazardous waste treatment, and routing transportation. In the model, two critical factors are taken into account: system operating costs and risk imposed on local residents, and a compensation factor is introduced to the risk objective function in order to account for the fact that the risk level imposed by one type of hazardous waste or treatment technology may significantly vary from that of other types. Besides, the policy instruments for promoting waste recycling are considered, and their influence on the costs and risk of hazardous waste management is also discussed. The model is coded and calculated in Lingo optimization solver, and the augmented ε-constraint method is employed to generate the Pareto optimal curve of the multi-objective optimization problem. The trade-off between different objectives is illustrated in the numerical experiment.

Tourism Routes, Local Economic Promotion and Pro-Poor ...

African Journals Online (AJOL)

In southern Africa, there is growing interest in the potential for establishing tourism routes as vehicles for tourism expansion and the promotion of local economic development. This article contributes towards understanding the potential and importance of organising routes for local tourism promotion and economic ...

An Integrated Inventory-Transportation System with Periodic Pick-Ups and Leveled Replenishment

Directory of Open Access Journals (Sweden)

Thomas Volling

2013-11-01

Full Text Available In this paper we develop a combined inventory-transportation system. The general idea is to integrate a simple replenishment policy with a routing component to derive operationally consistent standard routes as a basis for milk run design. The most interesting feature of the approach is that we combine stochastic vehicle routing with a replenishment policy which makes use of inventory to level the variability propagated into transportation operations. To evaluate the approach, we compare its performance with stochastic vehicle routing as well as sequential vehicle routing and replenishment planning. With respect to these approaches, substantial gains are achieved.

Periodic and almost periodic solutions for multi-valued differential equations in Banach spaces

Directory of Open Access Journals (Sweden)

E. Hanebaly

2000-03-01

Full Text Available It is known that for $omega$-periodic differential equations of monotonous type, in uniformly convex Banach spaces, the existence of a bounded solution on ${Bbb R}^+$ is equivalent to the existence of an omega-periodic solution (see Haraux [5] and Hanebaly [7, 10]. It is also known that if the Banach space is strictly convex and the equation is almost periodic and of monotonous type, then the existence of a continuous solution with a precompact range is equivalent to the existence of an almost periodic solution (see Hanebaly [8]. In this note we want to generalize the results above for multi-valued differential equations.

Adaptive powertrain control for plugin hybrid electric vehicles

Science.gov (United States)

Kedar-Dongarkar, Gurunath; Weslati, Feisel

2013-10-15

A powertrain control system for a plugin hybrid electric vehicle. The system comprises an adaptive charge sustaining controller; at least one internal data source connected to the adaptive charge sustaining controller; and a memory connected to the adaptive charge sustaining controller for storing data generated by the at least one internal data source. The adaptive charge sustaining controller is operable to select an operating mode of the vehicle's powertrain along a given route based on programming generated from data stored in the memory associated with that route. Further described is a method of adaptively controlling operation of a plugin hybrid electric vehicle powertrain comprising identifying a route being traveled, activating stored adaptive charge sustaining mode programming for the identified route and controlling operation of the powertrain along the identified route by selecting from a plurality of operational modes based on the stored adaptive charge sustaining mode programming.

Routing and scheduling problems

DEFF Research Database (Denmark)

Reinhardt, Line Blander

couple of decades. To deliver competitive service and price, transportation today needs to be cost effective. A company requiring for things to be shipped will aim at having the freight shipped as cheaply as possible while often satisfying certain time constraints. For the transportation company......, the effectiveness of the network is of importance aiming at satisfying as many costumer demands as possible at a low cost. Routing represent a path between locations such as an origin and destination for the object routed. Sometimes routing has a time dimension as well as the physical paths. This may...... set cost making the cost of the individual vehicle routes inter-dependant. Depending on the problem type, the size of the problems and time available for solving, different solution methods can be applicable. In this thesis both heuristic methods and several exact methods are investigated depending...

Multi-period risk sharing under financial fairness

NARCIS (Netherlands)

Bao, Hailong; Ponds, Eduard; Schumacher, Hans

We work with a multi-period system where a finite number of agents need to share multiple monetary risks. We look for the solutions that are both Pareto efficient utility-wise and financially fair value-wise. A buffer enables the inter-temporal capital transfer. Expected utility is used to evaluate

Multi-Period Risk Sharing under Financial Fairness

NARCIS (Netherlands)

Bao, Hailong; Ponds, Eduard; Schumacher, Hans

2015-01-01

We work with a multi-period system where a finite number of agents need to share multiple monetary risks. We look for the solutions that are both Pareto efficient utility-wise and financially fair value-wise. A buffer enables the inter-temporal capital transfer. Expected utility is used to evaluate

Roteamento de veículos com base em sistemas de informação geográfica Vehicle routing based on geographical information systems

Directory of Open Access Journals (Sweden)

Roberto Diéguez Galvão

1997-08-01

Full Text Available Um algoritmo para roteamento de veículos é integrado a um Sistema de Informação Geográfica, de cuja base de dados obtém as informações necessárias para o roteamento e no qual mostra as rotas resultantes. O algoritmo de roteamento utilizado tem como base a metaheurística de simulated annealing, que apresenta neste caso resultados computacionais de boa qualidade. Descrevemos a interface do algoritmo com um SIG específico e a aplicação do sistema resultante a um programa de entregas simulado, no bairro de Copacabana, no Rio de Janeiro.An algorithm for vehicle routing is embedded into a Geographical Information System (GIS, from the database of which it extracts the information needed for the routing and where it displays the resulting routes. The routing algorithm is a simulated annealing metaheuristic that produces good quality routes in reduced computational times. We describe the embedding of the algorithm into a specific GIS software and the application of the routing system to a simulated delivery schedule in the neighbourhood of Copacabana, in Rio de Janeiro.

Exact method for the vehicle routing problem with mixed linehaul and backhaul customers, heterogeneous fleet, time window and manufacturing capacity

OpenAIRE

Oesterle, Jonathan; Bauernhansl, Thomas

2016-01-01

Due to concerns over food safety, quality, and transparency, the food industry has been challenged to deal with an increased complexity in its logistics and production planning. This complexity is mostly associated to the task of optimally exploring a highly constrained solution space. This paper addresses the problem of designing a set of vehicle routes satisfying the delivery and the collection requirements of a set of geographically scattered linehaul and backhaul customers. Each customer ...

On line routing per mobile phone

DEFF Research Database (Denmark)

Bieding, Thomas; Görtz, Simon; Klose, Andreas

2009-01-01

On-line routing is concerned with building vehicle routes in an ongoing fashion in such a way that customer requests arriving dynamically in time are efficiently and effectively served. An indispensable prerequisite for applying on-line routing methods is mobile communication technology....... Additionally it is of utmost importance that the employed communication system is suitable integrated with the firm’s enterprise application system and business processes. On basis of a case study, we describe in this paper a system that is cheap and easy to implement due to the use of simple mobile phones...

The Effect of Route, Vehicle, and Divided Doses on the Pharmacokinetics of Chlorpyrifos and its Metabolite Trichloropyridinol in Neonatal Sprague-Dawley Rats

Energy Technology Data Exchange (ETDEWEB)

Marty, M. S.; Domoradzki, J. Y.; Hansen, S. C.; Timchalk, Chuck; Bartels, M. J.; Mattsson, Joel L.

2007-12-01

There is a paucity of data on neonatal systemic exposure using different dosing paradigms. Male CD (Sprague-Dawley derived) rats at postnatal day (PND) 5 were dosed with chlorpyrifos (CPF, 1 mg/kg) using different routes of exposure, vehicles, and single vs. divided doses. Blood concentrations of CPF and its primary metabolite, trichloropyridinol (TCP), were measured at multiple times through 24 h. Groups included: single gavage bolus vs. divided gavage doses in corn oil (1 vs 3 times in 24 h), single gavage bolus vs. divided gavage doses in rat milk, and subcutaneous administration in DMSO. These data were compared with lactational exposure of PND 5 pups from dams exposed to CPF in the diet at 5 mg/kg/day for four weeks or published data from dams exposed to daily gavage with CPF at 5 mg/kg/day. Maternal blood CPF levels were an order of magnitude lower from dietary exposure than gavage (1.1 vs 14.8 ng/g), and blood CPF levels in PND 5 pups that nursed dietary-exposed or gavage-exposed dams were below the limit of detection. Single gavage doses of 1 mg/kg CPF in corn oil vehicle in pups resulted in CPF blood levels of 49 ng/g, and in milk vehicle about 9 ng/g. Divided doses led to lower peak CPF levels. A bolus dose of 1 mg/kg CPF in DMSO administered sc appeared to have substantially altered pharmacokinetics from orally administered chlorpyrifos. To be meaningful for risk assessment, neonatal studies require attention to the exposure scenario, since route, vehicle, dose and frequency of administration result in different systemic exposure to the test chemical and its metabolites.

Research on consumable distribution mode of shipbuilder’s shop based on vehicle routing problem

Directory of Open Access Journals (Sweden)

Xiang Su

2017-02-01

Full Text Available A distribution vehicle optimization is established with considerations for the problem of long period of requisition and high shop costs due to the existing consumable requisition mode in shipbuilder’s shops for the requirements of shops for consumables. The shortest traveling distance of distribution vehicles are calculated with the genetic algorithm (GA. Explorations are made into a shop consumable distribution mode for shipbuilders to help them to effectively save their production logistics costs, enhance their internal material management level and provide reference for shipbuilder’s change in traditional ways and realization of just-in-time (JIT production.

A Multi-Attribute Pheromone Ant Secure Routing Algorithm Based on Reputation Value for Sensor Networks

Directory of Open Access Journals (Sweden)

Lin Zhang

2017-03-01

Full Text Available With the development of wireless sensor networks, certain network problems have become more prominent, such as limited node resources, low data transmission security, and short network life cycles. To solve these problems effectively, it is important to design an efficient and trusted secure routing algorithm for wireless sensor networks. Traditional ant-colony optimization algorithms exhibit only local convergence, without considering the residual energy of the nodes and many other problems. This paper introduces a multi-attribute pheromone ant secure routing algorithm based on reputation value (MPASR. This algorithm can reduce the energy consumption of a network and improve the reliability of the nodes’ reputations by filtering nodes with higher coincidence rates and improving the method used to update the nodes’ communication behaviors. At the same time, the node reputation value, the residual node energy and the transmission delay are combined to formulate a synthetic pheromone that is used in the formula for calculating the random proportion rule in traditional ant-colony optimization to select the optimal data transmission path. Simulation results show that the improved algorithm can increase both the security of data transmission and the quality of routing service.

A Multi-Attribute Pheromone Ant Secure Routing Algorithm Based on Reputation Value for Sensor Networks

Science.gov (United States)

Zhang, Lin; Yin, Na; Fu, Xiong; Lin, Qiaomin; Wang, Ruchuan

2017-01-01

With the development of wireless sensor networks, certain network problems have become more prominent, such as limited node resources, low data transmission security, and short network life cycles. To solve these problems effectively, it is important to design an efficient and trusted secure routing algorithm for wireless sensor networks. Traditional ant-colony optimization algorithms exhibit only local convergence, without considering the residual energy of the nodes and many other problems. This paper introduces a multi-attribute pheromone ant secure routing algorithm based on reputation value (MPASR). This algorithm can reduce the energy consumption of a network and improve the reliability of the nodes’ reputations by filtering nodes with higher coincidence rates and improving the method used to update the nodes’ communication behaviors. At the same time, the node reputation value, the residual node energy and the transmission delay are combined to formulate a synthetic pheromone that is used in the formula for calculating the random proportion rule in traditional ant-colony optimization to select the optimal data transmission path. Simulation results show that the improved algorithm can increase both the security of data transmission and the quality of routing service. PMID:28282894

On using multiple routing metrics with destination sequenced distance vector protocol for MultiHop wireless ad hoc networks

Science.gov (United States)

Mehic, M.; Fazio, P.; Voznak, M.; Partila, P.; Komosny, D.; Tovarek, J.; Chmelikova, Z.

2016-05-01

A mobile ad hoc network is a collection of mobile nodes which communicate without a fixed backbone or centralized infrastructure. Due to the frequent mobility of nodes, routes connecting two distant nodes may change. Therefore, it is not possible to establish a priori fixed paths for message delivery through the network. Because of its importance, routing is the most studied problem in mobile ad hoc networks. In addition, if the Quality of Service (QoS) is demanded, one must guarantee the QoS not only over a single hop but over an entire wireless multi-hop path which may not be a trivial task. In turns, this requires the propagation of QoS information within the network. The key to the support of QoS reporting is QoS routing, which provides path QoS information at each source. To support QoS for real-time traffic one needs to know not only minimum delay on the path to the destination but also the bandwidth available on it. Therefore, throughput, end-to-end delay, and routing overhead are traditional performance metrics used to evaluate the performance of routing protocol. To obtain additional information about the link, most of quality-link metrics are based on calculation of the lost probabilities of links by broadcasting probe packets. In this paper, we address the problem of including multiple routing metrics in existing routing packets that are broadcasted through the network. We evaluate the efficiency of such approach with modified version of DSDV routing protocols in ns-3 simulator.

Mitigating the effects of in-vehicle distractions through use of the Psychological Refractory Period paradigm.

Science.gov (United States)

Hibberd, Daryl L; Jamson, Samantha L; Carsten, Oliver M J

2013-01-01

Modern driving involves frequent and potentially detrimental interactions with distracting in-vehicle tasks. Distraction has been shown to slow brake reaction time and decrease lateral and longitudinal vehicle control. It is likely that these negative effects will become more prevalent in the future as advances are made in the functionality, availability, and number of in-vehicle systems. This paper addresses this problem by considering ways to manage in-vehicle task presentation to mitigate their distracting effects. A driving simulator experiment using 48 participants was performed to investigate the existence of the Psychological Refractory Period in the driving context and its effect on braking performance. Drivers were exposed to lead vehicle braking events in isolation (single-task) and with a preceding surrogate in-vehicle task (dual-task). In dual-task scenarios, the time interval between the in-vehicle and braking tasks was manipulated. Brake reaction time increased when drivers were distracted. The in-vehicle task interfered with the performance of the braking task in a manner that was dependent on the interval between the two tasks, with slower reactions following a shorter inter-task interval. This is the Psychological Refractory Period effect. These results have implications for driver safety during in-vehicle distraction. The findings are used to develop recommendations regarding the timing of in-vehicle task presentation so as to reduce their potentially damaging effects on braking performance. In future, these guidelines could be incorporated into a driver workload management system to minimise the opportunity for a driver to be distracted from the ongoing driving task. Copyright © 2012 Elsevier Ltd. All rights reserved.

Enhanced ant colony optimization for inventory routing problem

Science.gov (United States)

Wong, Lily; Moin, Noor Hasnah

2015-10-01

The inventory routing problem (IRP) integrates and coordinates two important components of supply chain management which are transportation and inventory management. We consider a one-to-many IRP network for a finite planning horizon. The demand for each product is deterministic and time varying as well as a fleet of capacitated homogeneous vehicles, housed at a depot/warehouse, delivers the products from the warehouse to meet the demand specified by the customers in each period. The inventory holding cost is product specific and is incurred at the customer sites. The objective is to determine the amount of inventory and to construct a delivery routing that minimizes both the total transportation and inventory holding cost while ensuring each customer's demand is met over the planning horizon. The problem is formulated as a mixed integer programming problem and is solved using CPLEX 12.4 to get the lower and upper bound (best integer) for each instance considered. We propose an enhanced ant colony optimization (ACO) to solve the problem and the built route is improved by using local search. The computational experiments demonstrating the effectiveness of our approach is presented.

Route churn: an analysis of low-cost carrier route continuity in Europe

NARCIS (Netherlands)

de Wit, J.G.; Zuidberg, J.

2016-01-01

Discontinuity of air routes is a subject that has been analysed in various ways. For example, the complex network approach focuses on network robustness and resilience due to route interruptions during a relatively short period. Also seasonal interruptions of air routes are a well-documented

Applied Multiprotocol Routing in IP Telephony

Directory of Open Access Journals (Sweden)

Miroslav Voznak

2010-01-01

Full Text Available The aim of the project was to create a multi-protocol system using SIP, H.323 and MGCP standards, which would ensure routing to various types of VoIP networks. The priority was to provide multi-protocol support to SIP and H.323 signalling and the support of the routing using the ENUM standard which has recently passed from the trial phase into full operation in the Czech Republic. The document describes the system's architecture and the components used. It also briefly describes ENUM.

Route survey periodicity for mine warfare

OpenAIRE

Coke, Hartwell F.

2009-01-01

Approved for public release, distribution unlimited One of the Navy's most long standing challenges has been conquering the mine warfare threat. As mines and mine warfare techniques evolve and become more sophisticated, so does the United States' ability to counter the threat. The United States newest technique for countering a potential mined harbor, or route, is a process known as "change detection." This concept uses previous side scan sonar images of the area prior to a mining event an...

Evaluation of cyclic battery ageing for railway vehicle application

OpenAIRE

Sigle, Sebastian; Kaimer, Stefan; Dittus, Holger; Barai, Anup; McGordon, Andrew; Widanage, W. Dhammika

2017-01-01

Mobile transportation systems rely heavily on hydrocarbon based internal combustions engines (ICE) as the prime mover of vehicles. For rail applications electrification of the route provides an opportunity to improve efficiency and eliminate local emissions at point of use. However, route electrification is not always cost effective for secondary routes which see lower passenger volumes and less frequent trains; there is therefore an increasing interest in railway vehicles being equipped with...

JOINT OPTIMIZATION OF PRODUCTION PLANNING AND VEHICLE ROUTING PROBLEMS: A REVIEW OF EXISTING STRATEGIES

Directory of Open Access Journals (Sweden)

Marc Reimann

2014-05-01

Full Text Available Keen competition and increasingly demanding customers have forced companies to use their resources more efficiently and to integrate production and transportation planning. In the last few years more and more researchers have also focused on this challenging problem by trying to determine the complexity of the individual problems and then developing fast and robust algorithms to solve them. This paper reviews existing literature on integrated production and distribution decisions at the tactical and operational level, where the distribution part is modelled as some variation of the well-known Vehicle Routing Problem (VRP. The focus is thereby on problems that explicitly consider deliveries to multiple clients in a less-than-truckload fashion. In terms of the production decisions we distinguish in our review between tactical and operational production problems by considering lot-sizing/capacity allocation and scheduling models, respectively.

Development of a hybrid genetic algorithm based decision support system for vehicle routing and scheduling in supply chain logistics managment

OpenAIRE

Khanian, Seyed Mohammad Shafi

2007-01-01

Vehicle Routing and Scheduling (VRS) constitute an important part of logistics management. Given the fact that the worldwide cost on physical distribution is evermore increasing, the global competition and the complex nature of logistics problems, one area, which determines the efficiency of all others, is the VRS activities. The application of Decision Support Systems (DSS) to assist logistics management with an efficient VRS could be of great benefit. Although the benefits of DSS in VRS are...

Multi-agent based modeling for electric vehicle integration in a distribution network operation

DEFF Research Database (Denmark)

Hu, Junjie; Morais, Hugo; Lind, Morten

2016-01-01

The purpose of this paper is to present a multi-agent based modeling technology for simulating and operating a hierarchical energy management of a power distribution system with focus on EVs integration. The proposed multi-agent system consists of four types of agents: i) Distribution system...... operator (DSO) technical agent and ii) DSO market agents that both belong to the top layer of the hierarchy and their roles are to manage the distribution network by avoiding grid congestions and using congestion prices to coordinate the energy scheduled; iii) Electric vehicle virtual power plant agents...

Artificial immune algorithm for multi-depot vehicle scheduling problems

Science.gov (United States)

Wu, Zhongyi; Wang, Donggen; Xia, Linyuan; Chen, Xiaoling

2008-10-01

In the fast-developing logistics and supply chain management fields, one of the key problems in the decision support system is that how to arrange, for a lot of customers and suppliers, the supplier-to-customer assignment and produce a detailed supply schedule under a set of constraints. Solutions to the multi-depot vehicle scheduling problems (MDVRP) help in solving this problem in case of transportation applications. The objective of the MDVSP is to minimize the total distance covered by all vehicles, which can be considered as delivery costs or time consumption. The MDVSP is one of nondeterministic polynomial-time hard (NP-hard) problem which cannot be solved to optimality within polynomial bounded computational time. Many different approaches have been developed to tackle MDVSP, such as exact algorithm (EA), one-stage approach (OSA), two-phase heuristic method (TPHM), tabu search algorithm (TSA), genetic algorithm (GA) and hierarchical multiplex structure (HIMS). Most of the methods mentioned above are time consuming and have high risk to result in local optimum. In this paper, a new search algorithm is proposed to solve MDVSP based on Artificial Immune Systems (AIS), which are inspirited by vertebrate immune systems. The proposed AIS algorithm is tested with 30 customers and 6 vehicles located in 3 depots. Experimental results show that the artificial immune system algorithm is an effective and efficient method for solving MDVSP problems.

Multi-site musculoskeletal pain in Swedish police: associations with discomfort from wearing mandatory equipment and prolonged sitting.

Science.gov (United States)

Larsen, Louise Bæk; Andersson, Elisabeth Elgmark; Tranberg, Roy; Ramstrand, Nerrolyn

2018-05-01

Musculoskeletal disorders are considered as a major issue affecting the health and well-being of active duty police. Discomfort from wearing mandatory equipment and sitting for long periods of time in fleet vehicles are workload factors linked to musculoskeletal disorders in police. This study aims to determine the prevalence of multi-site musculoskeletal pain among Swedish police and to explore the possible association to discomfort experience when wearing mandatory equipment and sitting for long periods in fleet vehicles. In this cross-sectional study responses from 4185 police were collected through a self-administered online survey including questions about physical work environment, mandatory equipment and musculoskeletal pain. Multi-site pain was determined through summing pain sites from four body regions. Binomial logistic regression was performed to explore the association between multi-site musculoskeletal pain: (1) discomfort from wearing mandatory equipment and (2) sitting for long periods in fleet vehicles. The prevalence of multi-site musculoskeletal pain at least 1 day per week within the previous 3 months was 41.3%. A statistically significant association between discomfort from wearing mandatory equipment and multi-site musculoskeletal pain was found; duty belt [OR 5.42 (95% CI 4.56-6.43)] as well as body armour [OR 2.69 (95% CI 2.11-3.42)]. Sitting for long periods in fleet vehicles was not significantly associated to multi-site musculoskeletal pain. Multi-site musculoskeletal pain is a considerable problem among Swedish police and modifying mandatory equipment to decrease discomfort is suggested as a potential means of decreasing the musculoskeletal pain experienced by many police officers.

Green Routing Fuel Saving Opportunity Assessment: A Case Study on California Large-Scale Real-World Travel Data

Energy Technology Data Exchange (ETDEWEB)

Zhu, Lei [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Holden, Jacob [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Gonder, Jeffrey D [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Wood, Eric W [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

2017-07-31

New technologies, such as connected and automated vehicles, have attracted more and more researchers for improving the energy efficiency and environmental impact of current transportation systems. The green routing strategy instructs a vehicle to select the most fuel-efficient route before the vehicle departs. It benefits the current transportation system with fuel saving opportunity through identifying the greenest route. This paper introduces an evaluation framework for estimating benefits of green routing based on large-scale, real-world travel data. The framework has the capability to quantify fuel savings by estimating the fuel consumption of actual routes and comparing to routes procured by navigation systems. A route-based fuel consumption estimation model, considering road traffic conditions, functional class, and road grade is proposed and used in the framework. An experiment using a large-scale data set from the California Household Travel Survey global positioning system trajectory data base indicates that 31% of actual routes have fuel savings potential with a cumulative estimated fuel savings of 12%.

Introducing radiality constraints in capacitated location-routing problems

Directory of Open Access Journals (Sweden)

Eliana Mirledy Toro Ocampo

2017-03-01

Full Text Available In this paper, we introduce a unified mathematical formulation for the Capacitated Vehicle Routing Problem (CVRP and for the Capacitated Location Routing Problem (CLRP, adopting radiality constraints in order to guarantee valid routes and eliminate subtours. This idea is inspired by formulations already employed in electric power distribution networks, which requires a radial topology in its operation. The results show that the proposed formulation greatly improves the convergence of the solver.

Analysis of a yearly multi-round, multi-period, multi-product transmission rights auction

International Nuclear Information System (INIS)

Ziogos, N.P.; Bakirtzis, A.G.

2008-01-01

A yearly multi-round, multi-period, multi-product transmission rights (TR) auction issuing both point-to-point Financial Transmission Rights (FTRs) and Flow-Gate Rights (FGRs) is studied in this paper. In each round the TR market participants (buyers or sellers) submit their bid or offer prices based on past energy market performance. A Locational Marginal Pricing (LMP) based energy market is assumed. The TR market participants' bid or offer prices reflect their expectation of the average annual LMP differences between withdrawal and injections points for FTRs and of the transmission link capacity prices for FGRs. The TR auction is performed in four rounds; in each round 25% of the entire system capability is awarded. TRs that are awarded in one round are modeled as fixed injections in subsequent rounds. Market participants that have acquired TRs in one round can sell them in subsequent rounds. A market participant can submit bids or offers for on-peak, off-peak or 24-h TRs. A three-area, nine-bus test system with six TR market participants is used for the analysis of the TR auction. (author)

An Adaptive Tabu Search Heuristic for the Location Routing Pickup and Delivery Problem with Time Windows with a Theater Distribution Application

National Research Council Canada - National Science Library

Burks, Jr, Robert E

2006-01-01

.... The location routing problem (LRP) is an extension of the vehicle routing problem where the solution identifies the optimal location of the depots and provides the vehicle schedules and distribution routes...

Selection of hybrid vehicle for green environment using multi-attributive border approximation area comparison method

Directory of Open Access Journals (Sweden)

Tapas Kumar Biswas

2018-02-01

Full Text Available The mobility sector including all kinds of transportation systems are facing global challenges in re-spect of green environmental issues. There has been a paradigm shift in the concept of design and manufacturing of automotive vehicles keeping in mind the scarcity of fossil fuel and the impact of emission on environment due to burning of it. The addition of hybrid and electric vehicles in pas-senger car segment has got significant momentum to address the global challenges. This research investigates the performance of a group of hybrid vehicles from customers’ perspective. Among the different brands that are available in the hybrid vehicle market, smart customers have given pri-ority to vehicle cost, mileage, tail pipe emission, comfortness and high tank size volume for long drive. Considering these attributes, selection strategy for hybrid vehicles has been developed using entropy based multi-attributive border approximation area comparison (MABAC method. This research highlights the best hybrid vehicle which reduces air pollution in cities with other significant environmental benefits, reduces dependence on foreign energy imports and minimizes the annual fuel cost.

Synthesis of the adaptive continuous system for the multi-axle wheeled vehicle body oscillation damping

Science.gov (United States)

Zhileykin, M. M.; Kotiev, G. O.; Nagatsev, M. V.

2018-02-01

In order to meet the growing mobility requirements for the wheeled vehicles on all types of terrain the engineers have to develop a large number of specialized control algorithms for the multi-axle wheeled vehicle (MWV) suspension improving such qualities as ride comfort, handling and stability. The authors have developed an adaptive algorithm of the dynamic damping of the MVW body oscillations. The algorithm provides high ride comfort and high mobility of the vehicle. The article discloses a method for synthesis of an adaptive dynamic continuous algorithm of the MVW body oscillation damping and provides simulation results proving high efficiency of the developed control algorithm.

Multi-Objective Dynamic Economic Dispatch of Microgrid Systems Including Vehicle-to-Grid

Directory of Open Access Journals (Sweden)

Haitao Liu

2015-05-01

Full Text Available Based on the characteristics of electric vehicles (EVs, this paper establishes the load models of EVs under the autonomous charging mode and the coordinated charging and discharging mode. Integrating the EVs into a microgrid system which includes wind turbines (WTs, photovoltaic arrays (PVs, diesel engines (DEs, fuel cells (FCs and a storage battery (BS, this paper establishes multi-objective economic dispatch models of a microgrid, including the lowest operating cost, the least carbon dioxide emissions, and the lowest pollutant treatment cost. After converting the multi-objective functions to a single objective function by using the judgment matrix method, we analyze the dynamic economic dispatch of the microgrid system including vehicle-to-grid (V2G with an improved particle swarm optimization algorithm under different operation control strategies. With the example system, the proposed models and strategies are verified and analyzed. Simulation results show that the microgrid system with EVs under the coordinated charging and discharging mode has better operation economics than the autonomous charging mode. Meanwhile, the greater the load fluctuation is, the higher the operating cost of the microgrid system is.

A Solution Approach from an Analytic Model to Heuristic Algorithm for Special Case of Vehicle Routing Problem with Stochastic Demands

Directory of Open Access Journals (Sweden)

2009-03-01

Full Text Available We define a special case for the vehicle routing problem with stochastic demands (SC-VRPSD where customer demands are normally distributed. We propose a new linear model for computing the expected length of a tour in SC-VRPSD. The proposed model is based on the integration of the “Traveling Salesman Problem” (TSP and the Assignment Problem. For large-scale problems, we also use an Iterated Local Search (ILS algorithm in order to reach an effective solution.

Bottom-up-then-up-down Route for Multi-level Construction of Hierarchical Bi2S3 Superstructures with Magnetism Alteration

Science.gov (United States)

Wei, Chengzhen; Wang, Lanfang; Dang, Liyun; Chen, Qun; Lu, Qingyi; Gao, Feng

2015-01-01

A bottom-up-then-up-down route was proposed to construct multi-level Bi2S3 hierarchical architectures assembled by two-dimensional (2D) Bi2S3 sheet-like networks. BiOCOOH hollow spheres and flower-like structures, which are both assembled by 2D BiOCOOH nanosheets, were prepared first by a “bottom-up” route through a “quasi-emulsion” mechanism. Then the BiOCOOH hierarchical structures were transferred to hierarchical Bi2S3 architectures through an “up-down” route by an ion exchange method. The obtained Bi2S3 nanostructures remain hollow-spherical and flower-like structures of the precursors but the constructing blocks are changed to 2D sheet-like networks interweaving by Bi2S3 nanowires. The close matching of crystal lattices between Bi2S3 and BiOCOOH was believed to be the key reason for the topotactic transformation from BiOCOOH nanosheets to 2D Bi2S3 sheet-like nanowire networks. Magnetism studies reveal that unlike diamagnetism of comparative Bi2S3 nanostructures, the obtained multi-level Bi2S3 structures display S-type hysteresis and ferromagnetism at low field which might result from ordered structure of 2D networks. PMID:26028331

Green Routing Fuel Saving Opportunity Assessment: A Case Study on California Large-Scale Real-World Travel Data: Preprint

Energy Technology Data Exchange (ETDEWEB)

Zhu, Lei; Holden, Jacob; Gonder, Jeff; Wood, Eric

2017-07-13

New technologies, such as connected and automated vehicles, have attracted more and more researchers for improving the energy efficiency and environmental impact of current transportation systems. The green routing strategy instructs a vehicle to select the most fuel-efficient route before the vehicle departs. It benefits the current transportation system with fuel saving opportunity through identifying the greenest route. This paper introduces an evaluation framework for estimating benefits of green routing based on large-scale, real-world travel data. The framework has the capability to quantify fuel savings by estimating the fuel consumption of actual routes and comparing to routes procured by navigation systems. A route-based fuel consumption estimation model, considering road traffic conditions, functional class, and road grade is proposed and used in the framework. An experiment using a large-scale data set from the California Household Travel Survey global positioning system trajectory data base indicates that 31% of actual routes have fuel savings potential with a cumulative estimated fuel savings of 12%.

Multi-sources model and control algorithm of an energy management system for light electric vehicles

International Nuclear Information System (INIS)

Hannan, M.A.; Azidin, F.A.; Mohamed, A.

2012-01-01

Highlights: ► An energy management system (EMS) is developed for a scooter under normal and heavy power load conditions. ► The battery, FC, SC, EMS, DC machine and vehicle dynamics are modeled and designed for the system. ► State-based logic control algorithms provide an efficient and feasible multi-source EMS for light electric vehicles. ► Vehicle’s speed and power are closely matched with the ECE-47 driving cycle under normal and heavy load conditions. ► Sources of energy changeover occurred at 50% of the battery state of charge level in heavy load conditions. - Abstract: This paper presents the multi-sources energy models and ruled based feedback control algorithm of an energy management system (EMS) for light electric vehicle (LEV), i.e., scooters. The multiple sources of energy, such as a battery, fuel cell (FC) and super-capacitor (SC), EMS and power controller, DC machine and vehicle dynamics are designed and modeled using MATLAB/SIMULINK. The developed control strategies continuously support the EMS of the multiple sources of energy for a scooter under normal and heavy power load conditions. The performance of the proposed system is analyzed and compared with that of the ECE-47 test drive cycle in terms of vehicle speed and load power. The results show that the designed vehicle’s speed and load power closely match those of the ECE-47 test driving cycle under normal and heavy load conditions. This study’s results suggest that the proposed control algorithm provides an efficient and feasible EMS for LEV.

Connectivity-Enhanced Route Selection and Adaptive Control for the Chevrolet Volt: Preprint

Energy Technology Data Exchange (ETDEWEB)

Gonder, J.; Wood, E.; Rajagopalan, S.

2014-09-01

The National Renewable Energy Laboratory and General Motors evaluated connectivity-enabled efficiency enhancements for the Chevrolet Volt. A high-level model was developed to predict vehicle fuel and electricity consumption based on driving characteristics and vehicle state inputs. These techniques were leveraged to optimize energy efficiency via green routing and intelligent control mode scheduling, which were evaluated using prospective driving routes between tens of thousands of real-world origin/destination pairs. The overall energy savings potential of green routing and intelligent mode scheduling was estimated at 5% and 3% respectively. These represent substantial opportunities considering that they only require software adjustments to implement.

Multi-objective parallel particle swarm optimization for day-ahead Vehicle-to-Grid scheduling

DEFF Research Database (Denmark)

Soares, Joao; Vale, Zita; Canizes, Bruno

2013-01-01

This paper presents a methodology for multi-objective day-ahead energy resource scheduling for smart grids considering intensive use of distributed generation and Vehicle-To-Grid (V2G). The main focus is the application of weighted Pareto to a multi-objective parallel particle swarm approach aiming...... to solve the dual-objective V2G scheduling: minimizing total operation costs and maximizing V2G income. A realistic mathematical formulation, considering the network constraints and V2G charging and discharging efficiencies is presented and parallel computing is applied to the Pareto weights. AC power flow...

Development of Constraint Force Equation Methodology for Application to Multi-Body Dynamics Including Launch Vehicle Stage Seperation

Science.gov (United States)

Pamadi, Bandu N.; Toniolo, Matthew D.; Tartabini, Paul V.; Roithmayr, Carlos M.; Albertson, Cindy W.; Karlgaard, Christopher D.

2016-01-01

The objective of this report is to develop and implement a physics based method for analysis and simulation of multi-body dynamics including launch vehicle stage separation. The constraint force equation (CFE) methodology discussed in this report provides such a framework for modeling constraint forces and moments acting at joints when the vehicles are still connected. Several stand-alone test cases involving various types of joints were developed to validate the CFE methodology. The results were compared with ADAMS(Registered Trademark) and Autolev, two different industry standard benchmark codes for multi-body dynamic analysis and simulations. However, these two codes are not designed for aerospace flight trajectory simulations. After this validation exercise, the CFE algorithm was implemented in Program to Optimize Simulated Trajectories II (POST2) to provide a capability to simulate end-to-end trajectories of launch vehicles including stage separation. The POST2/CFE methodology was applied to the STS-1 Space Shuttle solid rocket booster (SRB) separation and Hyper-X Research Vehicle (HXRV) separation from the Pegasus booster as a further test and validation for its application to launch vehicle stage separation problems. Finally, to demonstrate end-to-end simulation capability, POST2/CFE was applied to the ascent, orbit insertion, and booster return of a reusable two-stage-to-orbit (TSTO) vehicle concept. With these validation exercises, POST2/CFE software can be used for performing conceptual level end-to-end simulations, including launch vehicle stage separation, for problems similar to those discussed in this report.

Beyond Traditional DTN Routing: Social Networks for Opportunistic Communication

OpenAIRE

Schurgot, Mary R.; Comaniciu, Cristina; Jaffrès-Runser, Katia

2011-01-01

This article examines the evolution of routing protocols for intermittently connected ad hoc networks and discusses the trend toward social-based routing protocols. A survey of current routing solutions is presented, where routing protocols for opportunistic networks are classified based on the network graph employed. The need to capture performance tradeoffs from a multi-objective perspective is highlighted.

Multi-mode energy management strategy for fuel cell electric vehicles based on driving pattern identification using learning vector quantization neural network algorithm

Science.gov (United States)

Song, Ke; Li, Feiqiang; Hu, Xiao; He, Lin; Niu, Wenxu; Lu, Sihao; Zhang, Tong

2018-06-01

The development of fuel cell electric vehicles can to a certain extent alleviate worldwide energy and environmental issues. While a single energy management strategy cannot meet the complex road conditions of an actual vehicle, this article proposes a multi-mode energy management strategy for electric vehicles with a fuel cell range extender based on driving condition recognition technology, which contains a patterns recognizer and a multi-mode energy management controller. This paper introduces a learning vector quantization (LVQ) neural network to design the driving patterns recognizer according to a vehicle's driving information. This multi-mode strategy can automatically switch to the genetic algorithm optimized thermostat strategy under specific driving conditions in the light of the differences in condition recognition results. Simulation experiments were carried out based on the model's validity verification using a dynamometer test bench. Simulation results show that the proposed strategy can obtain better economic performance than the single-mode thermostat strategy under dynamic driving conditions.

Demonstration Project for a Multi-Material Lightweight Prototype Vehicle as Part of the Clean Energy Dialogue with Canada

Energy Technology Data Exchange (ETDEWEB)

Skszek, Tim [Vehma International Of America, Inc., Troy, MI (United States)

2015-12-29

The intent of the Multi-Material Lightweight Vehicle (“MMLV”) was to assess the feasibility of achieving a significant level of vehicle mass reduction, enabling engine downsizing resulting in a tangible fuel reduction and environmental benefit. The MMLV project included the development of two (2) lightweight vehicle designs, referred to as Mach-I and Mach-II MMLV variants, based on a 2013 Ford production C/D segment production vehicle (Fusion). Weight comparison, life cycle assessment and limited full vehicle testing are included in the project scope. The Mach-I vehicle variant was comprised of materials and processes that are commercially available or previously demonstrated. The 363 kg mass reduction associated with the Mach-I design enabled use of a one-liter, three-cylinder, gasoline turbocharged direct injection engine, maintaining the performance and utility of the baseline vehicle. The full MMLV project produced seven (7) MMLV Mach-I “concept vehicles” which were used for testing and evaluation. The full vehicle tests confirmed that MMLV Mach-I concept vehicle performed approximately equivalent to the baseline 2013 Ford Fusion vehicle thereby validating the design of the multi material lightweight vehicle design. The results of the Life Cycle Assessment, conducted by third party consultant, indicated that if the MMLV Mach-I design was built and operated in North America for 250,000 km (155,343 miles) it would produce significant environmental and fuel economy benefits including a 16% reduction in Global Warming Potential (GWP) and 16% reduction in Total Primary Energy (TPE). The LCA calculations estimated the combined fuel economy of 34 mpg (6.9 l/100 km) associated with the MMLV Mach-I Design compared to 28 mpg (8.4 l/100 km) for the 2013 Ford Fusion.

Location-routing Problem with Fuzzy time windows and Traffic time

Directory of Open Access Journals (Sweden)

Shima Teimoori

2014-05-01

Full Text Available The location-routing problem is a relatively new branch of logistics system. Its objective is to determine a suitable location for constructing distribution warehouses and proper transportation routing from warehouse to the customer. In this study, the location-routing problem is investigated with considering fuzzy servicing time window for each customer. Another important issue in this regard is the existence of congested times during the service time and distributing goods to the customer. This caused a delay in providing service for customer and imposed additional costs to distribution system. Thus we have provided a mathematical model for designing optimal distributing system. Since the vehicle location-routing problem is Np-hard, thus a solution method using genetic meta-heuristic algorithm was developed and the optimal sequence of servicing for the vehicle and optimal location for the warehouses were determined through an example.

Risk assessment of alternative proliferation routes

International Nuclear Information System (INIS)

Ahmed, S.; Husseiny, A.A.

1982-01-01

Multi-Attribute Decision Theory is applied to rank II alternative routes to nuclear proliferation in order of difficulty in acquiring nuclear weapons by nonnuclear countries. The method is based on reducing the various variables affecting the decision to a single function providing a measure for the proliferation route. The results indicate that the most difficult route to obtain atomic weapons is through nuclear power reactors, specifically the liquid-metal fast breeder reactor, heavy water Canada deuterium uranium reactor, and light water reactors such as boiling water and pressurized water reactors. The easiest routes are supercritical centrifuge isotope separation, laser isotope separation, and research reactor. However, nonnuclear routes available that result in substantial damage to life and property are easier than any nuclear route

Performance Evaluation of AODV Routing Protocol in VANET with NS2

Directory of Open Access Journals (Sweden)

Divya Rathi

2017-03-01

Full Text Available In intelligent transportation systems, the collaboration between vehicles and the road side units is essential to bring these systems to realization. The emerging Vehicular Ad Hoc Network (VANET is becoming more and more important as it provides intelligent transportation application, comfort, safety, entertainment for people in vehicles. In order to provide stable routes and to get good performance in VANET, there is a need of proper routing protocols must be designed. In this paper, we are working with the very well-known ad-hoc on-demand distance vector (AODV routing protocol. The existing Routing protocol AODV-L which is based on the Link expiration time is extended to propose a more reliable AODV-AD which is based on multichannel MAC protocol. For the performance evaluation of routing protocols, a simulation tool ‘NS2’ has been used. Simulation results show that the proposed AODV-AD protocol can achieves better performances in forms of high Route stability, Packet Delivery ratio and packet loss rate than traditional AODV-L and traditional AODV.

Distribution Route Planning of Clean Coal Based on Nearest Insertion Method

Science.gov (United States)

Wang, Yunrui

2018-01-01

Clean coal technology has made some achievements for several ten years, but the research in its distribution field is very small, the distribution efficiency would directly affect the comprehensive development of clean coal technology, it is the key to improve the efficiency of distribution by planning distribution route rationally. The object of this paper was a clean coal distribution system which be built in a county. Through the surveying of the customer demand and distribution route, distribution vehicle in previous years, it was found that the vehicle deployment was only distributed by experiences, and the number of vehicles which used each day changed, this resulted a waste of transport process and an increase in energy consumption. Thus, the mathematical model was established here in order to aim at shortest path as objective function, and the distribution route was re-planned by using nearest-insertion method which been improved. The results showed that the transportation distance saved 37 km and the number of vehicles used had also been decreased from the past average of 5 to fixed 4 every day, as well the real loading of vehicles increased by 16.25% while the current distribution volume staying same. It realized the efficient distribution of clean coal, achieved the purpose of saving energy and reducing consumption.

Multiple vehicle routing and dispatching to an emergency scene

OpenAIRE

M S Daskin; A Haghani

1984-01-01

A model of the distribution of arrival time at the scene of an emergency for the first of many vehicles is developed for the case in which travel times on the links of the network are normally distributed and the path travel times of different vehicles are correlated. The model suggests that the probability that the first vehicle arrives at the scene within a given time may be increased by reducing the path time correlations, even if doing so necessitates increasing the mean path travel time ...

A Problem-Reduction Evolutionary Algorithm for Solving the Capacitated Vehicle Routing Problem

Directory of Open Access Journals (Sweden)

Wanfeng Liu

2015-01-01

Full Text Available Assessment of the components of a solution helps provide useful information for an optimization problem. This paper presents a new population-based problem-reduction evolutionary algorithm (PREA based on the solution components assessment. An individual solution is regarded as being constructed by basic elements, and the concept of acceptability is introduced to evaluate them. The PREA consists of a searching phase and an evaluation phase. The acceptability of basic elements is calculated in the evaluation phase and passed to the searching phase. In the searching phase, for each individual solution, the original optimization problem is reduced to a new smaller-size problem. With the evolution of the algorithm, the number of common basic elements in the population increases until all individual solutions are exactly the same which is supposed to be the near-optimal solution of the optimization problem. The new algorithm is applied to a large variety of capacitated vehicle routing problems (CVRP with customers up to nearly 500. Experimental results show that the proposed algorithm has the advantages of fast convergence and robustness in solution quality over the comparative algorithms.

Route Assessment for Unmanned Aerial Vehicle Based on Cloud Model

Directory of Open Access Journals (Sweden)

Xixia Sun

2014-01-01

Full Text Available An integrated route assessment approach based on cloud model is proposed in this paper, where various sources of uncertainties are well kept and modeled by cloud theory. Firstly, a systemic criteria framework incorporating models for scoring subcriteria is developed. Then, the cloud model is introduced to represent linguistic variables, and survivability probability histogram of each route is converted into normal clouds by cloud transformation, enabling both randomness and fuzziness in the assessment environment to be managed simultaneously. Finally, a new way to measure the similarity between two normal clouds satisfying reflexivity, symmetry, transitivity, and overlapping is proposed. Experimental results demonstrate that the proposed route assessment approach outperforms fuzzy logic based assessment approach with regard to feasibility, reliability, and consistency with human thinking.

The Armys Armored Multi Purpose Vehicle (AMPV): Background and Issues for Congress

Science.gov (United States)

2016-02-24

1 Information in this section is taken from Christopher F. Foss, Jane’s Armour and Artillery, 2011-2012...for the ABCT AMPV is 2,907 vehicles—a 10 vehicle increase over 2013 quantities. Discussions with the AMPV Program Manager revealed the 10 extra...Selected Weapon Programs, GAO-14-340SP, March 2014, p. 129. 14 CRS Meeting with AMPV Program Manager May 20, 2014. 15 Ibid. The Army’s Armored Multi

A branch-and-cut-and-price algorithm for the mixed capacitated general routing problem

DEFF Research Database (Denmark)

Bach, Lukas; Wøhlk, Sanne; Lysgaard, Jens

2016-01-01

In this paper, we consider the Mixed Capacitated General Routing Problem which is a combination of the Capacitated Vehicle Routing Problem and the Capacitated Arc Routing Problem. The problem is also known as the Node, Edge, and Arc Routing Problem. We propose a Branch-and-Cut-and-Price algorithm...

Bilayer Local Search Enhanced Particle Swarm Optimization for the Capacitated Vehicle Routing Problem

Directory of Open Access Journals (Sweden)

A. K. M. Foysal Ahmed

2018-03-01

Full Text Available The classical capacitated vehicle routing problem (CVRP is a very popular combinatorial optimization problem in the field of logistics and supply chain management. Although CVRP has drawn interests of many researchers, no standard way has been established yet to obtain best known solutions for all the different problem sets. We propose an efficient algorithm Bilayer Local Search-based Particle Swarm Optimization (BLS-PSO along with a novel decoding method to solve CVRP. Decoding method is important to relate the encoded particle position to a feasible CVRP solution. In bilayer local search, one layer of local search is for the whole population in any iteration whereas another one is applied only on the pool of the best particles generated in different generations. Such searching strategies help the BLS-PSO to perform better than the existing proposals by obtaining best known solutions for most of the existing benchmark problems within very reasonable computational time. Computational results also show that the performance achieved by the proposed algorithm outperforms other PSO-based approaches.

Cascade Storage and Delivery System for a Multi Mission Space Exploration Vehicle (MMSEV)

Science.gov (United States)

Yagoda, Evan; Swickrath, Michael; Stambaugh, Imelda

2012-01-01

NASA is developing a Multi Mission Space Exploration Vehicle (MMSEV) for missions beyond Low Earth Orbit (LEO). The MMSEV is a pressurized vehicle used to extend the human exploration envelope for Lunar, Near Earth Object (NEO), and Deep Space missions. The Johnson Space Center is developing the Environmental Control and Life Support System (ECLSS) for the MMSEV. The MMSEV s intended use is to support longer sortie lengths with multiple Extra Vehicular Activities (EVAs) on a higher magnitude than any previous vehicle. This paper presents an analysis of a high pressure oxygen cascade storage and delivery system that will accommodate the crew during long duration Intra Vehicular Activity (IVA) and capable of multiple high pressure oxygen fills to the Portable Life Support System (PLSS) worn by the crew during EVAs. A cascade is a high pressure gas cylinder system used for the refilling of smaller compressed gas cylinders. Each of the large cylinders are filled by a compressor, but the cascade system allows small cylinders to be filled without the need of a compressor. In addition, the cascade system is useful as a "reservoir" to accommodate low pressure needs. A regression model was developed to provide the mechanism to size the cascade systems subject to constraints such as number of crew, extravehicular activity duration and frequency, and ullage gas requirements under contingency scenarios. The sizing routine employed a numerical integration scheme to determine gas compressibility changes during depressurization and compressibility effects were captured using the Soave-Redlich-Kwong (SRK) equation of state. A multi-dimensional nonlinear optimization routine was used to find the minimum cascade tank system mass that meets the mission requirements. The sizing algorithms developed in this analysis provide a powerful framework to assess cascade filling, compressor, and hybrid systems to design long duration vehicle ECLSS architecture. 1

Uniform Foam Crush Testing for Multi-Mission Earth Entry Vehicle Impact Attenuation

Science.gov (United States)

Patterson, Byron W.; Glaab, Louis J.

2012-01-01

Multi-Mission Earth Entry Vehicles (MMEEVs) are blunt-body vehicles designed with the purpose of transporting payloads from outer space to the surface of the Earth. To achieve high-reliability and minimum weight, MMEEVs avoid use of limited-reliability systems, such as parachutes and retro-rockets, instead using built-in impact attenuators to absorb energy remaining at impact to meet landing loads requirements. The Multi-Mission Systems Analysis for Planetary Entry (M-SAPE) parametric design tool is used to facilitate the design of MMEEVs and develop the trade space. Testing was conducted to characterize the material properties of several candidate impact foam attenuators to enhance M-SAPE analysis. In the current effort, four different Rohacell foams are tested at three different, uniform, strain rates (approximately 0.17, approximately 100, approximately 13,600%/s). The primary data analysis method uses a global data smoothing technique in the frequency domain to remove noise and system natural frequencies. The results from the data indicate that the filter and smoothing technique are successful in identifying the foam crush event and removing aberrations. The effect of strain rate increases with increasing foam density. The 71-WF-HT foam may support Mars Sample Return requirements. Several recommendations to improve the drop tower test technique are identified.

A multi-criteria decision aid methodology to design electric vehicles public charging networks

Directory of Open Access Journals (Sweden)

João Raposo

2015-05-01

Full Text Available This article presents a new multi-criteria decision aid methodology, dynamic-PROMETHEE, here used to design electric vehicle charging networks. In applying this methodology to a Portuguese city, results suggest that it is effective in designing electric vehicle charging networks, generating time and policy based scenarios, considering offer and demand and the city’s urban structure. Dynamic-PROMETHE adds to the already known PROMETHEE’s characteristics other useful features, such as decision memory over time, versatility and adaptability. The case study, used here to present the dynamic-PROMETHEE, served as inspiration and base to create this new methodology. It can be used to model different problems and scenarios that may present similar requirement characteristics.

A multi-criteria decision aid methodology to design electric vehicles public charging networks

Science.gov (United States)

Raposo, João; Rodrigues, Ana; Silva, Carlos; Dentinho, Tomaz

2015-05-01

This article presents a new multi-criteria decision aid methodology, dynamic-PROMETHEE, here used to design electric vehicle charging networks. In applying this methodology to a Portuguese city, results suggest that it is effective in designing electric vehicle charging networks, generating time and policy based scenarios, considering offer and demand and the city's urban structure. Dynamic-PROMETHE adds to the already known PROMETHEE's characteristics other useful features, such as decision memory over time, versatility and adaptability. The case study, used here to present the dynamic-PROMETHEE, served as inspiration and base to create this new methodology. It can be used to model different problems and scenarios that may present similar requirement characteristics.

Quantifying the Effects of Idle-Stop Systems on Fuel Economy in Light-Duty Passenger Vehicles

Energy Technology Data Exchange (ETDEWEB)

Jeff Wishart; Matthew Shirk

2012-12-01

Vehicles equipped with idle-stop (IS) systems are capable of engine shut down when the vehicle is stopped and rapid engine re-start for the vehicle launch. This capability reduces fuel consumption and emissions during periods when the engine is not being utilized to provide propulsion or to power accessories. IS systems are a low-cost and fast-growing technology in the industry-wide pursuit of increased vehicle efficiency, possibly becoming standard features in European vehicles in the near future. In contrast, currently there are only three non-hybrid vehicle models for sale in North America with IS systems and these models are distinctly low-volume models. As part of the United States Department of Energy’s Advanced Vehicle Testing Activity, ECOtality North America has tested the real-world effect of IS systems on fuel consumption in three vehicle models imported from Europe. These vehicles were chosen to represent three types of systems: (1) spark ignition with 12-V belt alternator starter; (2) compression ignition with 12-V belt alternator starter; and (3) direct-injection spark ignition, with 12-V belt alternator starter/combustion restart. The vehicles have undergone both dynamometer and on-road testing; the test results show somewhat conflicting data. The laboratory data and the portion of the on-road data in which driving is conducted on a prescribed route with trained drivers produced significant fuel economy improvement. However, the fleet data do not corroborate improvement, even though the data show significant engine-off time. It is possible that the effects of the varying driving styles and routes in the fleet testing overshadowed the fuel economy improvements. More testing with the same driver over routes that are similar with the IS system-enabled and disabled is recommended. There is anecdotal evidence that current Environmental Protection Agency fuel economy test procedures do not capture the fuel economy gains that IS systems produce in real

Multi-stability and almost periodic solutions of a class of recurrent neural networks

International Nuclear Information System (INIS)

Liu Yiguang; You Zhisheng

2007-01-01

This paper studies multi-stability, existence of almost periodic solutions of a class of recurrent neural networks with bounded activation functions. After introducing a sufficient condition insuring multi-stability, many criteria guaranteeing existence of almost periodic solutions are derived using Mawhin's coincidence degree theory. All the criteria are constructed without assuming the activation functions are smooth, monotonic or Lipschitz continuous, and that the networks contains periodic variables (such as periodic coefficients, periodic inputs or periodic activation functions), so all criteria can be easily extended to fit many concrete forms of neural networks such as Hopfield neural networks, or cellular neural networks, etc. Finally, all kinds of simulations are employed to illustrate the criteria

Vehicle routing with cross-docking

DEFF Research Database (Denmark)

Wen, Min; Larsen, Jesper; Clausen, Jens

2009-01-01

a set of homogeneous vehicles are used to transport orders from the suppliers to the corresponding customers via a cross-dock. The orders can be consolidated at the cross-dock but cannot be stored for very long because the cross-dock does not have long-term inventory-holding capabilities. The objective...... of the VRPCD is to minimize the total travel time while respecting time window constraints at the nodes and a time horizon for the whole transportation operation. In this paper, a mixed integer programming formulation for the VRPCD is proposed. A tabu search heuristic is embedded within an adaptive memory...... values) within very short computational time....

Multi-functional Electric Module for a Vehicle

Science.gov (United States)

Bluethmann, William J. (Inventor); Waligora, Thomas M. (Inventor); Fraser-Chanpong, Nathan (Inventor); Reed, Ryan (Inventor); Akinyode, Akinjide Akinniyi (Inventor); Spain, Ivan (Inventor); Dawson, Andrew D. (Inventor); Figuered, Joshua M. (Inventor); Herrera, Eduardo (Inventor); Markee, Mason M. (Inventor)

2015-01-01

A multi-functional electric module (eModule) is provided for a vehicle having a chassis, a master controller, and a drive wheel having a propulsion-braking module. The eModule includes a steering control assembly, mounting bracket, propulsion control assembly, brake controller, housing, and control arm. The steering control assembly includes a steering motor controlled by steering controllers in response to control signals from the master controller. A mounting feature of the bracket connects to the chassis. The propulsion control assembly and brake controller are in communication with the propulsion-braking module. The control arm connects to the lower portion and contains elements of a suspension system, with the control arm being connectable to the drive wheel via a wheel input/output block. The controllers are responsive to the master controller to control a respective steering, propulsion, and braking function. The steering motor may have a dual-wound stator with windings controlled via the respective steering controllers.

Comparative assessment of spent nuclear fuel transportation routes using risk factors and a geographic information system

International Nuclear Information System (INIS)

Toth, D.M.

1996-01-01

The assessment of potential alternative routes was simplified through the use of six comparative risk factors evaluated using detailed, route-specific data. The route and environmental attributes varied strongly with location and were developed from national, state, and local sources. The six comparative factors were risk measures of incident-free transportation radiation exposure, radiological accident population exposure, nonradiological accidents, contamination of environmental sensitive areas, environmental justice for minority populations, and environmental justice for low-income populations. An assessment of four real North-Central Florida routes provided a sample implementation of the analysis tools and risk factors. The assessment routes, consisting of common beginning and end locations, included an interstate highway, a rural highway, a mostly urban highway, and a combination interstate highway with rural bypass. This route comparative assessment study predicted that the interstate highway, despite a higher population density, greater traffic volume, and greater number of vehicular fatality accidents, would present the lowest cumulative risk. On the contrary, the rural highway route, characterized as having the lowest population density, minimal vehicle traffic volume, and the lowest percentages of minority and low-income populations, displayed the highest cumulative risk measure. Factors contributing to the high risk for the rural highway route included greater route length, higher vehicular fatality accident rates per vehicle mile traveled, and the close proximity to environmentally sensitive areas. This route comparative assessment study predicted that the interstate highway, despite a higher population density, greater traffic volume, and greater number of vehicular fatality accidents, would present the lowest cumulative risk. On the contrary, the rural highway route, characterized as having the lowest population density, minimal vehicle traffic volume

Acoustical characteristic predictions of a multi-layer system of a submerged vehicle hull mounted sonar simplified to an infinite planar model

Directory of Open Access Journals (Sweden)

Sung-Hee Kim

2012-06-01

Full Text Available Hull Mounted Sonar (HMS is a long range submerged vehicle's hull-mounted passive sonar system which detects low-frequency noise caused by machineries of enemy ships or submerged vehicles. The HMS needs a sound absorption /insulation multi-layer structure to shut out the self-noise from own machineries and to amplify signals from outside. Therefore, acoustic analysis of the multi-layer system should be performed when the HMS is designed. This paper simplified the HMS multi-layer system to be an infinite planar multi-layer model. Also, main excitations that influence the HMS were classified into mechanical, plane wave and turbulent flow excitation, and the investigations for each excitation were performed for various models. Stiffened multi-layer analysis for mechanical excitation and general multi-layer analysis for turbulent flow excitation were developed. The infinite planar multi-layer analysis was expected to be more useful for preliminary design stage of HMS system than the infinite cylindrical model because of short analysis time and easiness of parameter study.

Real-time immune-inspired optimum state-of-charge trajectory estimation using upcoming route information preview and neural networks for plug-in hybrid electric vehicles fuel economy

Science.gov (United States)

Mozaffari, Ahmad; Vajedi, Mahyar; Azad, Nasser L.

2015-06-01

The main proposition of the current investigation is to develop a computational intelligence-based framework which can be used for the real-time estimation of optimum battery state-of-charge (SOC) trajectory in plug-in hybrid electric vehicles (PHEVs). The estimated SOC trajectory can be then employed for an intelligent power management to significantly improve the fuel economy of the vehicle. The devised intelligent SOC trajectory builder takes advantage of the upcoming route information preview to achieve the lowest possible total cost of electricity and fossil fuel. To reduce the complexity of real-time optimization, the authors propose an immune system-based clustering approach which allows categorizing the route information into a predefined number of segments. The intelligent real-time optimizer is also inspired on the basis of interactions in biological immune systems, and is called artificial immune algorithm (AIA). The objective function of the optimizer is derived from a computationally efficient artificial neural network (ANN) which is trained by a database obtained from a high-fidelity model of the vehicle built in the Autonomie software. The simulation results demonstrate that the integration of immune inspired clustering tool, AIA and ANN, will result in a powerful framework which can generate a near global optimum SOC trajectory for the baseline vehicle, that is, the Toyota Prius PHEV. The outcomes of the current investigation prove that by taking advantage of intelligent approaches, it is possible to design a computationally efficient and powerful SOC trajectory builder for the intelligent power management of PHEVs.

Advanced Vehicle Testing and Evaluation

Energy Technology Data Exchange (ETDEWEB)

Garetson, Thomas [The Clarity Group, Incorporated, Chicago, IL (United States)

2013-03-31

The objective of the United States (U.S.) Department of Energy's (DOEs) Advanced Vehicle Testing and Evaluation (AVTE) project was to provide test and evaluation services for advanced technology vehicles, to establish a performance baseline, to determine vehicle reliability, and to evaluate vehicle operating costs in fleet operations.Vehicles tested include light and medium-duty vehicles in conventional, hybrid, and all-electric configurations using conventional and alternative fuels, including hydrogen in internal combustion engines. Vehicles were tested on closed tracks and chassis dynamometers, as well as operated on public roads, in fleet operations, and over prescribed routes. All testing was controlled by procedures developed specifically to support such testing.

Using the hybrid fuzzy goal programming model and hybrid genetic algorithm to solve a multi-objective location routing problem for infectious waste disposal

Directory of Open Access Journals (Sweden)

Narong Wichapa

2017-11-01

Originality/value: The novelty of the proposed methodologies, hybrid fuzzy goal programming model, is the simultaneous combination of both intangible and tangible factors in order to choose new suitable locations, and the hybrid genetic algorithm can be used to determine the optimal routes which provide a minimum number of vehicles and minimum transportation cost under the actual situation, efficiently.

Economical and environmental assessments of compressed natural gas for diesel vehicle in Thailand

Directory of Open Access Journals (Sweden)

Prateep Chouykerd

2008-08-01

Full Text Available The economic assessments for the use of compressed natural gas as fuel for several types of diesel vehicles, rarely pick up, non-fixed route truck and private truck, were studied. It is noted that two main technologies of diesel natural gas vehicle (NGV, i.e. dedicated retrofit and diesel dual fuel (DDF, were considered in this work. It was found that the dedicated retrofit needs higher investment costs than dual fuel, but can achieve higher diesel saving than dual fuel. In detail, the payback period of dual fuel non-fixed route truck was found to be identical to dual fuel private truck both in the cases of6 wheel and 10 wheel, while dedicated retrofit non-fixed route truck and private truck are also identical and have longerpay back period than dual fuel due to its higher conversion costs.This work also presents the emissions released from all types of engines especially green house gas CO2. It was found that, in the case of light duty diesel i.e. pickup truck, dedicated retrofit emitted high level of CO2 than both dual fuel and conventional diesel engines. For heavy duty i.e. non-fixed route truck and private truck vehicles, dedicated retrofit emitted a lower level of CO2 than normal diesel engine. Other pollutants from engine emission, i.e. hydrocarbon (HC,nitric oxide (NOx, carbon monoxide (CO and particulate matter, (PM were also observed. The results indicated that, inthe case of light duty diesel, dedicated retrofit engine emits higher levels of HC and CO than diesel engine; in contrast, it emits lower level of NOx and PM than diesel and dual fuel. Dual fuel emits HC and CO higher than diesel and dedicated retrofit but emits lower level of NOx and PM than diesel. Lastly, for heavy duty diesel, it was demonstrated that non-fixed route truck and private truck heavy duty dedicated retrofit have potential to reduce emissions of HC, NOx, CO and PM when compared to normal heavy duty diesel. Engine efficiencies under dual fuel and dedicated

Region based route planning - Multi-abstraction route planning based on intermediate level vision processing

Science.gov (United States)

Doshi, Rajkumar S.; Lam, Raymond; White, James E.

1989-01-01

Intermediate and high level processing operations are performed on vision data for the organization of images into more meaningful, higher-level topological representations by means of a region-based route planner (RBRP). The RBRP operates in terrain scenarios where some or most of the terrain is occluded, proceeding without a priori maps on the basis of two-dimensional representations and gradient-and-roughness information. Route planning is accomplished by three successive abstractions and yields a detailed point-by-point path by searching only within the boundaries of relatively small regions.

Coexisting chaotic and multi-periodic dynamics in a model of cardiac alternans

Energy Technology Data Exchange (ETDEWEB)

Skardal, Per Sebastian, E-mail: skardals@gmail.com [Departament d' Enginyeria Informàtica i Matemàtiques, Universitat Rovira i Virgili, 43007 Tarragona (Spain); Restrepo, Juan G., E-mail: juanga@colorado.edu [Department of Applied Mathematics, University of Colorado, Boulder, Colorado 80309 (United States)

2014-12-15

The spatiotemporal dynamics of cardiac tissue is an active area of research for biologists, physicists, and mathematicians. Of particular interest is the study of period-doubling bifurcations and chaos due to their link with cardiac arrhythmogenesis. In this paper, we study the spatiotemporal dynamics of a recently developed model for calcium-driven alternans in a one dimensional cable of tissue. In particular, we observe in the cable coexistence of regions with chaotic and multi-periodic dynamics over wide ranges of parameters. We study these dynamics using global and local Lyapunov exponents and spatial trajectory correlations. Interestingly, near nodes—or phase reversals—low-periodic dynamics prevail, while away from the nodes, the dynamics tend to be higher-periodic and eventually chaotic. Finally, we show that similar coexisting multi-periodic and chaotic dynamics can also be observed in a detailed ionic model.

Applications of multi-criteria and game theory approaches manufacturing and logistics

CERN Document Server

Hennet, Jean-Claude; Tiwari, Manoj

2014-01-01

Aligning the latest practices, innovations and case studies with academic frameworks and theories, the broad area of multi-criteria and game theory applications in manufacturing and logistics is covered in comprehensive details. Part 1 presents ‘multi-criteria applications’ and includes chapters on  logistics with a focus on vehicle routing problems, a multi-objective decision making approach to select the best storage policy and an exploratory study to predict the most important factors that can lead to successful mobile supply chain management adoption for manufacturing firms. Part 2 covers ‘game theory applications’ and encompasses the process of forming a coalition within a corporate network to the problem of integrating inventory and distribution optimization together with game theory to effectively manage supply networks. Providing a forum to investigate, exchange novel ideas and disseminate knowledge covering the broad area of multi-criteria and game theory applications in manufacturing and l...

Efficient routing of service vehicles. Publication No. 95-82, and Publication No. 1010

Energy Technology Data Exchange (ETDEWEB)

Gendreau, M.; Laporte, G.; Yelle, S.Y.

1995-12-31

GeoRoute is an arc routing software package that includes a route optimization module based on the GENIUS traveling salesman problem heuristic. The territory under study is represented by a directed graph in which arcs correspond to streets. The system also introduces artificial arcs to account for street crossings, street changes, and turns. In many applications of the package, penalties should be assigned to take into account such constraints as prohibited turns and minimization of deadheading. This report describes experiments performed using GeoRoute to determine optimal routes for garbage collection and for snow plowing operations on 30 street networks. The experiments tested various values of penalties in order to arrive at convenient packages of penalties for use in various situations. The results help GeoRoute users select sets of penalties without having to ponder a large set of possible parameters.

A Review Of Design And Control Of Automated Guided Vehicle Systems

NARCIS (Netherlands)

T. Le-Anh (Tuan); M.B.M. de Koster (René)

2004-01-01

textabstractThis paper presents a review on design and control of automated guided vehicle systems. We address most key related issues including guide-path design, estimating the number of vehicles, vehicle scheduling, idle-vehicle positioning, battery management, vehicle routing, and conflict

Credibilistic multi-period portfolio optimization based on scenario tree