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.

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.

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.

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...

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.

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

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.

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.

Performansi Algoritma CODEQ dalam Penyelesaian Vehicle Routing Problem

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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.

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.

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

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...

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.

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

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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.

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

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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.

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 ...

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.

An Endosymbiotic Evolutionary Algorithm for the Hub Location-Routing Problem

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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.

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

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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.

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.

Periodic Heterogeneous Vehicle Routing Problem With Driver Scheduling

Science.gov (United States)

Mardiana Panggabean, Ellis; Mawengkang, Herman; Azis, Zainal; Filia Sari, Rina

2018-01-01

The paper develops a model for the optimal management of logistic delivery of a given commodity. The company has different type of vehicles with different capacity to deliver the commodity for customers. The problem is then called Periodic Heterogeneous Vehicle Routing Problem (PHVRP). The goal is to schedule the deliveries according to feasible combinations of delivery days and to determine the scheduling of fleet and driver and routing policies of the vehicles. The objective is to minimize the sum of the costs of all routes over the planning horizon. We propose a combined approach of heuristic algorithm and exact method to solve the problem.

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.

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....

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.

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.

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.

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.

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...

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

Directory of Open Access Journals (Sweden)

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.

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.

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.

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.

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...

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.

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.

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.

A hybrid metaheuristic algorithm for the multi-depot covering tour vehicle routing problem

NARCIS (Netherlands)

Allahyari, S.; Salari, M.; Vigo, D.

2015-01-01

We propose a generalization of themulti-depot capacitated vehicle routing problem where the assumption of visiting each customer does not hold. In this problem, called the Multi-Depot Covering Tour Vehicle Routing Problem (MDCTVRP), the demand of each customer could be satisfied in two different

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...

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.

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

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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.

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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.

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

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

Directory of Open Access Journals (Sweden)

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.

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....

Simulated annealing (SA to vehicle routing problems with soft time windows

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Suphan Sodsoon

2014-12-01

Full Text Available The researcher has applied and develops the meta-heuristics method to solve Vehicle Routing Problems with Soft Time Windows (VRPSTW. For this case there was only one depot, multi customers which each generally sparse either or demand was different though perceived number of demand and specific period of time to receive them. The Operation Research was representative combinatorial optimization problems and is known to be NP-hard. In this research algorithm, use Simulated Annealing (SA to determine the optimum solutions which rapidly time solving. After developed the algorithms, apply them to examine the factors and the optimum extended time windows and test these factors with vehicle problem routing under specific time windows by Solomon in OR-Library in case of maximum 25 customers. Meanwhile, 6 problems are including of C101, C102, R101, R102, RC101 and RC102 respectively. The result shows the optimum extended time windows at level of 50%. At last, after comparison these answers with the case of vehicle problem routing under specific time windows and flexible time windows, found that percentage errors on number of vehicles approximately by -28.57% and percentage errors on distances approximately by -28.57% which this algorithm spent average processing time on 45.5 sec/problems.

A multi-objective location routing problem using imperialist competitive algorithm

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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.

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

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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.

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.

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...

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.

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.

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.

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

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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.

Determining the Effectiveness of Incorporating Geographic Information Into Vehicle Performance Algorithms

Energy Technology Data Exchange (ETDEWEB)

Sera White

2012-04-01

This thesis presents a research study using one year of driving data obtained from plug-in hybrid electric vehicles (PHEV) located in Sacramento and San Francisco, California to determine the effectiveness of incorporating geographic information into vehicle performance algorithms. Sacramento and San Francisco were chosen because of the availability of high resolution (1/9 arc second) digital elevation data. First, I present a method for obtaining instantaneous road slope, given a latitude and longitude, and introduce its use into common driving intensity algorithms. I show that for trips characterized by >40m of net elevation change (from key on to key off), the use of instantaneous road slope significantly changes the results of driving intensity calculations. For trips exhibiting elevation loss, algorithms ignoring road slope overestimated driving intensity by as much as 211 Wh/mile, while for trips exhibiting elevation gain these algorithms underestimated driving intensity by as much as 333 Wh/mile. Second, I describe and test an algorithm that incorporates vehicle route type into computations of city and highway fuel economy. Route type was determined by intersecting trip GPS points with ESRI StreetMap road types and assigning each trip as either city or highway route type according to whichever road type comprised the largest distance traveled. The fuel economy results produced by the geographic classification were compared to the fuel economy results produced by algorithms that assign route type based on average speed or driving style. Most results were within 1 mile per gallon ({approx}3%) of one another; the largest difference was 1.4 miles per gallon for charge depleting highway trips. The methods for acquiring and using geographic data introduced in this thesis will enable other vehicle technology researchers to incorporate geographic data into their research problems.

Vehicle routing problem in investment fund allocation

Science.gov (United States)

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

2013-04-01

Since its introduction by Dantzig and Ramser in 1959, vehicle routing problem keeps evolving in theories, applications and variability. The evolution in computing and technology are also important contributors to research in solving vehicle routing problem. The main sectors of interests among researchers and practitioners for vehicle routing problem are transportation, distribution and logistics. However, literature found that concept and benefits of vehicle routing problem are not taken advantages of by researchers in the field of investment. Other methods found used in investment include multi-objective programming, linear programming, goal programming and integer programming. Yet the application of vehicle routing problem is not fully explored. A proposal on a framework of the fund allocation optimization using vehicle routing problem is presented here. Preliminary results using FTSE Bursa Malaysia data testing the framework are also given.

An overview of smart grid routing algorithms

Science.gov (United States)

Wang, Junsheng; OU, Qinghai; Shen, Haijuan

2017-08-01

This paper summarizes the typical routing algorithm in smart grid by analyzing the communication business and communication requirements of intelligent grid. Mainly from the two kinds of routing algorithm is analyzed, namely clustering routing algorithm and routing algorithm, analyzed the advantages and disadvantages of two kinds of typical routing algorithm in routing algorithm and applicability.

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.

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...

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.

Single-Commodity Vehicle Routing Problem with Pickup and Delivery Service

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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.

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.

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

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

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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.

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.

Research and application of genetic algorithm in path planning of logistics distribution vehicle

Science.gov (United States)

Wang, Yong; Zhou, Heng; Wang, Ying

2017-08-01

The core of the logistics distribution system is the vehicle routing planning, research path planning problem, provide a better solution has become an important issue. In order to provide the decision support for logistics and distribution operations, this paper studies the problem of vehicle routing with capacity constraints (CVRP). By establishing a mathematical model, the genetic algorithm is used to plan the path of the logistics vehicle to meet the minimum logistics and transportation costs.

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.

A Monarch Butterfly Optimization for the Dynamic Vehicle Routing Problem

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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.

Planning of Vehicle Routing with Backup Provisioning Using Wireless Sensor Technologies

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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.

Two phase genetic algorithm for vehicle routing and scheduling problem with cross-docking and time windows considering customer satisfaction

Science.gov (United States)

Baniamerian, Ali; Bashiri, Mahdi; Zabihi, Fahime

2018-03-01

Cross-docking is a new warehousing policy in logistics which is widely used all over the world and attracts many researchers attention to study about in last decade. In the literature, economic aspects has been often studied, while one of the most significant factors for being successful in the competitive global market is improving quality of customer servicing and focusing on customer satisfaction. In this paper, we introduce a vehicle routing and scheduling problem with cross-docking and time windows in a three-echelon supply chain that considers customer satisfaction. A set of homogeneous vehicles collect products from suppliers and after consolidation process in the cross-dock, immediately deliver them to customers. A mixed integer linear programming model is presented for this problem to minimize transportation cost and early/tardy deliveries with scheduling of inbound and outbound vehicles to increase customer satisfaction. A two phase genetic algorithm (GA) is developed for the problem. For investigating the performance of the algorithm, it was compared with exact and lower bound solutions in small and large-size instances, respectively. Results show that there are at least 86.6% customer satisfaction by the proposed method, whereas customer satisfaction in the classical model is at most 33.3%. Numerical examples results show that the proposed two phase algorithm could achieve optimal solutions in small-size instances. Also in large-size instances, the proposed two phase algorithm could achieve better solutions with less gap from the lower bound in less computational time in comparison with the classic GA.

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...

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.

Performance of clustering techniques for solving multi depot vehicle routing problem

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Eliana M. Toro-Ocampo

2016-01-01

Full Text Available The vehicle routing problem considering multiple depots is classified as NP-hard. MDVRP determines simultaneously the routes of a set of vehicles and aims to meet a set of clients with a known demand. The objective function of the problem is to minimize the total distance traveled by the routes given that all customers must be served considering capacity constraints in depots and vehicles. This paper presents a hybrid methodology that combines agglomerative clustering techniques to generate initial solutions with an iterated local search algorithm (ILS to solve the problem. Although previous studies clustering methods have been proposed like strategies to generate initial solutions, in this work the search is intensified on the information generated after applying the clustering technique. Besides an extensive analysis on the performance of techniques, and their effect in the final solution is performed. The operation of the proposed methodology is feasible and effective to solve the problem regarding the quality of the answers and computational times obtained on request evaluated literature

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

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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.

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....

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.

Cooperative vehicles for robust traffic congestion reduction: An analysis based on algorithmic, environmental and agent behavioral factors.

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Prajakta Desai

Full Text Available Traffic congestion continues to be a persistent problem throughout the world. As vehicle-to-vehicle communication develops, there is an opportunity of using cooperation among close proximity vehicles to tackle the congestion problem. The intuition is that if vehicles could cooperate opportunistically when they come close enough to each other, they could, in effect, spread themselves out among alternative routes so that vehicles do not all jam up on the same roads. Our previous work proposed a decentralized multiagent based vehicular congestion management algorithm entitled Congestion Avoidance and Route Allocation using Virtual Agent Negotiation (CARAVAN, wherein the vehicles acting as intelligent agents perform cooperative route allocation using inter-vehicular communication. This paper focuses on evaluating the practical applicability of this approach by testing its robustness and performance (in terms of travel time reduction, across variations in: (a environmental parameters such as road network topology and configuration; (b algorithmic parameters such as vehicle agent preferences and route cost/preference multipliers; and (c agent-related parameters such as equipped/non-equipped vehicles and compliant/non-compliant agents. Overall, the results demonstrate the adaptability and robustness of the decentralized cooperative vehicles approach to providing global travel time reduction using simple local coordination strategies.

Cooperative vehicles for robust traffic congestion reduction: An analysis based on algorithmic, environmental and agent behavioral factors.

Science.gov (United States)

Desai, Prajakta; Loke, Seng W; Desai, Aniruddha

2017-01-01

Traffic congestion continues to be a persistent problem throughout the world. As vehicle-to-vehicle communication develops, there is an opportunity of using cooperation among close proximity vehicles to tackle the congestion problem. The intuition is that if vehicles could cooperate opportunistically when they come close enough to each other, they could, in effect, spread themselves out among alternative routes so that vehicles do not all jam up on the same roads. Our previous work proposed a decentralized multiagent based vehicular congestion management algorithm entitled Congestion Avoidance and Route Allocation using Virtual Agent Negotiation (CARAVAN), wherein the vehicles acting as intelligent agents perform cooperative route allocation using inter-vehicular communication. This paper focuses on evaluating the practical applicability of this approach by testing its robustness and performance (in terms of travel time reduction), across variations in: (a) environmental parameters such as road network topology and configuration; (b) algorithmic parameters such as vehicle agent preferences and route cost/preference multipliers; and (c) agent-related parameters such as equipped/non-equipped vehicles and compliant/non-compliant agents. Overall, the results demonstrate the adaptability and robustness of the decentralized cooperative vehicles approach to providing global travel time reduction using simple local coordination strategies.

Routing algorithms in networks-on-chip

CERN Document Server

Daneshtalab, Masoud

2014-01-01

This book provides a single-source reference to routing algorithms for Networks-on-Chip (NoCs), as well as in-depth discussions of advanced solutions applied to current and next generation, many core NoC-based Systems-on-Chip (SoCs). After a basic introduction to the NoC design paradigm and architectures, routing algorithms for NoC architectures are presented and discussed at all abstraction levels, from the algorithmic level to actual implementation.  Coverage emphasizes the role played by the routing algorithm and is organized around key problems affecting current and next generation, many-core SoCs. A selection of routing algorithms is included, specifically designed to address key issues faced by designers in the ultra-deep sub-micron (UDSM) era, including performance improvement, power, energy, and thermal issues, fault tolerance and reliability.   ·         Provides a comprehensive overview of routing algorithms for Networks-on-Chip and NoC-based, manycore systems; ·         Describe...

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...

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 ...

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...

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.

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...

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

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...

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

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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

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...

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

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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.

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.

Anticipatory vehicle routing using delegate multi-agent systems

OpenAIRE

Weyns, Danny; Holvoet, Tom; Helleboogh, Alexander

2007-01-01

This paper presents an agent-based approach, called delegate multi-agent systems, for anticipatory vehicle routing to avoid traffic congestion. In this approach, individual vehicles are represented by agents, which themselves issue light-weight agents that explore alternative routes in the environment on behalf of the vehicles. Based on the evaluation of the alternatives, the vehicles then issue light-weight agents for allocating road segments, spreading the vehicles’ intentions and coordi...

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...

Bellman Ford algorithm - in Routing Information Protocol (RIP)

Science.gov (United States)

Krianto Sulaiman, Oris; Mahmud Siregar, Amir; Nasution, Khairuddin; Haramaini, Tasliyah

2018-04-01

In a large scale network need a routing that can handle a lot number of users, one of the solutions to cope with large scale network is by using a routing protocol, There are 2 types of routing protocol that is static and dynamic, Static routing is manually route input based on network admin, while dynamic routing is automatically route input formed based on existing network. Dynamic routing is efficient used to network extensively because of the input of route automatic formed, Routing Information Protocol (RIP) is one of dynamic routing that uses the bellman-ford algorithm where this algorithm will search for the best path that traversed the network by leveraging the value of each link, so with the bellman-ford algorithm owned by RIP can optimize existing networks.

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.

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

PROPOSAL OF ALGORITHM FOR ROUTE OPTIMIZATION

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Robert Ramon de Carvalho Sousa

2016-06-01

Full Text Available This article uses “Six Sigma” methodology for the elaboration of an algorithm for routing problems which is able to obtain more efficient results than those from Clarke and Wright´s (CW algorithm (1964 in situations of random increase of product delivery demands, facing the incapability of service level increase . In some situations, the algorithm proposed obtained more efficient results than the CW algorithm. The key factor was a reduction in the number of mistakes (one way routes and in the level of result variation.

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

Directory of Open Access Journals (Sweden)

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%.

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.

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

Modeling and Solving the Multi-depot Vehicle Routing Problem with Time Window by Considering the Flexible end Depot in Each Route

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Mohammad Mirabi

2016-11-01

Full Text Available This paper considers the multi-depot vehicle routing problem with time window in which each vehicle starts from a depot and there is no need to return to its primary depot after serving customers. The mathematical model which is developed by new approach aims to minimizing the transportation cost including the travelled distance, the latest and the earliest arrival time penalties. Furthermore, in order to reduce the problem searching space, a novel GA clustering method is developed. Finally, Experiments are run on number problems of varying depots and time window, and customer sizes. The method is compared to two other clustering techniques, fuzzy C means (FCM and K-means algorithm. Experimental results show the robustness and effectiveness of the proposed algorithm.

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...

Selective epidemic vaccination under the performant routing algorithms

Science.gov (United States)

Bamaarouf, O.; Alweimine, A. Ould Baba; Rachadi, A.; EZ-Zahraouy, H.

2018-04-01

Despite the extensive research on traffic dynamics and epidemic spreading, the effect of the routing algorithms strategies on the traffic-driven epidemic spreading has not received an adequate attention. It is well known that more performant routing algorithm strategies are used to overcome the congestion problem. However, our main result shows unexpectedly that these algorithms favor the virus spreading more than the case where the shortest path based algorithm is used. In this work, we studied the virus spreading in a complex network using the efficient path and the global dynamic routing algorithms as compared to shortest path strategy. Some previous studies have tried to modify the routing rules to limit the virus spreading, but at the expense of reducing the traffic transport efficiency. This work proposed a solution to overcome this drawback by using a selective vaccination procedure instead of a random vaccination used often in the literature. We found that the selective vaccination succeeded in eradicating the virus better than a pure random intervention for the performant routing algorithm strategies.

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...

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...

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...

Solving a bi-objective vehicle routing problem under uncertainty by a revised multi-choice goal programming approach

Directory of Open Access Journals (Sweden)

Hossein Yousefi

2017-06-01

Full Text Available A vehicle routing problem with time windows (VRPTW is an important problem with many real applications in a transportation problem. The optimum set of routes with the minimum distance and vehicles used is determined to deliver goods from a central depot, using a vehicle with capacity constraint. In the real cases, there are other objective functions that should be considered. This paper considers not only the minimum distance and the number of vehicles used as the objective function, the customer’s satisfaction with the priority of customers is also considered. Additionally, it presents a new model for a bi-objective VRPTW solved by a revised multi-choice goal programming approach, in which the decision maker determines optimistic aspiration levels for each objective function. Two meta-heuristic methods, namely simulated annealing (SA and genetic algorithm (GA, are proposed to solve large-sized problems. Moreover, the experimental design is used to tune the parameters of the proposed algorithms. The presented model is verified by a real-world case study and a number of test problems. The computational results verify the efficiency of the proposed SA and GA.

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

Directory of Open Access Journals (Sweden)

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.

Capacity Constrained Routing Algorithms for Evacuation Route Planning

National Research Council Canada - National Science Library

Lu, Qingsong; George, Betsy; Shekhar, Shashi

2006-01-01

.... In this paper, we propose a new approach, namely a capacity constrained routing planner which models capacity as a time series and generalizes shortest path algorithms to incorporate capacity constraints...

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.

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...

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.

One Kind of Routing Algorithm Modified in Wireless Sensor Network

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Wei Ni Ni

2016-01-01

Full Text Available The wireless sensor networks are the emerging next generation sensor networks, Routing technology is the wireless sensor network communication layer of the core technology. To build reliable paths in wireless sensor networks, we can consider two ways: providing multiple paths utilizing the redundancy to assure the communication reliability or constructing transmission reliability mechanism to assure the reliability of every hop. Braid multipath algorithm and ReInforM routing algorithm are the realizations of these two mechanisms. After the analysis of these two algorithms, this paper proposes a ReInforM routing algorithm based braid multipath routing algorithm.

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

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.

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....

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.

Route planning algorithms: Planific@ Project

Directory of Open Access Journals (Sweden)

Gonzalo Martín Ortega

2009-12-01

Full Text Available Planific@ is a route planning project for the city of Madrid (Spain. Its main aim is to develop an intelligence system capable of routing people from one place in the city to any other using the public transport. In order to do this, it is necessary to take into account such things as: time, traffic, user preferences, etc. Before beginning to design the project is necessary to make a comprehensive study of the variety of main known route planning algorithms suitable to be used in this project.

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.

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.

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

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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.

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.

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

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

Directory of Open Access Journals (Sweden)

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.

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.

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 efficient heuristic for the multi-compartment vehicle routing problem

OpenAIRE

Paulo Vitor Silvestrin

2016-01-01

We study a variant of the vehicle routing problem that allows vehicles with multiple compartments. The need for multiple compartments frequently arises in practical applications when there are several products of different quality or type, that must be kept or handled separately. The resulting problem is called the multi-compartment vehicle routing problem (MCVRP). We propose a tabu search heuristic and embed it into an iterated local search to solve the MCVRP. In several experiments we analy...

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.

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.

Parallel algorithms for placement and routing in VLSI design. Ph.D. Thesis

Science.gov (United States)

Brouwer, Randall Jay

1991-01-01

The computational requirements for high quality synthesis, analysis, and verification of very large scale integration (VLSI) designs have rapidly increased with the fast growing complexity of these designs. Research in the past has focused on the development of heuristic algorithms, special purpose hardware accelerators, or parallel algorithms for the numerous design tasks to decrease the time required for solution. Two new parallel algorithms are proposed for two VLSI synthesis tasks, standard cell placement and global routing. The first algorithm, a parallel algorithm for global routing, uses hierarchical techniques to decompose the routing problem into independent routing subproblems that are solved in parallel. Results are then presented which compare the routing quality to the results of other published global routers and which evaluate the speedups attained. The second algorithm, a parallel algorithm for cell placement and global routing, hierarchically integrates a quadrisection placement algorithm, a bisection placement algorithm, and the previous global routing algorithm. Unique partitioning techniques are used to decompose the various stages of the algorithm into independent tasks which can be evaluated in parallel. Finally, results are presented which evaluate the various algorithm alternatives and compare the algorithm performance to other placement programs. Measurements are presented on the parallel speedups available.

InfoRoute: the CISMeF Context-specific Search Algorithm.

Science.gov (United States)

Merabti, Tayeb; Lelong, Romain; Darmoni, Stefan

2015-01-01

The aim of this paper was to present a practical InfoRoute algorithm and applications developed by CISMeF to perform a contextual information retrieval across multiple medical websites in different health domains. The algorithm was developed to treat multiple types of queries: natural, Boolean and advanced. The algorithm also generates multiple types of queries: Boolean query, PubMed query or Advanced query. Each query can be extended via an inter alignments relationship from UMLS and HeTOP portal. A web service and two web applications have been developed based on the InfoRoute algorithm to generate links-query across multiple websites, i.e.: "PubMed" or "ClinicalTrials.org". The InfoRoute algorithm is a useful tool to perform contextual information retrieval across multiple medical websites in both English and French.

PROPOSAL OF ALGORITHM FOR ROUTE OPTIMIZATION

OpenAIRE

Robert Ramon de Carvalho Sousa; Abimael de Jesus Barros Costa; Eliezé Bulhões de Carvalho; Adriano de Carvalho Paranaíba; Daylyne Maerla Gomes Lima Sandoval

2016-01-01

This article uses “Six Sigma” methodology for the elaboration of an algorithm for routing problems which is able to obtain more efficient results than those from Clarke and Wright´s (CW) algorithm (1964) in situations of random increase of product delivery demands, facing the incapability of service level increase . In some situations, the algorithm proposed obtained more efficient results than the CW algorithm. The key factor was a reduction in the number of mistakes (on...

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.

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.

Wavelength converter placement for different RWA algorithms in wavelength-routed all-optical networks

Science.gov (United States)

Chu, Xiaowen; Li, Bo; Chlamtac, Imrich

2002-07-01

Sparse wavelength conversion and appropriate routing and wavelength assignment (RWA) algorithms are the two key factors in improving the blocking performance in wavelength-routed all-optical networks. It has been shown that the optimal placement of a limited number of wavelength converters in an arbitrary mesh network is an NP complete problem. There have been various heuristic algorithms proposed in the literature, in which most of them assume that a static routing and random wavelength assignment RWA algorithm is employed. However, the existing work shows that fixed-alternate routing and dynamic routing RWA algorithms can achieve much better blocking performance. Our study in this paper further demonstrates that the wavelength converter placement and RWA algorithms are closely related in the sense that a well designed wavelength converter placement mechanism for a particular RWA algorithm might not work well with a different RWA algorithm. Therefore, the wavelength converter placement and the RWA have to be considered jointly. The objective of this paper is to investigate the wavelength converter placement problem under fixed-alternate routing algorithm and least-loaded routing algorithm. Under the fixed-alternate routing algorithm, we propose a heuristic algorithm called Minimum Blocking Probability First (MBPF) algorithm for wavelength converter placement. Under the least-loaded routing algorithm, we propose a heuristic converter placement algorithm called Weighted Maximum Segment Length (WMSL) algorithm. The objective of the converter placement algorithm is to minimize the overall blocking probability. Extensive simulation studies have been carried out over three typical mesh networks, including the 14-node NSFNET, 19-node EON and 38-node CTNET. We observe that the proposed algorithms not only outperform existing wavelength converter placement algorithms by a large margin, but they also can achieve almost the same performance comparing with full wavelength

A Hybrid Adaptive Routing Algorithm for Event-Driven Wireless Sensor Networks

Science.gov (United States)

Figueiredo, Carlos M. S.; Nakamura, Eduardo F.; Loureiro, Antonio A. F.

2009-01-01

Routing is a basic function in wireless sensor networks (WSNs). For these networks, routing algorithms depend on the characteristics of the applications and, consequently, there is no self-contained algorithm suitable for every case. In some scenarios, the network behavior (traffic load) may vary a lot, such as an event-driven application, favoring different algorithms at different instants. This work presents a hybrid and adaptive algorithm for routing in WSNs, called Multi-MAF, that adapts its behavior autonomously in response to the variation of network conditions. In particular, the proposed algorithm applies both reactive and proactive strategies for routing infrastructure creation, and uses an event-detection estimation model to change between the strategies and save energy. To show the advantages of the proposed approach, it is evaluated through simulations. Comparisons with independent reactive and proactive algorithms show improvements on energy consumption. PMID:22423207

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.

Improved Ant Colony Optimization for Seafood Product Delivery Routing Problem

Directory of Open Access Journals (Sweden)

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.

An Improved Shuffled Frog Leaping Algorithm and Its Application in Dynamic Emergency Vehicle Dispatching

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Xiaohong Duan

2018-01-01

Full Text Available The traditional method for solving the dynamic emergency vehicle dispatching problem can only get a local optimal strategy in each horizon. In order to obtain the dispatching strategy that can better respond to changes in road conditions during the whole dispatching process, the real-time and time-dependent link travel speeds are fused, and a time-dependent polygonal-shaped link travel speed function is set up to simulate the predictable changes in road conditions. Response times, accident severity, and accident time windows are taken as key factors to build an emergency vehicle dispatching model integrating dynamic emergency vehicle routing and selection. For the unpredictable changes in road conditions caused by accidents, the dispatching strategy is adjusted based on the real-time link travel speed. In order to solve the dynamic emergency vehicle dispatching model, an improved shuffled frog leaping algorithm (ISFLA is proposed. The global search of the improved algorithm uses the probability model of estimation of distribution algorithm to avoid the partial optimal solution. Based on the Beijing expressway network, the efficacy of the model and the improved algorithm were tested from three aspects. The results have shown the following: (1 Compared with SFLA, the optimization performance of ISFLA is getting better and better with the increase of the number of decision variables. When the possible emergency vehicle selection strategies are 815, the objective function value of optimal selection strategies obtained by the base algorithm is 210.10% larger than that of ISFLA. (2 The prediction error of the travel speed affects the accuracy of the initial emergency vehicle dispatching. The prediction error of ±10 can basically meet the requirements of the initial dispatching. (3 The adjustment of emergency vehicle dispatching strategy can successfully bypassed road sections affected by accidents and shorten the response time.

A study of routing algorithms for SCI-Based multistage networks

International Nuclear Information System (INIS)

Wu Bin; Kristiansen, E.; Skaali, B.; Bogaerts, A.; )

1994-03-01

The report deals with a particular class of multistage Scalable Coherent Interface (SCI) network systems and two important routing algorithms, namely self-routing and table-look up routing. The effect of routing delay on system performance is investigated by simulations. Adaptive routing and deadlock-free routing are studied. 8 refs., 11 figs., 1 tab

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...

Route Generation for a Synthetic Character (BOT) Using a Partial or Incomplete Knowledge Route Generation Algorithm in UT2004 Virtual Environment

Science.gov (United States)

Hanold, Gregg T.; Hanold, David T.

2010-01-01

This paper presents a new Route Generation Algorithm that accurately and realistically represents human route planning and navigation for Military Operations in Urban Terrain (MOUT). The accuracy of this algorithm in representing human behavior is measured using the Unreal Tournament(Trademark) 2004 (UT2004) Game Engine to provide the simulation environment in which the differences between the routes taken by the human player and those of a Synthetic Agent (BOT) executing the A-star algorithm and the new Route Generation Algorithm can be compared. The new Route Generation Algorithm computes the BOT route based on partial or incomplete knowledge received from the UT2004 game engine during game play. To allow BOT navigation to occur continuously throughout the game play with incomplete knowledge of the terrain, a spatial network model of the UT2004 MOUT terrain is captured and stored in an Oracle 11 9 Spatial Data Object (SOO). The SOO allows a partial data query to be executed to generate continuous route updates based on the terrain knowledge, and stored dynamic BOT, Player and environmental parameters returned by the query. The partial data query permits the dynamic adjustment of the planned routes by the Route Generation Algorithm based on the current state of the environment during a simulation. The dynamic nature of this algorithm more accurately allows the BOT to mimic the routes taken by the human executing under the same conditions thereby improving the realism of the BOT in a MOUT simulation environment.

DARAL: A Dynamic and Adaptive Routing Algorithm for Wireless Sensor Networks

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Francisco José Estévez

2016-06-01

Full Text Available The evolution of Smart City projects is pushing researchers and companies to develop more efficient embedded hardware and also more efficient communication technologies. These communication technologies are the focus of this work, presenting a new routing algorithm based on dynamically-allocated sub-networks and node roles. Among these features, our algorithm presents a fast set-up time, a reduced overhead and a hierarchical organization, which allows for the application of complex management techniques. This work presents a routing algorithm based on a dynamically-allocated hierarchical clustering, which uses the link quality indicator as a reference parameter, maximizing the network coverage and minimizing the control message overhead and the convergence time. The present work based its test scenario and analysis in the density measure, considered as a node degree. The routing algorithm is compared with some of the most well known routing algorithms for different scenario densities.

Energy Aware Simple Ant Routing Algorithm for Wireless Sensor Networks

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Sohail Jabbar

2015-01-01

Full Text Available Network lifetime is one of the most prominent barriers in deploying wireless sensor networks for large-scale applications because these networks employ sensors with nonrenewable scarce energy resources. Sensor nodes dissipate most of their energy in complex routing mechanisms. To cope with limited energy problem, we present EASARA, an energy aware simple ant routing algorithm based on ant colony optimization. Unlike most algorithms, EASARA strives to avoid low energy routes and optimizes the routing process through selection of least hop count path with more energy. It consists of three phases, that is, route discovery, forwarding node, and route selection. We have improved the route discovery procedure and mainly concentrate on energy efficient forwarding node and route selection, so that the network lifetime can be prolonged. The four possible cases of forwarding node and route selection are presented. The performance of EASARA is validated through simulation. Simulation results demonstrate the performance supremacy of EASARA over contemporary scheme in terms of various metrics.

Two models of the capacitated vehicle routing problem

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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.

Ship Pipe Routing Design Using NSGA-II and Coevolutionary Algorithm

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Wentie Niu

2016-01-01

Full Text Available Pipe route design plays a prominent role in ship design. Due to the complex configuration in layout space with numerous pipelines, diverse design constraints, and obstacles, it is a complicated and time-consuming process to obtain the optimal route of ship pipes. In this article, an optimized design method for branch pipe routing is proposed to improve design efficiency and to reduce human errors. By simplifying equipment and ship hull models and dividing workspace into three-dimensional grid cells, the mathematic model of layout space is constructed. Based on the proposed concept of pipe grading method, the optimization model of pipe routing is established. Then an optimization procedure is presented to deal with pipe route planning problem by combining maze algorithm (MA, nondominated sorting genetic algorithm II (NSGA-II, and cooperative coevolutionary nondominated sorting genetic algorithm II (CCNSGA-II. To improve the performance in genetic algorithm procedure, a fixed-length encoding method is presented based on improved maze algorithm and adaptive region strategy. Fuzzy set theory is employed to extract the best compromise pipeline from Pareto optimal solutions. Simulation test of branch pipe and design optimization of a fuel piping system were carried out to illustrate the design optimization procedure in detail and to verify the feasibility and effectiveness of the proposed methodology.

Evacuation route planning during nuclear emergency using genetic algorithm

International Nuclear Information System (INIS)

Suman, Vitisha; Sarkar, P.K.

2012-01-01

In nuclear industry the routing in case of any emergency is a cause of concern and of great importance. Even the smallest of time saved in the affected region saves a huge amount of otherwise received dose. Genetic algorithm an optimization technique has great ability to search for the optimal path from the affected region to a destination station in a spatially addressed problem. Usually heuristic algorithms are used to carry out these types of search strategy, but due to the lack of global sampling in the feasible solution space, these algorithms have considerable possibility of being trapped into local optima. Routing problems mainly are search problems for finding the shortest distance within a time limit to cover the required number of stations taking care of the traffics, road quality, population size etc. Lack of any formal mechanisms to help decision-makers explore the solution space of their problem and thereby challenges their assumptions about the number and range of options available. The Genetic Algorithm provides a way to optimize a multi-parameter constrained problem with an ease. Here use of Genetic Algorithm to generate a range of options available and to search a solution space and selectively focus on promising combinations of criteria makes them ideally suited to such complex spatial decision problems. The emergency response and routing can be made efficient, in accessing the closest facilities and determining the shortest route using genetic algorithm. The accuracy and care in creating database can be used to improve the result of the final output. The Genetic algorithm can be used to improve the accuracy of result on the basis of distance where other algorithm cannot be obtained. The search space can be utilized to its great extend

An Improved Differential Evolution Algorithm for Maritime Collision Avoidance Route Planning

Directory of Open Access Journals (Sweden)

Yu-xin Zhao

2014-01-01

Full Text Available High accuracy navigation and surveillance systems are pivotal to ensure efficient ship route planning and marine safety. Based on existing ship navigation and maritime collision prevention rules, an improved approach for collision avoidance route planning using a differential evolution algorithm was developed. Simulation results show that the algorithm is capable of significantly enhancing the optimized route over current methods. It has the potential to be used as a tool to generate optimal vessel routing in the presence of conflicts.

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.

An Improved Ant Colony Algorithm for Solving the Path Planning Problem of the Omnidirectional Mobile Vehicle

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Jiang Zhao

2016-01-01

Full Text Available This paper presents an improved ant colony algorithm for the path planning of the omnidirectional mobile vehicle. The purpose of the improved ant colony algorithm is to design an appropriate route to connect the starting point and ending point of the environment with obstacles. Ant colony algorithm, which is used to solve the path planning problem, is improved according to the characteristics of the omnidirectional mobile vehicle. And in the improved algorithm, the nonuniform distribution of the initial pheromone and the selection strategy with direction play a very positive role in the path search. The coverage and updating strategy of pheromone is introduced to avoid repeated search reducing the effect of the number of ants on the performance of the algorithm. In addition, the pheromone evaporation coefficient is segmented and adjusted, which can effectively balance the convergence speed and search ability. Finally, this paper provides a theoretical basis for the improved ant colony algorithm by strict mathematical derivation, and some numerical simulations are also given to illustrate the effectiveness of the theoretical results.

Congested Link Inference Algorithms in Dynamic Routing IP Network

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Yu Chen

2017-01-01

Full Text Available The performance descending of current congested link inference algorithms is obviously in dynamic routing IP network, such as the most classical algorithm CLINK. To overcome this problem, based on the assumptions of Markov property and time homogeneity, we build a kind of Variable Structure Discrete Dynamic Bayesian (VSDDB network simplified model of dynamic routing IP network. Under the simplified VSDDB model, based on the Bayesian Maximum A Posteriori (BMAP and Rest Bayesian Network Model (RBNM, we proposed an Improved CLINK (ICLINK algorithm. Considering the concurrent phenomenon of multiple link congestion usually happens, we also proposed algorithm CLILRS (Congested Link Inference algorithm based on Lagrangian Relaxation Subgradient to infer the set of congested links. We validated our results by the experiments of analogy, simulation, and actual Internet.

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.

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.

MULTI-VEHICLE COVERING TOUR PROBLEM: BUILDING ROUTES FOR URBAN PATROLLING

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Washington Alves de Oliveira

2015-12-01

Full Text Available ABSTRACT In this paper we study a particular aspect of the urban community policing: routine patrol route planning. We seek routes that guarantee visibility, as this has a sizable impact on the community perceived safety, allowing quick emergency responses and providing surveillance of selected sites (e.g., hospitals, schools. The planning is restricted to the availability of vehicles and strives to achieve balanced routes. We study an adaptation of the model for the multi-vehicle covering tour problem, in which a set of locations must be visited, whereas another subset must be close enough to the planned routes. It constitutes an NP-complete integer programming problem. Suboptimal solutions are obtained with several heuristics, some adapted from the literature and others developed by us. We solve some adapted instances from TSPLIB and an instance with real data, the former being compared with results from literature, and latter being compared with empirical data.

Iterated Local Search Algorithm with Strategic Oscillation for School Bus Routing Problem with Bus Stop Selection

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Mohammad Saied Fallah Niasar

2017-02-01

Full Text Available he school bus routing problem (SBRP represents a variant of the well-known vehicle routing problem. The main goal of this study is to pick up students allocated to some bus stops and generate routes, including the selected stops, in order to carry students to school. In this paper, we have proposed a simple but effective metaheuristic approach that employs two features: first, it utilizes large neighborhood structures for a deeper exploration of the search space; second, the proposed heuristic executes an efficient transition between the feasible and infeasible portions of the search space. Exploration of the infeasible area is controlled by a dynamic penalty function to convert the unfeasible solution into a feasible one. Two metaheuristics, called N-ILS (a variant of the Nearest Neighbourhood with Iterated Local Search algorithm and I-ILS (a variant of Insertion with Iterated Local Search algorithm are proposed to solve SBRP. Our experimental procedure is based on the two data sets. The results show that N-ILS is able to obtain better solutions in shorter computing times. Additionally, N-ILS appears to be very competitive in comparison with the best existing metaheuristics suggested for SBRP

An Enhanced Hybrid Social Based Routing Algorithm for MANET-DTN

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Martin Matis

2016-01-01

Full Text Available A new routing algorithm for mobile ad hoc networks is proposed in this paper: an Enhanced Hybrid Social Based Routing (HSBR algorithm for MANET-DTN as optimal solution for well-connected multihop mobile networks (MANET and/or worse connected MANET with small density of the nodes and/or due to mobility fragmented MANET into two or more subnetworks or islands. This proposed HSBR algorithm is fully decentralized combining main features of both Dynamic Source Routing (DSR and Social Based Opportunistic Routing (SBOR algorithms. The proposed scheme is simulated and evaluated by replaying real life traces which exhibit this highly dynamic topology. Evaluation of new proposed HSBR algorithm was made by comparison with DSR and SBOR. All methods were simulated with different levels of velocity. The results show that HSBR has the highest success of packet delivery, but with higher delay in comparison with DSR, and much lower in comparison with SBOR. Simulation results indicate that HSBR approach can be applicable in networks, where MANET or DTN solutions are separately useless or ineffective. This method provides delivery of the message in every possible situation in areas without infrastructure and can be used as backup method for disaster situation when infrastructure is destroyed.

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.

Mobility-Assisted on-Demand Routing Algorithm for MANETs in the Presence of Location Errors

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Trung Kien Vu

2014-01-01

Full Text Available We propose a mobility-assisted on-demand routing algorithm for mobile ad hoc networks in the presence of location errors. Location awareness enables mobile nodes to predict their mobility and enhances routing performance by estimating link duration and selecting reliable routes. However, measured locations intrinsically include errors in measurement. Such errors degrade mobility prediction and have been ignored in previous work. To mitigate the impact of location errors on routing, we propose an on-demand routing algorithm taking into account location errors. To that end, we adopt the Kalman filter to estimate accurate locations and consider route confidence in discovering routes. Via simulations, we compare our algorithm and previous algorithms in various environments. Our proposed mobility prediction is robust to the location errors.

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...

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.

Collaborative en-route and slot allocation algorithm based on fuzzy comprehensive evaluation

Science.gov (United States)

Yang, Shangwen; Guo, Baohua; Xiao, Xuefei; Gao, Haichao

2018-01-01

To allocate the en-routes and slots to the flights with collaborative decision making, a collaborative en-route and slot allocation algorithm based on fuzzy comprehensive evaluation was proposed. Evaluation indexes include flight delay costs, delay time and the number of turning points. Analytic hierarchy process is applied to determining index weights. Remark set for current two flights not yet obtained the en-route and slot in flight schedule is established. Then, fuzzy comprehensive evaluation is performed, and the en-route and slot for the current two flights are determined. Continue selecting the flight not yet obtained an en-route and a slot in flight schedule. Perform fuzzy comprehensive evaluation until all flights have obtained the en-routes and slots. MatlabR2007b was applied to numerical test based on the simulated data of a civil en-route. Test results show that, compared with the traditional strategy of first come first service, the algorithm gains better effect. The effectiveness of the algorithm was verified.

Improved AODV route recovery in mobile ad-hoc networks using a genetic algorithm

Directory of Open Access Journals (Sweden)

Ahmad Maleki

2014-09-01

Full Text Available An important issue in ad-hoc on-demand distance vector (AODV routing protocols is route failure caused by node mobility in the MANETs. The AODV requires a new route discovery procedure whenever a route breaks and these frequent route discoveries increase transmission delays and routing overhead. The present study proposes a new method for AODVs using a genetic algorithm to improve the route recovery mechanism. When failure occurs in a route, the proposed method (GAAODV makes decisions regarding the QOS parameter to select source or local repair. The task of the genetic algorithm is to find an appropriate combination of weights to optimize end-to-end delay. This paper evaluates the metrics of routing overhead, average end-to-end delay, and packet delivery ratio. Comparison of the new algorithm and AODV (RFC 3561 using a NS-2 simulator shows that GAAODV obtains better results for the QOS parameters.

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.         

Location-Based Self-Adaptive Routing Algorithm for Wireless Sensor Networks in Home Automation

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Hong SeungHo

2011-01-01

Full Text Available The use of wireless sensor networks in home automation (WSNHA is attractive due to their characteristics of self-organization, high sensing fidelity, low cost, and potential for rapid deployment. Although the AODVjr routing algorithm in IEEE 802.15.4/ZigBee and other routing algorithms have been designed for wireless sensor networks, not all are suitable for WSNHA. In this paper, we propose a location-based self-adaptive routing algorithm for WSNHA called WSNHA-LBAR. It confines route discovery flooding to a cylindrical request zone, which reduces the routing overhead and decreases broadcast storm problems in the MAC layer. It also automatically adjusts the size of the request zone using a self-adaptive algorithm based on Bayes' theorem. This makes WSNHA-LBAR more adaptable to the changes of the network state and easier to implement. Simulation results show improved network reliability as well as reduced routing overhead.

An algorithm for link restoration of wavelength routing optical networks

DEFF Research Database (Denmark)

Limal, Emmanuel; Stubkjær, Kristian

1999-01-01

We present an algorithm for restoration of single link failure in wavelength routing multihop optical networks. The algorithm is based on an innovative study of networks using graph theory. It has the following original features: it (i) assigns working and spare channels simultaneously, (ii......) prevents the search for unacceptable routing paths by pointing out channels required for restoration, (iii) offers a high utilization of the capacity resources and (iv) allows a trivial search for the restoration paths. The algorithm is for link restoration of networks without wavelength translation. Its...

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

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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.

The Dynamic Multi-Period Vehicle Routing Problem

DEFF Research Database (Denmark)

Wen, Min; Cordeau, Jean-Francois; Laporte, Gilbert

This paper considers the Dynamic Multi-Period Vehicle Routing Problem which deals with the distribution of orders from a depot to a set of customers over a multi-period time horizon. Customer orders and their feasible service periods are dynamically revealed over time. The objectives are to minim......This paper considers the Dynamic Multi-Period Vehicle Routing Problem which deals with the distribution of orders from a depot to a set of customers over a multi-period time horizon. Customer orders and their feasible service periods are dynamically revealed over time. The objectives...... are to minimize total travel costs and customer waiting, and to balance the daily workload over the planning horizon. This problem originates from a large distributor operating in Sweden. It is modeled as a mixed integer linear program, and solved by means of a three-phase heuristic that works over a rolling...... planning horizon. The multi-objective aspect of the problem is handled through a scalar technique approach. Computational results show that our solutions improve upon those of the Swedish distributor....

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

Research on distributed QOS routing algorithm based on TCP/IP

Science.gov (United States)

Liu, Xiaoyue; Chen, Yongqiang

2011-10-01

At present, network environment follow protocol standard of IPV4 is intended to do the best effort of network to provide network applied service for users, however, not caring about service quality.Thus the packet loss rate is high, it cannot reach an ideal applied results. This article through the establishment of mathematical model, put forward a new distributed multi QOS routing algorithm, given the realization process of this distributed QOS routing algorithm, and simulation was carried out by simulation software. The results show the proposed algorithm can improve the utilization rate of network resources and the service quality of network application.

Application of the multi-objective cross-entropy method to the vehicle routing problem with soft time windows

Directory of Open Access Journals (Sweden)

C Hauman

2014-06-01

Full Text Available The vehicle routing problem with time windows is a widely studied problem with many real-world applications. The problem considered here entails the construction of routes that a number of identical vehicles travel to service different nodes within a certain time window. New benchmark problems with multi-objective features were recently suggested in the literature and the multi-objective optimisation cross-entropy method is applied to these problems to investigate the feasibility of the method and to determine and propose reference solutions for the benchmark problems. The application of the cross-entropy method to the multi-objective vehicle routing problem with soft time windows is investigated. The objectives that are evaluated include the minimisation of the total distance travelled, the number of vehicles and/or routes, the total waiting time and delay time of the vehicles and the makespan of a route.

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...

Reliable Ant Colony Routing Algorithm for Dual-Channel Mobile Ad Hoc Networks

Directory of Open Access Journals (Sweden)

YongQiang Li

2018-01-01

Full Text Available For the problem of poor link reliability caused by high-speed dynamic changes and congestion owing to low network bandwidth in ad hoc networks, an ant colony routing algorithm, based on reliable path under dual-channel condition (DSAR, is proposed. First, dual-channel communication mode is used to improve network bandwidth, and a hierarchical network model is proposed to optimize the dual-layer network. Thus, we reduce network congestion and communication delay. Second, a comprehensive reliable path selection strategy is designed, and the reliable path is selected ahead of time to reduce the probability of routing restart. Finally, the ant colony algorithm is used to improve the adaptability of the routing algorithm to changes of network topology. Simulation results show that DSAR improves the reliability of routing, packet delivery, and throughput.

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.

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.

Capacitated Bounded Cardinality Hub Routing Problem: Model and Solution Algorithm

OpenAIRE

Gelareha, Shahin; Monemic, Rahimeh Neamatian; Semetd, Frederic

2017-01-01

In this paper, we address the Bounded Cardinality Hub Location Routing with Route Capacity wherein each hub acts as a transshipment node for one directed route. The number of hubs lies between a minimum and a maximum and the hub-level network is a complete subgraph. The transshipment operations take place at the hub nodes and flow transfer time from a hub-level transporter to a spoke-level vehicle influences spoke- to-hub allocations. We propose a mathematical model and a branch-and-cut algor...

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...

Effective ANT based Routing Algorithm for Data Replication in MANETs

Directory of Open Access Journals (Sweden)

N.J. Nithya Nandhini

2013-12-01

Full Text Available In mobile ad hoc network, the nodes often move and keep on change its topology. Data packets can be forwarded from one node to another on demand. To increase the data accessibility data are replicated at nodes and made as sharable to other nodes. Assuming that all mobile host cooperative to share their memory and allow forwarding the data packets. But in reality, all nodes do not share the resources for the benefits of others. These nodes may act selfishly to share memory and to forward the data packets. This paper focuses on selfishness of mobile nodes in replica allocation and routing protocol based on Ant colony algorithm to improve the efficiency. The Ant colony algorithm is used to reduce the overhead in the mobile network, so that it is more efficient to access the data than with other routing protocols. This result shows the efficiency of ant based routing algorithm in the replication allocation.

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.

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.

An Effective Hybrid Routing Algorithm in WSN: Ant Colony Optimization in combination with Hop Count Minimization

Directory of Open Access Journals (Sweden)

Ailian Jiang

2018-03-01

Full Text Available Low cost, high reliability and easy maintenance are key criteria in the design of routing protocols for wireless sensor networks (WSNs. This paper investigates the existing ant colony optimization (ACO-based WSN routing algorithms and the minimum hop count WSN routing algorithms by reviewing their strengths and weaknesses. We also consider the critical factors of WSNs, such as energy constraint of sensor nodes, network load balancing and dynamic network topology. Then we propose a hybrid routing algorithm that integrates ACO and a minimum hop count scheme. The proposed algorithm is able to find the optimal routing path with minimal total energy consumption and balanced energy consumption on each node. The algorithm has unique superiority in terms of searching for the optimal path, balancing the network load and the network topology maintenance. The WSN model and the proposed algorithm have been implemented using C++. Extensive simulation experimental results have shown that our algorithm outperforms several other WSN routing algorithms on such aspects that include the rate of convergence, the success rate in searching for global optimal solution, and the network lifetime.

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...

Evaluation of Opportunistic Routing Algorithms on Opportunistic Mobile Sensor Networks with Infrastructure Assistance

NARCIS (Netherlands)

Le Viet Duc, L Duc; Scholten, Johan; Havinga, Paul J.M.

2012-01-01

Recently the increasing number of sensors integrated in smartphones, especially the iPhone and Android phones, has motivated the development of routing algorithms for Opportunistic Mobile Sensor Networks (OppMSNs). Although there are many existing opportunistic routing algorithms, researchers still

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...

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

Directory of Open Access Journals (Sweden)

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.

Intelligent QoS routing algorithm based on improved AODV protocol for Ad Hoc networks

Science.gov (United States)

Huibin, Liu; Jun, Zhang

2016-04-01

Mobile Ad Hoc Networks were playing an increasingly important part in disaster reliefs, military battlefields and scientific explorations. However, networks routing difficulties are more and more outstanding due to inherent structures. This paper proposed an improved cuckoo searching-based Ad hoc On-Demand Distance Vector Routing protocol (CSAODV). It elaborately designs the calculation methods of optimal routing algorithm used by protocol and transmission mechanism of communication-package. In calculation of optimal routing algorithm by CS Algorithm, by increasing QoS constraint, the found optimal routing algorithm can conform to the requirements of specified bandwidth and time delay, and a certain balance can be obtained among computation spending, bandwidth and time delay. Take advantage of NS2 simulation software to take performance test on protocol in three circumstances and validate the feasibility and validity of CSAODV protocol. In results, CSAODV routing protocol is more adapt to the change of network topological structure than AODV protocol, which improves package delivery fraction of protocol effectively, reduce the transmission time delay of network, reduce the extra burden to network brought by controlling information, and improve the routing efficiency of network.

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.

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. ...

Branch-pipe-routing approach for ships using improved genetic algorithm

Science.gov (United States)

Sui, Haiteng; Niu, Wentie

2016-09-01

Branch-pipe routing plays fundamental and critical roles in ship-pipe design. The branch-pipe-routing problem is a complex combinatorial optimization problem and is thus difficult to solve when depending only on human experts. A modified genetic-algorithm-based approach is proposed in this paper to solve this problem. The simplified layout space is first divided into threedimensional (3D) grids to build its mathematical model. Branch pipes in layout space are regarded as a combination of several two-point pipes, and the pipe route between two connection points is generated using an improved maze algorithm. The coding of branch pipes is then defined, and the genetic operators are devised, especially the complete crossover strategy that greatly accelerates the convergence speed. Finally, simulation tests demonstrate the performance of proposed method.

Power Balance AODV Routing Algorithm of WSN in Precision Agriculture Environment Monitoring

Directory of Open Access Journals (Sweden)

Xiaoqin Qin

2013-11-01

Full Text Available As one of important technologies of IOT (Internet of Things, WSN (Wireless Sensor Networks has been widely used in precision agriculture environment monitoring. WSN is a kind of energy-constrained network, but power balance is not taken into account in traditional routing protocols. A novel routing algorithm, named Power Balance Ad hoc On-Demand Distance Vector (PB-AODV, is proposed on cross-layer design. In the route discovery process of PB-AODV, routing path is established by the Received Signal Strength Indication (RSSI value. The optimal transmitting power, which is computed according to RSSI value, power threshold and node’s surplus energy, is encapsulated into Route Reply Packet. Hence, the sender node can adjust its transmission power to save energy according to the Route Reply Packet. Simulation results show that the proposed algorithm is effective for load balancing, and increases the WSN’s lifetime 14.3% consequently.

Optimization Route of Food Logistics Distribution Based on Genetic and Graph Cluster Scheme Algorithm

OpenAIRE

Jing Chen

2015-01-01

This study takes the concept of food logistics distribution as the breakthrough point, by means of the aim of optimization of food logistics distribution routes and analysis of the optimization model of food logistics route, as well as the interpretation of the genetic algorithm, it discusses the optimization of food logistics distribution route based on genetic and cluster scheme algorithm.

Autonomous intelligent vehicles theory, algorithms, and implementation

CERN Document Server

Cheng, Hong

2011-01-01

Here is the latest on intelligent vehicles, covering object and obstacle detection and recognition and vehicle motion control. Includes a navigation approach using global views; introduces algorithms for lateral and longitudinal motion control and more.

A guidance and control algorithm for scent tracking micro-robotic vehicle swarms

International Nuclear Information System (INIS)

Dohner, J.L.

1998-03-01

Cooperative micro-robotic scent tracking vehicles are designed to collectively sniff out locations of high scent concentrations in unknown, geometrically complex environments. These vehicles are programmed with guidance and control algorithms that allow inter cooperation among vehicles. In this paper a cooperative guidance and control algorithm for scent tracking micro-robotic vehicles is presented. This algorithm is comprised of a sensory compensation sub-algorithm using point source cancellation, a guidance sub-algorithm using gradient descent tracking, and a control sub-algorithm using proportional feedback. The concepts of social rank and point source cancellation are new concepts introduced within. Simulation results for cooperative vehicles swarms are given. Limitations are discussed

A guidance and control algorithm for scent tracking micro-robotic vehicle swarms

Energy Technology Data Exchange (ETDEWEB)

Dohner, J.L. [Sandia National Labs., Albuquerque, NM (United States). Structural Dynamics Dept.

1998-03-01

Cooperative micro-robotic scent tracking vehicles are designed to collectively sniff out locations of high scent concentrations in unknown, geometrically complex environments. These vehicles are programmed with guidance and control algorithms that allow inter cooperation among vehicles. In this paper a cooperative guidance and control algorithm for scent tracking micro-robotic vehicles is presented. This algorithm is comprised of a sensory compensation sub-algorithm using point source cancellation, a guidance sub-algorithm using gradient descent tracking, and a control sub-algorithm using proportional feedback. The concepts of social rank and point source cancellation are new concepts introduced within. Simulation results for cooperative vehicles swarms are given. Limitations are discussed.

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...

Experiences with serial and parallel algorithms for channel routing using simulated annealing

Science.gov (United States)

Brouwer, Randall Jay

1988-01-01

Two algorithms for channel routing using simulated annealing are presented. Simulated annealing is an optimization methodology which allows the solution process to back up out of local minima that may be encountered by inappropriate selections. By properly controlling the annealing process, it is very likely that the optimal solution to an NP-complete problem such as channel routing may be found. The algorithm presented proposes very relaxed restrictions on the types of allowable transformations, including overlapping nets. By freeing that restriction and controlling overlap situations with an appropriate cost function, the algorithm becomes very flexible and can be applied to many extensions of channel routing. The selection of the transformation utilizes a number of heuristics, still retaining the pseudorandom nature of simulated annealing. The algorithm was implemented as a serial program for a workstation, and a parallel program designed for a hypercube computer. The details of the serial implementation are presented, including many of the heuristics used and some of the resulting solutions.

A Mathematical Model and Algorithm for Routing Air Traffic Under Weather Uncertainty

Science.gov (United States)

Sadovsky, Alexander V.

2016-01-01

A central challenge in managing today's commercial en route air traffic is the task of routing the aircraft in the presence of adverse weather. Such weather can make regions of the airspace unusable, so all affected flights must be re-routed. Today this task is carried out by conference and negotiation between human air traffic controllers (ATC) responsible for the involved sectors of the airspace. One can argue that, in so doing, ATC try to solve an optimization problem without giving it a precise quantitative formulation. Such a formulation gives the mathematical machinery for constructing and verifying algorithms that are aimed at solving the problem. This paper contributes one such formulation and a corresponding algorithm. The algorithm addresses weather uncertainty and has closed form, which allows transparent analysis of correctness, realism, and computational costs.

An improved artificial bee colony algorithm based on balance-evolution strategy for unmanned combat aerial vehicle path planning.

Science.gov (United States)

Li, Bai; Gong, Li-gang; Yang, Wen-lun

2014-01-01

Unmanned combat aerial vehicles (UCAVs) have been of great interest to military organizations throughout the world due to their outstanding capabilities to operate in dangerous or hazardous environments. UCAV path planning aims to obtain an optimal flight route with the threats and constraints in the combat field well considered. In this work, a novel artificial bee colony (ABC) algorithm improved by a balance-evolution strategy (BES) is applied in this optimization scheme. In this new algorithm, convergence information during the iteration is fully utilized to manipulate the exploration/exploitation accuracy and to pursue a balance between local exploitation and global exploration capabilities. Simulation results confirm that BE-ABC algorithm is more competent for the UCAV path planning scheme than the conventional ABC algorithm and two other state-of-the-art modified ABC algorithms.

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.

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.

Backtracking search algorithm in CVRP models for efficient solid waste collection and route optimization.

Science.gov (United States)

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

2017-03-01

Waste collection is an important part of waste management that involves different issues, including environmental, economic, and social, among others. Waste collection optimization can reduce the waste collection budget and environmental emissions by reducing the collection route distance. This paper presents a modified Backtracking Search Algorithm (BSA) in capacitated vehicle routing problem (CVRP) models with the smart bin concept to find the best optimized waste collection route solutions. The objective function minimizes the sum of the waste collection route distances. The study introduces the concept of the threshold waste level (TWL) of waste bins to reduce the number of bins to be emptied by finding an optimal range, thus minimizing the distance. A scheduling model is also introduced to compare the feasibility of the proposed model with that of the conventional collection system in terms of travel distance, collected waste, fuel consumption, fuel cost, efficiency and CO 2 emission. The optimal TWL was found to be between 70% and 75% of the fill level of waste collection nodes and had the maximum tightness value for different problem cases. The obtained results for four days show a 36.80% distance reduction for 91.40% of the total waste collection, which eventually increases the average waste collection efficiency by 36.78% and reduces the fuel consumption, fuel cost and CO 2 emission by 50%, 47.77% and 44.68%, respectively. Thus, the proposed optimization model can be considered a viable tool for optimizing waste collection routes to reduce economic costs and environmental impacts. Copyright © 2017 Elsevier Ltd. All rights reserved.

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.

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.

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...

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

Multifeature Fusion Vehicle Detection Algorithm Based on Choquet Integral

Directory of Open Access Journals (Sweden)

Wenhui Li

2014-01-01

Full Text Available Vision-based multivehicle detection plays an important role in Forward Collision Warning Systems (FCWS and Blind Spot Detection Systems (BSDS. The performance of these systems depends on the real-time capability, accuracy, and robustness of vehicle detection methods. To improve the accuracy of vehicle detection algorithm, we propose a multifeature fusion vehicle detection algorithm based on Choquet integral. This algorithm divides the vehicle detection problem into two phases: feature similarity measure and multifeature fusion. In the feature similarity measure phase, we first propose a taillight-based vehicle detection method, and then vehicle taillight feature similarity measure is defined. Second, combining with the definition of Choquet integral, the vehicle symmetry similarity measure and the HOG + AdaBoost feature similarity measure are defined. Finally, these three features are fused together by Choquet integral. Being evaluated on public test collections and our own test images, the experimental results show that our method has achieved effective and robust multivehicle detection in complicated environments. Our method can not only improve the detection rate but also reduce the false alarm rate, which meets the engineering requirements of Advanced Driving Assistance Systems (ADAS.

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.

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...

An Improved Artificial Bee Colony Algorithm Based on Balance-Evolution Strategy for Unmanned Combat Aerial Vehicle Path Planning

Directory of Open Access Journals (Sweden)

Bai Li

2014-01-01

Full Text Available Unmanned combat aerial vehicles (UCAVs have been of great interest to military organizations throughout the world due to their outstanding capabilities to operate in dangerous or hazardous environments. UCAV path planning aims to obtain an optimal flight route with the threats and constraints in the combat field well considered. In this work, a novel artificial bee colony (ABC algorithm improved by a balance-evolution strategy (BES is applied in this optimization scheme. In this new algorithm, convergence information during the iteration is fully utilized to manipulate the exploration/exploitation accuracy and to pursue a balance between local exploitation and global exploration capabilities. Simulation results confirm that BE-ABC algorithm is more competent for the UCAV path planning scheme than the conventional ABC algorithm and two other state-of-the-art modified ABC algorithms.

A Distance-Adaptive Refueling Recommendation Algorithm for Self-Driving Travel

Directory of Open Access Journals (Sweden)

Quanli Xu

2018-03-01

Full Text Available Taking the maximum vehicle driving distance, the distances from gas stations, the route length, and the number of refueling gas stations as the decision conditions, recommendation rules and an early refueling service warning mechanism for gas stations along a self-driving travel route were constructed by using the algorithm presented in this research, based on the spatial clustering characteristics of gas stations and the urgency of refueling. Meanwhile, by combining ArcEngine and Matlab capabilities, a scenario simulation system of refueling for self-driving travel was developed by using c#.net in order to validate and test the accuracy and applicability of the algorithm. A total of nine testing schemes with four simulation scenarios were designed and executed using this algorithm, and all of the simulation results were consistent with expectations. The refueling recommendation algorithm proposed in this study can automatically adapt to changes in the route length of self-driving travel, the maximum driving distance of the vehicle, and the distance from gas stations, which could provide variable refueling recommendation strategies according to differing gas station layouts along the route. Therefore, the results of this study could provide a scientific reference for the reasonable planning and timely supply of vehicle refueling during self-driving travel.

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...

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 ...

A Hybrid Genetic-Simulated Annealing Algorithm for the Location-Inventory-Routing Problem Considering Returns under E-Supply Chain Environment

Science.gov (United States)

Guo, Hao; Fu, Jing

2013-01-01

Facility location, inventory control, and vehicle routes scheduling are critical and highly related problems in the design of logistics system for e-business. Meanwhile, the return ratio in Internet sales was significantly higher than in the traditional business. Many of returned merchandise have no quality defects, which can reenter sales channels just after a simple repackaging process. Focusing on the existing problem in e-commerce logistics system, we formulate a location-inventory-routing problem model with no quality defects returns. To solve this NP-hard problem, an effective hybrid genetic simulated annealing algorithm (HGSAA) is proposed. Results of numerical examples show that HGSAA outperforms GA on computing time, optimal solution, and computing stability. The proposed model is very useful to help managers make the right decisions under e-supply chain environment. PMID:24489489

A hybrid genetic-simulated annealing algorithm for the location-inventory-routing problem considering returns under e-supply chain environment.

Science.gov (United States)

Li, Yanhui; Guo, Hao; Wang, Lin; Fu, Jing

2013-01-01

Facility location, inventory control, and vehicle routes scheduling are critical and highly related problems in the design of logistics system for e-business. Meanwhile, the return ratio in Internet sales was significantly higher than in the traditional business. Many of returned merchandise have no quality defects, which can reenter sales channels just after a simple repackaging process. Focusing on the existing problem in e-commerce logistics system, we formulate a location-inventory-routing problem model with no quality defects returns. To solve this NP-hard problem, an effective hybrid genetic simulated annealing algorithm (HGSAA) is proposed. Results of numerical examples show that HGSAA outperforms GA on computing time, optimal solution, and computing stability. The proposed model is very useful to help managers make the right decisions under e-supply chain environment.

A Hybrid Genetic-Simulated Annealing Algorithm for the Location-Inventory-Routing Problem Considering Returns under E-Supply Chain Environment

Directory of Open Access Journals (Sweden)

Yanhui Li

2013-01-01

Full Text Available Facility location, inventory control, and vehicle routes scheduling are critical and highly related problems in the design of logistics system for e-business. Meanwhile, the return ratio in Internet sales was significantly higher than in the traditional business. Many of returned merchandise have no quality defects, which can reenter sales channels just after a simple repackaging process. Focusing on the existing problem in e-commerce logistics system, we formulate a location-inventory-routing problem model with no quality defects returns. To solve this NP-hard problem, an effective hybrid genetic simulated annealing algorithm (HGSAA is proposed. Results of numerical examples show that HGSAA outperforms GA on computing time, optimal solution, and computing stability. The proposed model is very useful to help managers make the right decisions under e-supply chain environment.

A Combination of Meta-heuristic and Heuristic Algorithms for the VRP, OVRP and VRP with Simultaneous Pickup and Delivery

Directory of Open Access Journals (Sweden)

Maryam Ashouri

2017-07-01

Full Text Available Vehicle routing problem (VRP is a Nondeterministic Polynomial Hard combinatorial optimization problem to serve the consumers from central depots and returned back to the originated depots with given vehicles. Furthermore, two of the most important extensions of the VRPs are the open vehicle routing problem (OVRP and VRP with simultaneous pickup and delivery (VRPSPD. In OVRP, the vehicles have not return to the depot after last visit and in VRPSPD, customers require simultaneous delivery and pick-up service. The aim of this paper is to present a combined effective ant colony optimization (CEACO which includes sweep and several local search algorithms which is different with common ant colony optimization (ACO. An extensive numerical experiment is performed on benchmark problem instances addressed in the literature. The computational result shows that suggested CEACO approach not only presented a very satisfying scalability, but also was competitive with other meta-heuristic algorithms in the literature for solving VRP, OVRP and VRPSPD problems. Keywords: Meta-heuristic algorithms, Vehicle Routing Problem, Open Vehicle Routing Problem, Simultaneously Pickup and Delivery, Ant Colony Optimization.

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

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...

The production route selection algorithm in virtual manufacturing networks

Science.gov (United States)

Krenczyk, D.; Skolud, B.; Olender, M.

2017-08-01

The increasing requirements and competition in the global market are challenges for the companies profitability in production and supply chain management. This situation became the basis for construction of virtual organizations, which are created in response to temporary needs. The problem of the production flow planning in virtual manufacturing networks is considered. In the paper the algorithm of the production route selection from the set of admissible routes, which meets the technology and resource requirements and in the context of the criterion of minimum cost is proposed.

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...

The multi-depot electric vehicle location routing problem with time windows

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Juan Camilo Paz

2018-01-01

Full Text Available In this paper, the Multi-Depot Electric Vehicle Location Routing Problem with Time Windows (MDVLRP is addressed. This problem is an extension of the MDVLRP, where electric vehicles are used instead of internal combustion engine vehicles. The recent development of this model is explained by the advantages of this technology, such as the diminution of carbon dioxide emissions, and the support that they can provide to the design of the logistic and energy-support structure of electric vehicle fleets. There are many models that extend the classical VRP model to take electric vehicles into consideration, but the multi-depot case for location-routing models has not been worked out yet. Moreover, we consider the availability of two energy supply technologies: the “Plug-in” Conventional Charge technology, and Battery Swapping Stations; options in which the recharging time is a function of the amount of energy to charge and a fixed time, respectively. Three models are proposed: one for each of the technologies mentioned above, and another in which both options are taken in consideration. The models were solved for small scale instances using C++ and Cplex 12.5. The results show that the models can be used to design logistic and energy-support structures, and compare the performance of the different options of energy supply, as well as measure the impact of these decisions on the overall distance traveled or other optimization objectives that could be worked on in the future.

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...

Public Transport Route Finding using a Hybrid Genetic Algorithm

OpenAIRE

Liviu Adrian COTFAS; Andreea DIOSTEANU

2011-01-01

In this paper we present a public transport route finding solution based on a hybrid genetic algorithm. The algorithm uses two heuristics that take into consideration the number of trans-fers and the remaining distance to the destination station in order to improve the convergence speed. The interface of the system uses the latest web technologies to offer both portability and advanced functionality. The approach has been evaluated using the data for the Bucharest public transport network.

Secure Multicast Routing Algorithm for Wireless Mesh Networks

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Rakesh Matam

2016-01-01

Full Text Available Multicast is an indispensable communication technique in wireless mesh network (WMN. Many applications in WMN including multicast TV, audio and video conferencing, and multiplayer social gaming use multicast transmission. On the other hand, security in multicast transmissions is crucial, without which the network services are significantly disrupted. Existing secure routing protocols that address different active attacks are still vulnerable due to subtle nature of flaws in protocol design. Moreover, existing secure routing protocols assume that adversarial nodes cannot share an out-of-band communication channel which rules out the possibility of wormhole attack. In this paper, we propose SEMRAW (SEcure Multicast Routing Algorithm for Wireless mesh network that is resistant against all known active threats including wormhole attack. SEMRAW employs digital signatures to prevent a malicious node from gaining illegitimate access to the message contents. Security of SEMRAW is evaluated using the simulation paradigm approach.

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

Indian Academy of Sciences (India)

Pinar Kirci

PINAR KIRCI. Engineering Sciences Department, Istanbul University, Istanbul, Turkey .... In VRP solution methods, tabu search algorithm belongs to ..... systems which are considered in statistical mechanics is ..... Procedia-Social Behav. Sci.

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

A Pseudo-Parallel Genetic Algorithm Integrating Simulated Annealing for Stochastic Location-Inventory-Routing Problem with Consideration of Returns in E-Commerce

Directory of Open Access Journals (Sweden)

Bailing Liu

2015-01-01

Full Text Available Facility location, inventory control, and vehicle routes scheduling are three key issues to be settled in the design of logistics system for e-commerce. Due to the online shopping features of e-commerce, customer returns are becoming much more than traditional commerce. This paper studies a three-phase supply chain distribution system consisting of one supplier, a set of retailers, and a single type of product with continuous review (Q, r inventory policy. We formulate a stochastic location-inventory-routing problem (LIRP model with no quality defects returns. To solve the NP-hand problem, a pseudo-parallel genetic algorithm integrating simulated annealing (PPGASA is proposed. The computational results show that PPGASA outperforms GA on optimal solution, computing time, and computing stability.

Routing and scheduling of hazardous materials shipments: algorithmic approaches to managing spent nuclear fuel transport

International Nuclear Information System (INIS)

Cox, R.G.

1984-01-01

Much controversy surrounds government regulation of routing and scheduling of Hazardous Materials Transportation (HMT). Increases in operating costs must be balanced against expected benefits from local HMT bans and curfews when promulgating or preempting HMT regulations. Algorithmic approaches for evaluating HMT routing and scheduling regulatory policy are described. A review of current US HMT regulatory policy is presented to provide a context for the analysis. Next, a multiobjective shortest path algorithm to find the set of efficient routes under conflicting objectives is presented. This algorithm generates all efficient routes under any partial ordering in a single pass through the network. Also, scheduling algorithms are presented to estimate the travel time delay due to HMT curfews along a route. Algorithms are presented assuming either deterministic or stochastic travel times between curfew cities and also possible rerouting to avoid such cities. These algorithms are applied to the case study of US highway transport of spent nuclear fuel from reactors to permanent repositories. Two data sets were used. One data set included the US Interstate Highway System (IHS) network with reactor locations, possible repository sites, and 150 heavily populated areas (HPAs). The other data set contained estimates of the population residing with 0.5 miles of the IHS and the Eastern US. Curfew delay is dramatically reduced by optimally scheduling departure times unless inter-HPA travel times are highly uncertain. Rerouting shipments to avoid HPAs is a less efficient approach to reducing delay

Function-Oriented Networking and On-Demand Routing System in Network Using Ant Colony Optimization Algorithm

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Young-Bo Sim

2017-11-01

Full Text Available In this paper, we proposed and developed Function-Oriented Networking (FON, a platform for network users. It has a different philosophy as opposed to technologies for network managers of Software-Defined Networking technology, OpenFlow. It is a technology that can immediately reflect the demands of the network users in the network, unlike the existing OpenFlow and Network Functions Virtualization (NFV, which do not reflect directly the needs of the network users. It allows the network user to determine the policy of the direct network, so it can be applied more precisely than the policy applied by the network manager. This is expected to increase the satisfaction of the service users when the network users try to provide new services. We developed FON function that performs on-demand routing for Low-Delay Required service. We analyzed the characteristics of the Ant Colony Optimization (ACO algorithm and found that the algorithm is suitable for low-delay required services. It was also the first in the world to implement the routing software using ACO Algorithm in the real Ethernet network. In order to improve the routing performance, several algorithms of the ACO Algorithm have been developed to enable faster path search-routing and path recovery. The relationship between the network performance index and the ACO routing parameters is derived, and the results are compared and analyzed. Through this, it was possible to develop the ACO algorithm.

A Region Tracking-Based Vehicle Detection Algorithm in Nighttime Traffic Scenes

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Jianqiang Wang

2013-12-01

Full Text Available The preceding vehicles detection technique in nighttime traffic scenes is an important part of the advanced driver assistance system (ADAS. This paper proposes a region tracking-based vehicle detection algorithm via the image processing technique. First, the brightness of the taillights during nighttime is used as the typical feature, and we use the existing global detection algorithm to detect and pair the taillights. When the vehicle is detected, a time series analysis model is introduced to predict vehicle positions and the possible region (PR of the vehicle in the next frame. Then, the vehicle is only detected in the PR. This could reduce the detection time and avoid the false pairing between the bright spots in the PR and the bright spots out of the PR. Additionally, we present a thresholds updating method to make the thresholds adaptive. Finally, experimental studies are provided to demonstrate the application and substantiate the superiority of the proposed algorithm. The results show that the proposed algorithm can simultaneously reduce both the false negative detection rate and the false positive detection rate.

Optimal solutions for routing problems with profits

NARCIS (Netherlands)

Archetti, C.; Bianchessi, N.; Speranza, M. G.

2013-01-01

In this paper, we present a branch-and-price algorithm to solve two well-known vehicle routing problems with profits, the Capacitated Team Orienteering Problem and the Capacitated Profitable Tour Problem. A restricted master heuristic is applied at each node of the branch-and-bound tree in order to

Public Transport Route Finding using a Hybrid Genetic Algorithm

Directory of Open Access Journals (Sweden)

Liviu Adrian COTFAS

2011-01-01

Full Text Available In this paper we present a public transport route finding solution based on a hybrid genetic algorithm. The algorithm uses two heuristics that take into consideration the number of trans-fers and the remaining distance to the destination station in order to improve the convergence speed. The interface of the system uses the latest web technologies to offer both portability and advanced functionality. The approach has been evaluated using the data for the Bucharest public transport network.

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...

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.

Route Selection with Unspecified Sites Using Knowledge Based Genetic Algorithm

Science.gov (United States)

Kanoh, Hitoshi; Nakamura, Nobuaki; Nakamura, Tomohiro

This paper addresses the problem of selecting a route to a given destination that traverses several non-specific sites (e.g. a bank, a gas station) as requested by a driver. The proposed solution uses a genetic algorithm that includes viral infection. The method is to generate two populations of viruses as domain specific knowledge in addition to a population of routes. A part of an arterial road is regarded as a main virus, and a road that includes a site is regarded as a site virus. An infection occurs between two points common to a candidate route and the virus, and involves the substitution of the intersections carried by the virus for those on the existing candidate route. Crossover and infection determine the easiest-to-drive and quasi-shortest route through the objective landmarks. Experiments using actual road maps show that this infection-based mechanism is an effective way of solving the problem. Our strategy is general, and can be effectively used in other optimization problems.

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...

Energy Balance Routing Algorithm Based on Virtual MIMO Scheme for Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Jianpo Li

2014-01-01

Full Text Available Wireless sensor networks are usually energy limited and therefore an energy-efficient routing algorithm is desired for prolonging the network lifetime. In this paper, we propose a new energy balance routing algorithm which has the following three improvements over the conventional LEACH algorithm. Firstly, we propose a new cluster head selection scheme by taking into consideration the remaining energy and the most recent energy consumption of the nodes and the entire network. In this way, the sensor nodes with smaller remaining energy or larger energy consumption will be much less likely to be chosen as cluster heads. Secondly, according to the ratio of remaining energy to distance, cooperative nodes are selected to form virtual MIMO structures. It mitigates the uneven distribution of clusters and the unbalanced energy consumption of the whole network. Thirdly, we construct a comprehensive energy consumption model, which can reflect more realistically the practical energy consumption. Numerical simulations analyze the influences of cooperative node numbers and cluster head node numbers on the network lifetime. It is shown that the energy consumption of the proposed routing algorithm is lower than the conventional LEACH algorithm and for the simulation example the network lifetime is prolonged about 25%.

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.

Algorithm Research of Individualized Travelling Route Recommendation Based on Similarity

Directory of Open Access Journals (Sweden)

Xue Shan

2015-01-01

Full Text Available Although commercial recommendation system has made certain achievement in travelling route development, the recommendation system is facing a series of challenges because of people’s increasing interest in travelling. It is obvious that the core content of the recommendation system is recommendation algorithm. The advantages of recommendation algorithm can bring great effect to the recommendation system. Based on this, this paper applies traditional collaborative filtering algorithm for analysis. Besides, illustrating the deficiencies of the algorithm, such as the rating unicity and rating matrix sparsity, this paper proposes an improved algorithm combing the multi-similarity algorithm based on user and the element similarity algorithm based on user, so as to compensate for the deficiencies that traditional algorithm has within a controllable range. Experimental results have shown that the improved algorithm has obvious advantages in comparison with the traditional one. The improved algorithm has obvious effect on remedying the rating matrix sparsity and rating unicity.

An Efficient Addressing Scheme and Its Routing Algorithm for a Large-Scale Wireless Sensor Network

Directory of Open Access Journals (Sweden)

Choi Jeonghee

2008-01-01

Full Text Available Abstract So far, various addressing and routing algorithms have been extensively studied for wireless sensor networks (WSNs, but many of them were limited to cover less than hundreds of sensor nodes. It is largely due to stringent requirements for fully distributed coordination among sensor nodes, leading to the wasteful use of available address space. As there is a growing need for a large-scale WSN, it will be extremely challenging to support more than thousands of nodes, using existing standard bodies. Moreover, it is highly unlikely to change the existing standards, primarily due to backward compatibility issue. In response, we propose an elegant addressing scheme and its routing algorithm. While maintaining the existing address scheme, it tackles the wastage problem and achieves no additional memory storage during a routing. We also present an adaptive routing algorithm for location-aware applications, using our addressing scheme. Through a series of simulations, we prove that our approach can achieve two times lesser routing time than the existing standard in a ZigBee network.

An Efficient Addressing Scheme and Its Routing Algorithm for a Large-Scale Wireless Sensor Network

Directory of Open Access Journals (Sweden)

Yongwan Park

2008-12-01

Full Text Available So far, various addressing and routing algorithms have been extensively studied for wireless sensor networks (WSNs, but many of them were limited to cover less than hundreds of sensor nodes. It is largely due to stringent requirements for fully distributed coordination among sensor nodes, leading to the wasteful use of available address space. As there is a growing need for a large-scale WSN, it will be extremely challenging to support more than thousands of nodes, using existing standard bodies. Moreover, it is highly unlikely to change the existing standards, primarily due to backward compatibility issue. In response, we propose an elegant addressing scheme and its routing algorithm. While maintaining the existing address scheme, it tackles the wastage problem and achieves no additional memory storage during a routing. We also present an adaptive routing algorithm for location-aware applications, using our addressing scheme. Through a series of simulations, we prove that our approach can achieve two times lesser routing time than the existing standard in a ZigBee network.

Vision-based vehicle detection and tracking algorithm design

Science.gov (United States)

Hwang, Junyeon; Huh, Kunsoo; Lee, Donghwi

2009-12-01

The vision-based vehicle detection in front of an ego-vehicle is regarded as promising for driver assistance as well as for autonomous vehicle guidance. The feasibility of vehicle detection in a passenger car requires accurate and robust sensing performance. A multivehicle detection system based on stereo vision has been developed for better accuracy and robustness. This system utilizes morphological filter, feature detector, template matching, and epipolar constraint techniques in order to detect the corresponding pairs of vehicles. After the initial detection, the system executes the tracking algorithm for the vehicles. The proposed system can detect front vehicles such as the leading vehicle and side-lane vehicles. The position parameters of the vehicles located in front are obtained based on the detection information. The proposed vehicle detection system is implemented on a passenger car, and its performance is verified experimentally.

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.

Hyperspectral Vehicle BRDF Learning: An Exploration of Vehicle Reflectance Variation and Optimal Measures of Spectral Similarity for Vehicle Reacquisition and Tracking Algorithms

Science.gov (United States)

Svejkosky, Joseph

The spectral signatures of vehicles in hyperspectral imagery exhibit temporal variations due to the preponderance of surfaces with material properties that display non-Lambertian bi-directional reflectance distribution functions (BRDFs). These temporal variations are caused by changing illumination conditions, changing sun-target-sensor geometry, changing road surface properties, and changing vehicle orientations. To quantify these variations and determine their relative importance in a sub-pixel vehicle reacquisition and tracking scenario, a hyperspectral vehicle BRDF sampling experiment was conducted in which four vehicles were rotated at different orientations and imaged over a six-hour period. The hyperspectral imagery was calibrated using novel in-scene methods and converted to reflectance imagery. The resulting BRDF sampled time-series imagery showed a strong vehicle level BRDF dependence on vehicle shape in off-nadir imaging scenarios and a strong dependence on vehicle color in simulated nadir imaging scenarios. The imagery also exhibited spectral features characteristic of sampling the BRDF of non-Lambertian targets, which were subsequently verified with simulations. In addition, the imagery demonstrated that the illumination contribution from vehicle adjacent horizontal surfaces significantly altered the shape and magnitude of the vehicle reflectance spectrum. The results of the BRDF sampling experiment illustrate the need for a target vehicle BRDF model and detection scheme that incorporates non-Lambertian BRDFs. A new detection algorithm called Eigenvector Loading Regression (ELR) is proposed that learns a hyperspectral vehicle BRDF from a series of BRDF measurements using regression in a lower dimensional space and then applies the learned BRDF to make test spectrum predictions. In cases of non-Lambertian vehicle BRDF, this detection methodology performs favorably when compared to subspace detections algorithms and graph-based detection algorithms that

Solving Inventory Routing Problems Using Location Based Heuristics

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Paweł Hanczar

2014-01-01

Full Text Available Inventory routing problems (IRPs occur where vendor managed inventory replenishment strategies are implemented in supply chains. These problems are characterized by the presence of both transportation and inventory considerations, either as parameters or constraints. The research presented in this paper aims at extending IRP formulation developed on the basis of location based heuristics proposed by Bramel and Simchi-Levi and continued by Hanczar. In the first phase of proposed algorithms, mixed integer programming is used to determine the partitioning of customers as well as dates and quantities of deliveries. Then, using 2-opt algorithm for solving the traveling sales-person problem the optimal routes for each partition are determined. In the main part of research the classical formulation is extended by additional constraints (visit spacing, vehicle filling rate, driver (vehicle consistency, and heterogeneous fleet of vehicles as well as the additional criteria are discussed. Then the impact of using each of proposed extensions for solution possibilities is evaluated. The results of computational tests are presented and discussed. Obtained results allow to conclude that the location based heuristics should be considered when solving real life instances of IRP. (original abstract

Series Hybrid Electric Vehicle Power System Optimization Based on Genetic Algorithm

Science.gov (United States)

Zhu, Tianjun; Li, Bin; Zong, Changfu; Wu, Yang

2017-09-01

Hybrid electric vehicles (HEV), compared with conventional vehicles, have complex structures and more component parameters. If variables optimization designs are carried on all these parameters, it will increase the difficulty and the convergence of algorithm program, so this paper chooses the parameters which has a major influence on the vehicle fuel consumption to make it all work at maximum efficiency. First, HEV powertrain components modelling are built. Second, taking a tandem hybrid structure as an example, genetic algorithm is used in this paper to optimize fuel consumption and emissions. Simulation results in ADVISOR verify the feasibility of the proposed genetic optimization algorithm.

Dynamic Routing of Short Transfer Baggage

DEFF Research Database (Denmark)

Clausen, Tommy; Pisinger, David

of dispatch. Computational results are presented for real-life passenger data with stochastic bag arrival times and travel times. The results indicate that the algorithm is able to dispatch the baggage considerably better than the manual delivery plans reported in the case study, and due to its fast running...... that arrive continuously during the day. We present an IP model of the problem and describe the problem as a case study from a real life setting. We present a weighted greedy algorithm for dispatching vehicles that works in an dynamic context, meaning that it only considers bags available at the time......We consider a variant of the Vehicle Routing Problem that arises in airports when transporting baggage for passengers with connecting flights. Each bag can be delivered in two locations with disjunctive time windows. The task is to define multiple trips for the vehicles in order to deliver bags...

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.

DEHAR: a Distributed Energy Harvesting Aware Routing Algorithm for Ad-hoc Multi-hop Wireless Sensor Networks

DEFF Research Database (Denmark)

Jakobsen, Mikkel Koefoed; Madsen, Jan; Hansen, Michael Reichhardt

2010-01-01

One of the key design goals in Wireless Sensor Networks is long lasting or even continuous operation. Continuous operation is made possible through energy harvesting. Keeping the network operational imposes a demand to prevent network segmentation and power loss in nodes. It is therefore important...... that the best energy-wise route is found for each data transfer from a source node to the sink node. We present a new adaptive and distributed routing algorithm for finding energy optimised routes in a wireless sensor network with energy harvesting. The algorithm finds an energy efficient route from each source...

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.

A human-machine cooperation route planning method based on improved A* algorithm

Science.gov (United States)

Zhang, Zhengsheng; Cai, Chao

2011-12-01

To avoid the limitation of common route planning method to blindly pursue higher Machine Intelligence and autoimmunization, this paper presents a human-machine cooperation route planning method. The proposed method includes a new A* path searing strategy based on dynamic heuristic searching and a human cooperated decision strategy to prune searching area. It can overcome the shortage of A* algorithm to fall into a local long term searching. Experiments showed that this method can quickly plan a feasible route to meet the macro-policy thinking.

Path Planning Algorithms for Autonomous Border Patrol Vehicles

Science.gov (United States)

Lau, George Tin Lam

This thesis presents an online path planning algorithm developed for unmanned vehicles in charge of autonomous border patrol. In this Pursuit-Evasion game, the unmanned vehicle is required to capture multiple trespassers on its own before any of them reach a target safe house where they are safe from capture. The problem formulation is based on Isaacs' Target Guarding problem, but extended to the case of multiple evaders. The proposed path planning method is based on Rapidly-exploring random trees (RRT) and is capable of producing trajectories within several seconds to capture 2 or 3 evaders. Simulations are carried out to demonstrate that the resulting trajectories approach the optimal solution produced by a nonlinear programming-based numerical optimal control solver. Experiments are also conducted on unmanned ground vehicles to show the feasibility of implementing the proposed online path planning algorithm on physical applications.

Energy Efficiency Performance Improvements for Ant-Based Routing Algorithm in Wireless Sensor Networks

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Adamu Murtala Zungeru

2013-01-01

Full Text Available The main problem for event gathering in wireless sensor networks (WSNs is the restricted communication range for each node. Due to the restricted communication range and high network density, event forwarding in WSNs is very challenging and requires multihop data forwarding. Currently, the energy-efficient ant based routing (EEABR algorithm, based on the ant colony optimization (ACO metaheuristic, is one of the state-of-the-art energy-aware routing protocols. In this paper, we propose three improvements to the EEABR algorithm to further improve its energy efficiency. The improvements to the original EEABR are based on the following: (1 a new scheme to intelligently initialize the routing tables giving priority to neighboring nodes that simultaneously could be the destination, (2 intelligent update of routing tables in case of a node or link failure, and (3 reducing the flooding ability of ants for congestion control. The energy efficiency improvements are significant particularly for dynamic routing environments. Experimental results using the RMASE simulation environment show that the proposed method increases the energy efficiency by up to 9% and 64% in converge-cast and target-tracking scenarios, respectively, over the original EEABR without incurring a significant increase in complexity. The method is also compared and found to also outperform other swarm-based routing protocols such as sensor-driven and cost-aware ant routing (SC and Beesensor.

Capacitated Hub Routing Problem in Hub-and-Feeder Network Design: Modeling and Solution Algorithm

OpenAIRE

Gelareh , Shahin; Neamatian Monemi , Rahimeh; Semet , Frédéric

2015-01-01

International audience; In this paper, we address the Bounded Cardinality Hub Location Routing with Route Capacity wherein eachhub acts as a transshipment node for one directed route. The number of hubs lies between a minimum anda maximum and the hub-level network is a complete subgraph. The transshipment operations take place atthe hub nodes and flow transfer time from a hub-level transporter to a spoke-level vehicle influences spoketo-hub allocations. We propose a mathematical model and a b...

An innovative localisation algorithm for railway vehicles

Science.gov (United States)

Allotta, B.; D'Adamio, P.; Malvezzi, M.; Pugi, L.; Ridolfi, A.; Rindi, A.; Vettori, G.

2014-11-01

In modern railway automatic train protection and automatic train control systems, odometry is a safety relevant on-board subsystem which estimates the instantaneous speed and the travelled distance of the train; a high reliability of the odometry estimate is fundamental, since an error on the train position may lead to a potentially dangerous overestimation of the distance available for braking. To improve the odometry estimate accuracy, data fusion of different inputs coming from a redundant sensor layout may be used. The aim of this work has been developing an innovative localisation algorithm for railway vehicles able to enhance the performances, in terms of speed and position estimation accuracy, of the classical odometry algorithms, such as the Italian Sistema Controllo Marcia Treno (SCMT). The proposed strategy consists of a sensor fusion between the information coming from a tachometer and an Inertial Measurements Unit (IMU). The sensor outputs have been simulated through a 3D multibody model of a railway vehicle. The work has provided the development of a custom IMU, designed by ECM S.p.a, in order to meet their industrial and business requirements. The industrial requirements have to be compliant with the European Train Control System (ETCS) standards: the European Rail Traffic Management System (ERTMS), a project developed by the European Union to improve the interoperability among different countries, in particular as regards the train control and command systems, fixes some standard values for the odometric (ODO) performance, in terms of speed and travelled distance estimation. The reliability of the ODO estimation has to be taken into account basing on the allowed speed profiles. The results of the currently used ODO algorithms can be improved, especially in case of degraded adhesion conditions; it has been verified in the simulation environment that the results of the proposed localisation algorithm are always compliant with the ERTMS requirements

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.

The Social Relationship Based Adaptive Multi-Spray-and-Wait Routing Algorithm for Disruption Tolerant Network

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Jianfeng Guan

2017-01-01

Full Text Available The existing spray-based routing algorithms in DTN cannot dynamically adjust the number of message copies based on actual conditions, which results in a waste of resource and a reduction of the message delivery rate. Besides, the existing spray-based routing protocols may result in blind spots or dead end problems due to the limitation of various given metrics. Therefore, this paper proposes a social relationship based adaptive multiple spray-and-wait routing algorithm (called SRAMSW which retransmits the message copies based on their residence times in the node via buffer management and selects forwarders based on the social relationship. By these means, the proposed algorithm can remove the plight of the message congestion in the buffer and improve the probability of replicas to reach their destinations. The simulation results under different scenarios show that the SRAMSW algorithm can improve the message delivery rate and reduce the messages’ dwell time in the cache and further improve the buffer effectively.

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.

A Dynamic Travel Time Estimation Model Based on Connected Vehicles

Directory of Open Access Journals (Sweden)

Daxin Tian

2015-01-01

Full Text Available With advances in connected vehicle technology, dynamic vehicle route guidance models gradually become indispensable equipment for drivers. Traditional route guidance models are designed to direct a vehicle along the shortest path from the origin to the destination without considering the dynamic traffic information. In this paper a dynamic travel time estimation model is presented which can collect and distribute traffic data based on the connected vehicles. To estimate the real-time travel time more accurately, a road link dynamic dividing algorithm is proposed. The efficiency of the model is confirmed by simulations, and the experiment results prove the effectiveness of the travel time estimation method.

DATA-ORIENTED ALGORITHM FOR ROUTE CHOICE SET GENERATION IN A METROPOLITAN AREA WITH MOBILE PHONE GPS DATA

Directory of Open Access Journals (Sweden)

T. Nakamura

2012-07-01

Full Text Available Nowadays, for the estimation of traffic demand or people flow, modelling route choice activity in road networks is an important task and many algorithms have been developed to generate route choice sets. However, developing an algorithm based on a small amount of data that can be applied generally within a metropolitan area is difficult. This is because the characteristics of road networks vary widely. On the other hand, recently, the collection of people movement data has lately become much easier, especially through mobile phones. Lately, most mobile phones include GPS functionality. Given this background, we propose a data-oriented algorithm to generate route choice sets using mobile phone GPS data. GPS data contain a number of measurement errors; hence, they must be adjusted to account for these errors before use in advanced people movement analysis. However, this is time-consuming and expensive, because an enormous amount of daily data can be obtained. Hence, the objective of this study is to develop an algorithm that can easily manage GPS data. Specifically, at first movement data from all GPS data are selected by calculating the speed. Next, the nearest roads in the road network are selected from the GPS location and count such data for each road. Then An algorithm based on the GSP (Gateway Shortest Path algorithm is proposed, which searches the shortest path through a given gateway. In the proposed algorithm, the road for which the utilization volume calculated by GPS data is large is selected as the gateway. Thus, route choice sets that are based on trends in real GPS data are generated. To evaluate the proposed method, GPS data from 0.7 million people a year in Japan and DRM (Digital Road Map as the road network are used. DRM is one of the most detailed road networks in Japan. Route choice sets using the proposed algorithm are generated and the cover rate of the utilization volume of each road under evaluation is calculated. As a

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.

Night-Time Vehicle Detection Algorithm Based on Visual Saliency and Deep Learning

Directory of Open Access Journals (Sweden)

Yingfeng Cai

2016-01-01

Full Text Available Night vision systems get more and more attention in the field of automotive active safety field. In this area, a number of researchers have proposed far-infrared sensor based night-time vehicle detection algorithm. However, existing algorithms have low performance in some indicators such as the detection rate and processing time. To solve this problem, we propose a far-infrared image vehicle detection algorithm based on visual saliency and deep learning. Firstly, most of the nonvehicle pixels will be removed with visual saliency computation. Then, vehicle candidate will be generated by using prior information such as camera parameters and vehicle size. Finally, classifier trained with deep belief networks will be applied to verify the candidates generated in last step. The proposed algorithm is tested in around 6000 images and achieves detection rate of 92.3% and processing time of 25 Hz which is better than existing methods.

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.

Cone Algorithm of Spinning Vehicles under Dynamic Coning Environment

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Shuang-biao Zhang

2015-01-01

Full Text Available Due to the fact that attitude error of vehicles has an intense trend of divergence when vehicles undergo worsening coning environment, in this paper, the model of dynamic coning environment is derived firstly. Then, through investigation of the effect on Euler attitude algorithm for the equivalency of traditional attitude algorithm, it is found that attitude error is actually the roll angle error including drifting error and oscillating error, which is induced directly by dynamic coning environment and further affects the pitch angle and yaw angle through transferring. Based on definition of the cone frame and cone attitude, a cone algorithm is proposed by rotation relationship to calculate cone attitude, and the relationship between cone attitude and Euler attitude of spinning vehicle is established. Through numerical simulations with different conditions of dynamic coning environment, it is shown that the induced error of Euler attitude fluctuates by the variation of precession and nutation, especially by that of nutation, and the oscillating frequency of roll angle error is twice that of pitch angle error and yaw angle error. In addition, the rotation angle is more competent to describe the spinning process of vehicles under coning environment than Euler angle gamma, and the real pitch angle and yaw angle are calculated finally.

Design Optimization of Space Launch Vehicles Using a Genetic Algorithm

National Research Council Canada - National Science Library

Bayley, Douglas J

2007-01-01

.... A genetic algorithm (GA) was employed to optimize the design of the space launch vehicle. A cost model was incorporated into the optimization process with the goal of minimizing the overall vehicle cost...

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

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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

A variable neighborhood descent based heuristic to solve the capacitated location-routing problem

Directory of Open Access Journals (Sweden)

M. S. Jabal-Ameli

2011-01-01

Full Text Available Location-routing problem (LRP is established as a new research area in the context of location analysis. The primary concern of LRP is on locating facilities and routing of vehicles among established facilities and existing demand points. In this work, we address the capacitated LRP which arises in many practical applications within logistics and supply chain management. The objective is to minimize the overall system costs which include the fixed costs of opening depots and using vehicles at each depot site, and the variable costs associated with delivery activities. A novel heuristic is proposed which is based on variable neighborhood descent (VND algorithm to solve the resulted problem. The computational study indicates that the proposed VND based heuristic is highly competitive with the existing solution algorithms in terms of solution quality.

An optimal control-based algorithm for hybrid electric vehicle using preview route information

NARCIS (Netherlands)

Ngo, D.V.; Hofman, T.; Steinbuch, M.; Serrarens, A.F.A.

2010-01-01

Control strategies for Hybrid Electric Vehicles (HEVs) are generally aimed at optimally choosing the power distribution between the internal combustion engine and the electric motor in order to minimize the fuel consumption and/or emissions. Using vehicle navigation systems in combination with

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.

Shockwave-Based Automated Vehicle Longitudinal Control Algorithm for Nonrecurrent Congestion Mitigation

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Liuhui Zhao

2017-01-01

Full Text Available A shockwave-based speed harmonization algorithm for the longitudinal movement of automated vehicles is presented in this paper. In the advent of Connected/Automated Vehicle (C/AV environment, the proposed algorithm can be applied to capture instantaneous shockwaves constructed from vehicular speed profiles shared by individual equipped vehicles. With a continuous wavelet transform (CWT method, the algorithm detects abnormal speed drops in real-time and optimizes speed to prevent the shockwave propagating to the upstream traffic. A traffic simulation model is calibrated to evaluate the applicability and efficiency of the proposed algorithm. Based on 100% C/AV market penetration, the simulation results show that the CWT-based algorithm accurately detects abnormal speed drops. With the improved accuracy of abnormal speed drop detection, the simulation results also demonstrate that the congestion can be mitigated by reducing travel time and delay up to approximately 9% and 18%, respectively. It is also found that the shockwave caused by nonrecurrent congestion is quickly dissipated even with low market penetration.

Application of Fuzzy Sets for the Improvement of Routing Optimization Heuristic Algorithms

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Mattas Konstantinos

2016-12-01

Full Text Available The determination of the optimal circular path has become widely known for its difficulty in producing a solution and for the numerous applications in the scope of organization and management of passenger and freight transport. It is a mathematical combinatorial optimization problem for which several deterministic and heuristic models have been developed in recent years, applicable to route organization issues, passenger and freight transport, storage and distribution of goods, waste collection, supply and control of terminals, as well as human resource management. Scope of the present paper is the development, with the use of fuzzy sets, of a practical, comprehensible and speedy heuristic algorithm for the improvement of the ability of the classical deterministic algorithms to identify optimum, symmetrical or non-symmetrical, circular route. The proposed fuzzy heuristic algorithm is compared to the corresponding deterministic ones, with regard to the deviation of the proposed solution from the best known solution and the complexity of the calculations needed to obtain this solution. It is shown that the use of fuzzy sets reduced up to 35% the deviation of the solution identified by the classical deterministic algorithms from the best known solution.

Research on vehicles and cargos matching model based on virtual logistics platform

Science.gov (United States)

Zhuang, Yufeng; Lu, Jiang; Su, Zhiyuan

2018-04-01

Highway less than truckload (LTL) transportation vehicles and cargos matching problem is a joint optimization problem of typical vehicle routing and loading, which is also a hot issue of operational research. This article based on the demand of virtual logistics platform, for the problem of the highway LTL transportation, the matching model of the idle vehicle and the transportation order is set up and the corresponding genetic algorithm is designed. Then the algorithm is implemented by Java. The simulation results show that the solution is satisfactory.

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...

Algorithm of Particle Data Association for SLAM Based on Improved Ant Algorithm

Directory of Open Access Journals (Sweden)

KeKe Gen

2015-01-01

Full Text Available The article considers a problem of data association algorithm for simultaneous localization and mapping guidelines in determining the route of unmanned aerial vehicles (UAVs. Currently, these equipments are already widely used, but mainly controlled from the remote operator. An urgent task is to develop a control system that allows for autonomous flight. Algorithm SLAM (simultaneous localization and mapping, which allows to predict the location, speed, the ratio of flight parameters and the coordinates of landmarks and obstacles in an unknown environment, is one of the key technologies to achieve real autonomous UAV flight. The aim of this work is to study the possibility of solving this problem by using an improved ant algorithm.The data association for SLAM algorithm is meant to establish a matching set of observed landmarks and landmarks in the state vector. Ant algorithm is one of the widely used optimization algorithms with positive feedback and the ability to search in parallel, so the algorithm is suitable for solving the problem of data association for SLAM. But the traditional ant algorithm in the process of finding routes easily falls into local optimum. Adding random perturbations in the process of updating the global pheromone to avoid local optima. Setting limits pheromone on the route can increase the search space with a reasonable amount of calculations for finding the optimal route.The paper proposes an algorithm of the local data association for SLAM algorithm based on an improved ant algorithm. To increase the speed of calculation, local data association is used instead of the global data association. The first stage of the algorithm defines targets in the matching space and the observed landmarks with the possibility of association by the criterion of individual compatibility (IC. The second stage defines the matched landmarks and their coordinates using improved ant algorithm. Simulation results confirm the efficiency and

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

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...

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

Research on Innovating, Applying Multiple Paths Routing Technique Based on Fuzzy Logic and Genetic Algorithm for Routing Messages in Service - Oriented Routing

Directory of Open Access Journals (Sweden)

Nguyen Thanh Long

2015-02-01

Full Text Available MANET (short for Mobile Ad-Hoc Network consists of a set of mobile network nodes, network configuration changes very fast. In content based routing, data is transferred from source node to request nodes is not based on destination addresses. Therefore, it is very flexible and reliable, because source node does not need to know destination nodes. If We can find multiple paths that satisfies bandwidth requirement, split the original message into multiple smaller messages to transmit concurrently on these paths. On destination nodes, combine separated messages into the original message. Hence it can utilize better network resources, causes data transfer rate to be higher, load balancing, failover. Service Oriented Routing is inherited from the model of content based routing (CBR, combined with several advanced techniques such as Multicast, multiple path routing, Genetic algorithm to increase the data rate, and data encryption to ensure information security. Fuzzy logic is a logical field study evaluating the accuracy of the results based on the approximation of the components involved, make decisions based on many factors relative accuracy based on experimental or mathematical proof. This article presents some techniques to support multiple path routing from one network node to a set of nodes with guaranteed quality of service. By using these techniques can decrease the network load, congestion, use network resources efficiently.

Location and multi-depot vehicle routing for emergency vehicles using tour coverage and random sampling

Directory of Open Access Journals (Sweden)

Alireza Goli

2015-09-01

Full Text Available Distribution and optimum allocation of emergency resources are the most important tasks, which need to be accomplished during crisis. When a natural disaster such as earthquake, flood, etc. takes place, it is necessary to deliver rescue efforts as quickly as possible. Therefore, it is important to find optimum location and distribution of emergency relief resources. When a natural disaster occurs, it is not possible to reach some damaged areas. In this paper, location and multi-depot vehicle routing for emergency vehicles using tour coverage and random sampling is investigated. In this study, there is no need to visit all the places and some demand points receive their needs from the nearest possible location. The proposed study is implemented for some randomly generated numbers in different sizes. The preliminary results indicate that the proposed method was capable of reaching desirable solutions in reasonable amount of time.

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.

An Optimization Routing Algorithm for Green Communication in Underground Mines

Directory of Open Access Journals (Sweden)

Heng Xu

2018-06-01

Full Text Available With the long-term dependence of humans on ore-based energy, underground mines are utilized around the world, and underground mining is often dangerous. Therefore, many underground mines have established networks that manage and acquire information from sensor nodes deployed on miners and in other places. Since the power supplies of many mobile sensor nodes are batteries, green communication is an effective approach of reducing the energy consumption of a network and extending its longevity. To reduce the energy consumption of networks, all factors that negatively influence the lifetime should be considered. The degree constraint minimum spanning tree (DCMST is introduced in this study to consider all the heterogeneous factors and assign weights for the next step of the evaluation. Then, a genetic algorithm (GA is introduced to cluster sensor nodes in the network and balance energy consumption according to several heterogeneous factors and routing paths from DCMST. Based on a comparison of the simulation results, the optimization routing algorithm proposed in this study for use in green communication in underground mines can effectively reduce the network energy consumption and extend the lifetimes of networks.

Improving Transportation Services for the University of the Thai Chamber of Commerce: A Case Study on Solving the Mixed-Fleet Vehicle Routing Problem with Split Deliveries

Science.gov (United States)

Suthikarnnarunai, N.; Olinick, E.

2009-01-01

We present a case study on the application of techniques for solving the Vehicle Routing Problem (VRP) to improve the transportation service provided by the University of The Thai Chamber of Commerce to its staff. The problem is modeled as VRP with time windows, split deliveries, and a mixed fleet. An exact algorithm and a heuristic solution procedure are developed to solve the problem and implemented in the AMPL modeling language and CPLEX Integer Programming solver. Empirical results indicate that the heuristic can find relatively good solutions in a small fraction of the time required by the exact method. We also perform sensitivity analysis and find that a savings in outsourcing cost can be achieved with a small increase in vehicle capacity.

Using virtual environment for autonomous vehicle algorithm validation

Science.gov (United States)

Levinskis, Aleksandrs

2018-04-01

This paper describes possible use of modern game engine for validating and proving the concept of algorithm design. As the result simple visual odometry algorithm will be provided to show the concept and go over all workflow stages. Some of stages will involve using of Kalman filter in such a way that it will estimate optical flow velocity as well as position of moving camera located at vehicle body. In particular Unreal Engine 4 game engine will be used for generating optical flow patterns and ground truth path. For optical flow determination Horn and Schunck method will be applied. As the result, it will be shown that such method can estimate position of the camera attached to vehicle with certain displacement error respect to ground truth depending on optical flow pattern. For displacement rate RMS error is calculating between estimated and actual position.

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.

A multicast tree aggregation algorithm in wavelength-routed WDM networks

Science.gov (United States)

Cheng, Hsu-Chen; Kuo, Chin-Chun; Lin, Frank Y.

2005-02-01

Wavelength division multiplexing (WDM) has been considered a promising transmission technology in optical communication networks. With the continuous advance in optical technology, WDM network will play an important role in wide area backbone networks. Optical wavelength switching, compared with optical packet switching, is a more mature and more cost-effective choice for optical switching technologies. Besides, the technology of time division multiplexing in optical communication networks has been working smoothly for a long time. In the proposed research, the problem of multicast groups aggregation and multicast routing and wavelength assignment in wavelength-routed WDM network is studied. The optical cross connect switches in the problem are assumed to have limited optical multicast/splitting and TDM functionalities. Given the physical network topology and capacity, the objective is to maximize the total revenue by means of utmost merging multicast groups into larger macro-groups. The groups in the same macro-group will share a multicast tree to conduct data transmission. The problem is formulated as an optimization problem, where the objective function is to maximize the total revenue subject to capacity constraints of components in the optical network, wavelength continuity constraints, and tree topology constraints. The decision variables in the formulations include the merging results between groups, multicast tree routing assignment and wavelength assignment. The basic approach to the algorithm development for this model is Lagrangean relaxation in conjunction with a number of optimization techniques. In computational experiments, the proposed algorithms are evaluated on different network topologies and perform efficiently and effectively according to the experiment results.

Multidepot UAV Routing Problem with Weapon Configuration and Time Window

Directory of Open Access Journals (Sweden)

Tianren Zhou

2018-01-01

Full Text Available In recent wars, there is an increasing trend that unmanned aerial vehicles (UAVs are utilized to conduct military attacking missions. In this paper, we investigate a novel multidepot UAV routing problem with consideration of weapon configuration in the UAV and the attacking time window of the target. A mixed-integer linear programming model is developed to jointly optimize three kinds of decisions: the weapon configuration strategy in the UAV, the routing strategy of target, and the allocation strategy of weapons to targets. An adaptive large neighborhood search (ALNS algorithm is proposed for solving the problem, which is tested by randomly generated instances covering the small, medium, and large sizes. Experimental results confirm the effectiveness and robustness of the proposed ALNS algorithm.

On-demand high-capacity ride-sharing via dynamic trip-vehicle assignment.

Science.gov (United States)

Alonso-Mora, Javier; Samaranayake, Samitha; Wallar, Alex; Frazzoli, Emilio; Rus, Daniela

2017-01-17

Ride-sharing services are transforming urban mobility by providing timely and convenient transportation to anybody, anywhere, and anytime. These services present enormous potential for positive societal impacts with respect to pollution, energy consumption, congestion, etc. Current mathematical models, however, do not fully address the potential of ride-sharing. Recently, a large-scale study highlighted some of the benefits of car pooling but was limited to static routes with two riders per vehicle (optimally) or three (with heuristics). We present a more general mathematical model for real-time high-capacity ride-sharing that (i) scales to large numbers of passengers and trips and (ii) dynamically generates optimal routes with respect to online demand and vehicle locations. The algorithm starts from a greedy assignment and improves it through a constrained optimization, quickly returning solutions of good quality and converging to the optimal assignment over time. We quantify experimentally the tradeoff between fleet size, capacity, waiting time, travel delay, and operational costs for low- to medium-capacity vehicles, such as taxis and van shuttles. The algorithm is validated with ∼3 million rides extracted from the New York City taxicab public dataset. Our experimental study considers ride-sharing with rider capacity of up to 10 simultaneous passengers per vehicle. The algorithm applies to fleets of autonomous vehicles and also incorporates rebalancing of idling vehicles to areas of high demand. This framework is general and can be used for many real-time multivehicle, multitask assignment problems.

A social activity and physical contact-based routing algorithm in mobile opportunistic networks for emergency response to sudden disasters

Science.gov (United States)

Wang, Xiaoming; Lin, Yaguang; Zhang, Shanshan; Cai, Zhipeng

2017-05-01

Sudden disasters such as earthquake, flood and hurricane necessitate the employment of communication networks to carry out emergency response activities. Routing has a significant impact on the functionality, performance and flexibility of communication networks. In this article, the routing problem is studied considering the delivery ratio of messages, the overhead ratio of messages and the average delay of messages in mobile opportunistic networks (MONs) for enterprise-level emergency response communications in sudden disaster scenarios. Unlike the traditional routing methods for MONS, this article presents a new two-stage spreading and forwarding dynamic routing algorithm based on the proposed social activity degree and physical contact factor for mobile customers. A new modelling method for describing a dynamic evolving process of the topology structure of a MON is first proposed. Then a multi-copy spreading strategy based on the social activity degree of nodes and a single-copy forwarding strategy based on the physical contact factor between nodes are designed. Compared with the most relevant routing algorithms such as Epidemic, Prophet, Labelled-sim, Dlife-comm and Distribute-sim, the proposed routing algorithm can significantly increase the delivery ratio of messages, and decrease the overhead ratio and average delay of messages.

The Effects of the Tractor and Semitrailer Routing Problem on Mitigation of Carbon Dioxide Emissions

Directory of Open Access Journals (Sweden)

Hongqi Li

2013-01-01

Full Text Available The incorporation of CO2 emissions minimization in the vehicle routing problem (VRP is of critical importance to enterprise practice. Focusing on the tractor and semitrailer routing problem with full truckloads between any two terminals of the network, this paper proposes a mathematical programming model with the objective of minimizing CO2 emissions per ton-kilometer. A simulated annealing (SA algorithm is given to solve practical-scale problems. To evaluate the performance of the proposed algorithm, a lower bound is developed. Computational experiments on various problems generated randomly and a realistic instance are conducted. The results show that the proposed methods are effective and the algorithm can provide reasonable solutions within an acceptable computational time.

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.

Learning Mobility: Adaptive Control Algorithms for the Novel Unmanned Ground Vehicle (NUGV)

National Research Council Canada - National Science Library

Blackburn, Mike

2003-01-01

Mobility is a serious limiting factor in the usefulness of unmanned ground vehicles, This paper contains a description of our approach to develop control algorithms for the Novel Unmanned Ground Vehicle (NUGV...

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

Simulated annealing with restart strategy for the blood pickup routing problem

Science.gov (United States)

Yu, V. F.; Iswari, T.; Normasari, N. M. E.; Asih, A. M. S.; Ting, H.

2018-04-01

This study develops a simulated annealing heuristic with restart strategy (SA_RS) for solving the blood pickup routing problem (BPRP). BPRP minimizes the total length of the routes for blood bag collection between a blood bank and a set of donation sites, each associated with a time window constraint that must be observed. The proposed SA_RS is implemented in C++ and tested on benchmark instances of the vehicle routing problem with time windows to verify its performance. The algorithm is then tested on some newly generated BPRP instances and the results are compared with those obtained by CPLEX. Experimental results show that the proposed SA_RS heuristic effectively solves BPRP.

Solving the Dial-a-Ride Problem using Genetic algorithms

DEFF Research Database (Denmark)

Bergvinsdottir, Kristin Berg; Larsen, Jesper; Jørgensen, Rene Munk

In the Dial-a-Ride problem (DARP) customers send transportation requests to an operator. A request consists of a specified pickup location and destination location along with a desired departure or arrival time and demand. The aim of DARP is to minimize transportation cost while satisfying custom...... routing problems for the vehicles using a routing heuristic. The algorithm is implemented in Java and tested on publicly available data sets....

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.

ON THE USE OF LYTLE’S ALGORITHM FOR SOLVING TRAVELING SALESMAN PROBLEM AT DEVELOPING SUBURBAN ROUTE

Directory of Open Access Journals (Sweden)

S. Kantsedal

2012-01-01

Full Text Available Lytle’s algorithm is described as proposed for an accurate solution of the salesman Problem. Statistical characteristics of solution duration with lytle’s algorithm of some problems and of their modifications are specified. On the basis of the results obtained the limits for the algorithm practical specification in the preparation of the route network are given.

DESIGNING DAILY PATROL ROUTES FOR POLICING BASED ON ANT COLONY ALGORITHM

Directory of Open Access Journals (Sweden)

H. Chen

2015-07-01

Full Text Available In this paper, we address the problem of planning police patrol routes to regularly cover street segments of high crime density (hotspots with limited police forces. A good patrolling strategy is required to minimise the average time lag between two consecutive visits to hotspots, as well as coordinating multiple patrollers and imparting unpredictability in patrol routes. Previous studies have designed different police patrol strategies for routing police patrol, but these strategies have difficulty in generalising to real patrolling and meeting various requirements. In this research we develop a new police patrolling strategy based on Bayesian method and ant colony algorithm. In this strategy, virtual marker (pheromone is laid to mark the visiting history of each crime hotspot, and patrollers continuously decide which hotspot to patrol next based on pheromone level and other variables. Simulation results using real data testifies the effective, scalable, unpredictable and extensible nature of this strategy.

A New Algorithm for ABS/GPS Integration Based on Fuzzy-Logic in Vehicle Navigation System

Directory of Open Access Journals (Sweden)

Ali Amin Zadeh

2011-10-01

Full Text Available GPS based vehicle navigation systems have difficulties in tracking vehicles in urban canyons due to poor satellite availability. ABS (Antilock Brake System Navigation System consists of self-contained optical encoders mounted on vehicle wheels that can continuously provide accurate short-term positioning information. In this paper, a new concept regarding GPS/ABS integration, based on Fuzzy Logic is presented. The proposed algorithm is used to identify GPS position accuracy based on environment and vehicle dynamic knowledge. The GPS is used as reference during the time it is in a good condition and replaced by ABS positioning system when GPS information is unreliable. We compare our proposed algorithm with other common algorithm in real environment. Our results show that the proposed algorithm can significantly improve the stability and reliability of ABS/GPS navigation system.

An Immune Cooperative Particle Swarm Optimization Algorithm for Fault-Tolerant Routing Optimization in Heterogeneous Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Yifan Hu

2012-01-01

Full Text Available The fault-tolerant routing problem is important consideration in the design of heterogeneous wireless sensor networks (H-WSNs applications, and has recently been attracting growing research interests. In order to maintain k disjoint communication paths from source sensors to the macronodes, we present a hybrid routing scheme and model, in which multiple paths are calculated and maintained in advance, and alternate paths are created once the previous routing is broken. Then, we propose an immune cooperative particle swarm optimization algorithm (ICPSOA in the model to provide the fast routing recovery and reconstruct the network topology for path failure in H-WSNs. In the ICPSOA, mutation direction of the particle is determined by multi-swarm evolution equation, and its diversity is improved by immune mechanism, which can enhance the capacity of global search and improve the converging rate of the algorithm. Then we validate this theoretical model with simulation results. The results indicate that the ICPSOA-based fault-tolerant routing protocol outperforms several other protocols due to its capability of fast routing recovery mechanism, reliable communications, and prolonging the lifetime of WSNs.

Electric vehicle charging algorithms for coordination of the grid and distribution transformer levels

International Nuclear Information System (INIS)

Ramos Muñoz, Edgar; Razeghi, Ghazal; Zhang, Li; Jabbari, Faryar

2016-01-01

The need to reduce greenhouse gas emissions and fossil fuel consumption has increased the popularity of plug-in electric vehicles. However, a large penetration of plug-in electric vehicles can pose challenges at the grid and local distribution levels. Various charging strategies have been proposed to address such challenges, often separately. In this paper, it is shown that, with uncoordinated charging, distribution transformers and the grid can operate under highly undesirable conditions. Next, several strategies that require modest communication efforts are proposed to mitigate the burden created by high concentrations of plug-in electric vehicles, at the grid and local levels. Existing transformer and battery electric vehicle characteristics are used along with the National Household Travel Survey to simulate various charging strategies. It is shown through the analysis of hot spot temperature and equivalent aging factor that the coordinated strategies proposed here reduce the chances of transformer failure with the addition of plug-in electric vehicle loads, even for an under-designed transformer while uncontrolled and uncoordinated plug-in electric vehicle charging results in increased risk of transformer failure. - Highlights: • Charging algorithm for battery electric vehicles, for high penetration levels. • Algorithm reduces transformer overloading, for grid level valley filling. • Computation and communication requirements are minimal. • The distributed algorithm is implemented without large scale iterations. • Hot spot temperature and loss of life for transformers are evaluated.

Measuring Algorithm for the Distance to a Preceding Vehicle on Curve Road Using On-Board Monocular Camera

Science.gov (United States)

Yu, Guizhen; Zhou, Bin; Wang, Yunpeng; Wun, Xinkai; Wang, Pengcheng

2015-12-01

Due to more severe challenges of traffic safety problems, the Advanced Driver Assistance Systems (ADAS) has received widespread attention. Measuring the distance to a preceding vehicle is important for ADAS. However, the existing algorithm focuses more on straight road sections than on curve measurements. In this paper, we present a novel measuring algorithm for the distance to a preceding vehicle on a curve road using on-board monocular camera. Firstly, the characteristics of driving on the curve road is analyzed and the recognition of the preceding vehicle road area is proposed. Then, the vehicle detection and distance measuring algorithms are investigated. We have verified these algorithms on real road driving. The experimental results show that this method proposed in the paper can detect the preceding vehicle on curve roads and accurately calculate the longitudinal distance and horizontal distance to the preceding vehicle.

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.

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...

Energy Aware Cluster-Based Routing in Flying Ad-Hoc Networks.

Science.gov (United States)

Aadil, Farhan; Raza, Ali; Khan, Muhammad Fahad; Maqsood, Muazzam; Mehmood, Irfan; Rho, Seungmin

2018-05-03

Flying ad-hoc networks (FANETs) are a very vibrant research area nowadays. They have many military and civil applications. Limited battery energy and the high mobility of micro unmanned aerial vehicles (UAVs) represent their two main problems, i.e., short flight time and inefficient routing. In this paper, we try to address both of these problems by means of efficient clustering. First, we adjust the transmission power of the UAVs by anticipating their operational requirements. Optimal transmission range will have minimum packet loss ratio (PLR) and better link quality, which ultimately save the energy consumed during communication. Second, we use a variant of the K-Means Density clustering algorithm for selection of cluster heads. Optimal cluster heads enhance the cluster lifetime and reduce the routing overhead. The proposed model outperforms the state of the art artificial intelligence techniques such as Ant Colony Optimization-based clustering algorithm and Grey Wolf Optimization-based clustering algorithm. The performance of the proposed algorithm is evaluated in term of number of clusters, cluster building time, cluster lifetime and energy consumption.

Energy Aware Cluster-Based Routing in Flying Ad-Hoc Networks

Directory of Open Access Journals (Sweden)

Farhan Aadil

2018-05-01

Full Text Available Flying ad-hoc networks (FANETs are a very vibrant research area nowadays. They have many military and civil applications. Limited battery energy and the high mobility of micro unmanned aerial vehicles (UAVs represent their two main problems, i.e., short flight time and inefficient routing. In this paper, we try to address both of these problems by means of efficient clustering. First, we adjust the transmission power of the UAVs by anticipating their operational requirements. Optimal transmission range will have minimum packet loss ratio (PLR and better link quality, which ultimately save the energy consumed during communication. Second, we use a variant of the K-Means Density clustering algorithm for selection of cluster heads. Optimal cluster heads enhance the cluster lifetime and reduce the routing overhead. The proposed model outperforms the state of the art artificial intelligence techniques such as Ant Colony Optimization-based clustering algorithm and Grey Wolf Optimization-based clustering algorithm. The performance of the proposed algorithm is evaluated in term of number of clusters, cluster building time, cluster lifetime and energy consumption.

Performance of multiobjective computational intelligence algorithms for the routing and wavelength assignment problem

Directory of Open Access Journals (Sweden)

Jorge Patiño

2016-01-01

Full Text Available This paper presents an evaluation performance of computational intelligence algorithms based on the multiobjective theory for the solution of the Routing and Wavelength Assignment problem (RWA in optical networks. The study evaluates the Firefly Algorithm, the Differential Evolutionary Algorithm, the Simulated Annealing Algorithm and two versions of the Particle Swarm Optimization algorithm. The paper provides a description of the multiobjective algorithms; then, an evaluation based on the performance provided by the multiobjective algorithms versus mono-objective approaches when dealing with different traffic loads, different numberof wavelengths and wavelength conversion process over the NSFNet topology is presented. Simulation results show that monoobjective algorithms properly solve the RWA problem for low values of data traffic and low number of wavelengths. However, the multiobjective approaches adapt better to online traffic when the number of wavelengths available in the network increases as well as when wavelength conversion is implemented in the nodes.

A Fully-Distributed Heuristic Algorithm for Control of Autonomous Vehicle Movements at Isolated Intersections

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Abdallah A. Hassan

2014-12-01

Full Text Available Optimizing autonomous vehicle movements through roadway intersections is a challenging problem. It has been demonstrated in the literature that traditional traffic control, such as traffic signal and stop sign control are not optimal especially for heavy traffic demand levels. Alternatively, centralized autonomous vehicle control strategies are costly and not scalable given that the ability of a central controller to track and schedule the movement of hundreds of vehicles in real-time is questionable. Consequently, in this paper a fully distributed algorithm is proposed where vehicles in the vicinity of an intersection continuously cooperate with each other to develop a schedule that allows them to safely proceed through the intersection while incurring minimum delay. Unlike other distributed approaches described in the literature, the wireless communication constraints are considered in the design of the control algorithm. Specifically, the proposed algorithm requires vehicles heading to an intersection to communicate only with neighboring vehicles, while the lead vehicles on each approach lane share information to develop a complete intersection utilization schedule. The scheduling rotates between vehicles to identify higher traffic volumes and favor vehicles coming from heavier lanes to minimize the overall intersection delay. The simulated experiments show significant reductions in the average delay using the proposed approach compared to other methods reported in the literature and reduction in the maximum delay experienced by a vehicle especially in cases of heavy traffic demand levels.

Fuzzy Weight Cluster-Based Routing Algorithm for Wireless Sensor Networks

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Teng Gao

2015-01-01

Full Text Available Cluster-based protocol is a kind of important routing in wireless sensor networks. However, due to the uneven distribution of cluster heads in classical clustering algorithm, some nodes may run out of energy too early, which is not suitable for large-scale wireless sensor networks. In this paper, a distributed clustering algorithm based on fuzzy weighted attributes is put forward to ensure both energy efficiency and extensibility. On the premise of a comprehensive consideration of all attributes, the corresponding weight of each parameter is assigned by using the direct method of fuzzy engineering theory. Then, each node works out property value. These property values will be mapped to the time axis and be triggered by a timer to broadcast cluster headers. At the same time, the radio coverage method is adopted, in order to avoid collisions and to ensure the symmetrical distribution of cluster heads. The aggregated data are forwarded to the sink node in the form of multihop. The simulation results demonstrate that clustering algorithm based on fuzzy weighted attributes has a longer life expectancy and better extensibility than LEACH-like algorithms.

Energy Efficient Routing Algorithms in Dynamic Optical Core Networks with Dual Energy Sources

DEFF Research Database (Denmark)

Wang, Jiayuan; Fagertun, Anna Manolova; Ruepp, Sarah Renée

2013-01-01

This paper proposes new energy efficient routing algorithms in optical core networks, with the application of solar energy sources and bundled links. A comprehensive solar energy model is described in the proposed network scenarios. Network performance in energy savings, connection blocking...... probability, resource utilization and bundled link usage are evaluated with dynamic network simulations. Results show that algorithms proposed aiming for reducing the dynamic part of the energy consumption of the network may raise the fixed part of the energy consumption meanwhile....

THERMAL PERFORMANCE OF REFRIGERATED VEHICLES IN THE DISTRIBUTION OF PERISHABLE FOOD

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Antônio G.N. Novaes

2015-08-01

Full Text Available The temperature of refrigerated products along the distribution process must be kept within close limits to ensure optimum food safety levels and high product quality. The variation of product temperature along the vehicle routing sequence is represented by non-linear functions. The temperature variability is also correlated with the time required for the refrigerated unit to recover after cargo unloading, due to the cargo discharging process. The vehicle routing optimization methods employed in traditional cargo distribution problems are generally based on the Travelling Salesman Problem with the objective of minimizing travelled distance or time. The thermal quality of routing alternatives is evaluated in this analysis with Process Capability Indices (PCI. Since temperature does not vary linearly with time, a Simulated Annealing algorithm was developed to get the optimal solution in which the minimum vehicle traveling distance is searched, but respecting the quality level expressed by a required minimum PCI value.

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

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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.

Evaluation of odometry algorithm performances using a railway vehicle dynamic model

Science.gov (United States)

Allotta, B.; Pugi, L.; Ridolfi, A.; Malvezzi, M.; Vettori, G.; Rindi, A.

2012-05-01

In modern railway Automatic Train Protection and Automatic Train Control systems, odometry is a safety relevant on-board subsystem which estimates the instantaneous speed and the travelled distance of the train; a high reliability of the odometry estimate is fundamental, since an error on the train position may lead to a potentially dangerous overestimation of the distance available for braking. To improve the odometry estimate accuracy, data fusion of different inputs coming from a redundant sensor layout may be used. Simplified two-dimensional models of railway vehicles have been usually used for Hardware in the Loop test rig testing of conventional odometry algorithms and of on-board safety relevant subsystems (like the Wheel Slide Protection braking system) in which the train speed is estimated from the measures of the wheel angular speed. Two-dimensional models are not suitable to develop solutions like the inertial type localisation algorithms (using 3D accelerometers and 3D gyroscopes) and the introduction of Global Positioning System (or similar) or the magnetometer. In order to test these algorithms correctly and increase odometry performances, a three-dimensional multibody model of a railway vehicle has been developed, using Matlab-Simulink™, including an efficient contact model which can simulate degraded adhesion conditions (the development and prototyping of odometry algorithms involve the simulation of realistic environmental conditions). In this paper, the authors show how a 3D railway vehicle model, able to simulate the complex interactions arising between different on-board subsystems, can be useful to evaluate the odometry algorithm and safety relevant to on-board subsystem performances.

Intelligent Shuttle Management and Routing Algorithm

Science.gov (United States)

Thomas, Toshen M.; Subashanthini, S.

2017-11-01

Nowadays, most of the big Universities and campuses have Shuttle cabs running in them to cater the transportational needs of the students and faculties. While some shuttle services ask for a meagre sum to be paid for the usage, no digital payment system is onboard these vehicles to go truly cashless. Even more troublesome is the fact that sometimes during the day, some of these cabs run with bare number of passengers, which can result in unwanted budget loss to the shuttle operator. The main purpose of this paper is to create a system with two types of applications: A web portal and an Android app, to digitize the Shuttle cab industry. This system can be used for digital cashless payment feature, tracking passengers, tracking cabs and more importantly, manage the number of shuttle cabs in every route to maximize profit. This project is built upon an ASP.NET website connected to a cloud service along with an Android app that tracks and reads the passengers ID using an attached barcode reader along with the current GPS coordinates, and sends these data to the cloud for processing using the phone’s internet connectivity.

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.

An optimized routing algorithm for the automated assembly of standard multimode ribbon fibers in a full-mesh optical backplane

Science.gov (United States)

Basile, Vito; Guadagno, Gianluca; Ferrario, Maddalena; Fassi, Irene

2018-03-01

In this paper a parametric, modular and scalable algorithm allowing a fully automated assembly of a backplane fiber-optic interconnection circuit is presented. This approach guarantees the optimization of the optical fiber routing inside the backplane with respect to specific criteria (i.e. bending power losses), addressing both transmission performance and overall costs issues. Graph theory has been exploited to simplify the complexity of the NxN full-mesh backplane interconnection topology, firstly, into N independent sub-circuits and then, recursively, into a limited number of loops easier to be generated. Afterwards, the proposed algorithm selects a set of geometrical and architectural parameters whose optimization allows to identify the optimal fiber optic routing for each sub-circuit of the backplane. The topological and numerical information provided by the algorithm are then exploited to control a robot which performs the automated assembly of the backplane sub-circuits. The proposed routing algorithm can be extended to any array architecture and number of connections thanks to its modularity and scalability. Finally, the algorithm has been exploited for the automated assembly of an 8x8 optical backplane realized with standard multimode (MM) 12-fiber ribbons.

A feature matching and fusion-based positive obstacle detection algorithm for field autonomous land vehicles

Directory of Open Access Journals (Sweden)

Tao Wu

2017-03-01

Full Text Available Positive obstacles will cause damage to field robotics during traveling in field. Field autonomous land vehicle is a typical field robotic. This article presents a feature matching and fusion-based algorithm to detect obstacles using LiDARs for field autonomous land vehicles. There are three main contributions: (1 A novel setup method of compact LiDAR is introduced. This method improved the LiDAR data density and reduced the blind region of the LiDAR sensor. (2 A mathematical model is deduced under this new setup method. The ideal scan line is generated by using the deduced mathematical model. (3 Based on the proposed mathematical model, a feature matching and fusion (FMAF-based algorithm is presented in this article, which is employed to detect obstacles. Experimental results show that the performance of the proposed algorithm is robust and stable, and the computing time is reduced by an order of two magnitudes by comparing with other exited algorithms. This algorithm has been perfectly applied to our autonomous land vehicle, which has won the champion in the challenge of Chinese “Overcome Danger 2014” ground unmanned vehicle.

An Adaptive Large Neighborhood Search-based Three-Stage Matheuristic for the Vehicle Routing Problem with Time Windows

DEFF Research Database (Denmark)

Christensen, Jonas Mark; Røpke, Stefan

that serves all the customers. The second stage usesan Adaptive Large Neighborhood Search (ALNS) algorithm to minimise the travel distance, during the second phase all of the generated routes are considered by solving a set cover problem. The ALNS algorithm uses 4 destroy operators, 2 repair operators...

The design and results of an algorithm for intelligent ground vehicles

Science.gov (United States)

Duncan, Matthew; Milam, Justin; Tote, Caleb; Riggins, Robert N.

2010-01-01

This paper addresses the design, design method, test platform, and test results of an algorithm used in autonomous navigation for intelligent vehicles. The Bluefield State College (BSC) team created this algorithm for its 2009 Intelligent Ground Vehicle Competition (IGVC) robot called Anassa V. The BSC robotics team is comprised of undergraduate computer science, engineering technology, marketing students, and one robotics faculty advisor. The team has participated in IGVC since the year 2000. A major part of the design process that the BSC team uses each year for IGVC is a fully documented "Post-IGVC Analysis." Over the nine years since 2000, the lessons the students learned from these analyses have resulted in an ever-improving, highly successful autonomous algorithm. The algorithm employed in Anassa V is a culmination of past successes and new ideas, resulting in Anassa V earning several excellent IGVC 2009 performance awards, including third place overall. The paper will discuss all aspects of the design of this autonomous robotic system, beginning with the design process and ending with test results for both simulation and real environments.

A HYBRID HOPFIELD NEURAL NETWORK AND TABU SEARCH ALGORITHM TO SOLVE ROUTING PROBLEM IN COMMUNICATION NETWORK

Directory of Open Access Journals (Sweden)

MANAR Y. KASHMOLA

2012-06-01

Full Text Available The development of hybrid algorithms for solving complex optimization problems focuses on enhancing the strengths and compensating for the weakness of two or more complementary approaches. The goal is to intelligently combine the key elements of these approaches to find superior solutions to solve optimization problems. Optimal routing in communication network is considering a complex optimization problem. In this paper we propose a hybrid Hopfield Neural Network (HNN and Tabu Search (TS algorithm, this algorithm called hybrid HNN-TS algorithm. The paradigm of this hybridization is embedded. We embed the short-term memory and tabu restriction features from TS algorithm in the HNN model. The short-term memory and tabu restriction control the neuron selection process in the HNN model in order to get around the local minima problem and find an optimal solution using the HNN model to solve complex optimization problem. The proposed algorithm is intended to find the optimal path for packet transmission in the network which is fills in the field of routing problem. The optimal path that will be selected is depending on 4-tuples (delay, cost, reliability and capacity. Test results show that the propose algorithm can find path with optimal cost and a reasonable number of iterations. It also shows that the complexity of the network model won’t be a problem since the neuron selection is done heuristically.

Heuristic algorithms for solving of the tool routing problem for CNC cutting machines

Science.gov (United States)

Chentsov, P. A.; Petunin, A. A.; Sesekin, A. N.; Shipacheva, E. N.; Sholohov, A. E.

2015-11-01

The article is devoted to the problem of minimizing the path of the cutting tool to shape cutting machines began. This problem can be interpreted as a generalized traveling salesman problem. Earlier version of the dynamic programming method to solve this problem was developed. Unfortunately, this method allows to process an amount not exceeding thirty circuits. In this regard, the task of constructing quasi-optimal route becomes relevant. In this paper we propose options for quasi-optimal greedy algorithms. Comparison of the results of exact and approximate algorithms is given.

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 semi-active suspension control algorithm for vehicle comprehensive vertical dynamics performance

Science.gov (United States)

Nie, Shida; Zhuang, Ye; Liu, Weiping; Chen, Fan

2017-08-01

Comprehensive performance of the vehicle, including ride qualities and road-holding, is essentially of great value in practice. Many up-to-date semi-active control algorithms improve vehicle dynamics performance effectively. However, it is hard to improve comprehensive performance for the conflict between ride qualities and road-holding around the second-order resonance. Hence, a new control algorithm is proposed to achieve a good trade-off between ride qualities and road-holding. In this paper, the properties of the invariant points are analysed, which gives an insight into the performance conflicting around the second-order resonance. Based on it, a new control algorithm is proposed. The algorithm employs a novel frequency selector to balance suspension ride and handling performance by adopting a medium damping around the second-order resonance. The results of this study show that the proposed control algorithm could improve the performance of ride qualities and suspension working space up to 18.3% and 8.2%, respectively, with little loss of road-holding compared to the passive suspension. Consequently, the comprehensive performance can be improved by 6.6%. Hence, the proposed algorithm is of great potential to be implemented in practice.

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

Economic and Environmental Evaluation of a Brick Delivery System Based on Multi-Trip Vehicle Loader Routing Problem for Small Construction Sites

Directory of Open Access Journals (Sweden)

Heungjo An

2018-05-01

Full Text Available While large construction sites have on-site loaders to handle heavy and large packages of bricks, small brick manufacturers employ a truck-mounted loader or sometimes deploy a loader truck to accompany normal brick delivery trucks to small construction sites lacking on-site loaders. It may be very challenging for small contractors to manage a sustainable delivery system that is both cost-effective and environmentally friendly. To address this issue, this paper proposes to solve a multi-trip vehicle loader routing problem by uniquely planning routes and schedules of several types of vehicles considering their synchronized operations at customer sites and multi trips. This paper also evaluates the sustainability of the developed model from both economic and environmental perspectives. Case studies based on small construction sites in the Middle East demonstrate applications of the proposed model to make the most economical plans for delivering bricks. Compared to the single-trip vehicle loader routing problem, the proposed model reduces, on average, 18.7% of the total delivery cost while increasing CO2 emission negligibly. The economic benefit is mainly achieved by reducing the required number of vehicles. Brick plant managers can use the proposed mathematical model to plan the most cost-effective delivery schedules sustainably while minimizing negative environmental effects.

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.

Ecodriver. D23.1: Report on test scenarios for val-idation of on-line vehicle algorithms

NARCIS (Netherlands)

Seewald, P.; Ivens, T.W.T.; Spronkmans, S.

2014-01-01

This deliverable provides a description of test scenarios that will be used for validation of WP22’s on-line vehicle algorithms. These algorithms consist of the two modules VE³ (Vehicle Energy and Environment Estimator) and RSG (Reference Signal Genera-tor) and will be tested using the

A proposal of multi-objective function for submarine rigid pipelines route optimization via evolutionary algorithms

Energy Technology Data Exchange (ETDEWEB)

Fernandes, D.H.; Medeiros, A.R. [Subsea7, Niteroi, RJ (Brazil); Jacob, B.P.; Lima, B.S.L.P.; Albrecht, C.H. [Universidade Federaldo Rio de Janeiro (COPPE/UFRJ), RJ (Brazil). Coordenacao de Programas de Pos-graduacao em Engenharia

2009-07-01

This work presents studies regarding the determination of optimal pipeline routes for offshore applications. The assembly of an objective function is presented; this function can be later associated with Evolutionary Algorithm to implement a computational tool for the automatic determination of the most advantageous pipeline route for a given scenario. This tool may reduce computational overheads, avoid mistakes with route interpretation, and minimize costs with respect to submarine pipeline design and installation. The following aspects can be considered in the assembly of the objective function: Geophysical and geotechnical data obtained from the bathymetry and sonography; the influence of the installation method, total pipeline length and number of free spans to be mitigated along the routes as well as vessel time for both cases. Case studies are presented to illustrate the use of the proposed objective function, including a sensitivity analysis intended to identify the relative influence of selected parameters in the evaluation of different routes. (author)

Evaluation of connected vehicle impact on mobility and mode choice

Directory of Open Access Journals (Sweden)

Simon Minelli

2015-10-01

Full Text Available Connected vehicle is emerging as a solution to exacerbating congestion problems in urban areas. It is important to understand the impacts of connected vehicle on network and travel behavior of road users. The main objective of this paper is to evaluate the impact of connected vehicle on the mode choice and mobility of transportation networks. An iterative methodology was used in this paper where demands for various modes were modified based on the changes in travel time between each origin-destination (OD pair caused by introduction of connected vehicle. Then a traffic assignment was performed in a micro-simulation model, which was able to accurately simulate vehicle-to-vehicle communication. It is assumed that vehicles are equipped with a dynamic route guidance technology to choose their own route using real-time traffic information obtained through communication. The travel times obtained from the micro-simulation model were compared with a base scenario with no connected vehicle. The methodology was tested for a portion of Downtown Toronto, Ontario, Canada. In order to quantify changes in mode share with changes in travel time associated with each OD pair, mode choice models were developed for auto, transit, cycling and pedestrians using data mainly from the Transportation Tomorrow Survey. The impact of connected vehicle on mode choice was evaluated for different market penetrations of connected vehicle. The results of this study show that average travel times for the whole auto mode will generally increase, with the largest increase from connected vehicles. This causes an overall move away from the auto mode for high market penetrations if a dynamic route guidance algorithm is implemented.

Advanced Emergency Braking Control Based on a Nonlinear Model Predictive Algorithm for Intelligent Vehicles

Directory of Open Access Journals (Sweden)

Ronghui Zhang

2017-05-01

Full Text Available Focusing on safety, comfort and with an overall aim of the comprehensive improvement of a vision-based intelligent vehicle, a novel Advanced Emergency Braking System (AEBS is proposed based on Nonlinear Model Predictive Algorithm. Considering the nonlinearities of vehicle dynamics, a vision-based longitudinal vehicle dynamics model is established. On account of the nonlinear coupling characteristics of the driver, surroundings, and vehicle itself, a hierarchical control structure is proposed to decouple and coordinate the system. To avoid or reduce the collision risk between the intelligent vehicle and collision objects, a coordinated cost function of tracking safety, comfort, and fuel economy is formulated. Based on the terminal constraints of stable tracking, a multi-objective optimization controller is proposed using the theory of non-linear model predictive control. To quickly and precisely track control target in a finite time, an electronic brake controller for AEBS is designed based on the Nonsingular Fast Terminal Sliding Mode (NFTSM control theory. To validate the performance and advantages of the proposed algorithm, simulations are implemented. According to the simulation results, the proposed algorithm has better integrated performance in reducing the collision risk and improving the driving comfort and fuel economy of the smart car compared with the existing single AEBS.

Solving the Dial-a-Ride Problem using Genetic Algorithms

DEFF Research Database (Denmark)

Jørgensen, Rene Munk; Larsen, Jesper; Bergvinsdottir, Kristin Berg

2007-01-01

In the Dial-a-Ride problem (DARP), customers request transportation from an operator. A request consists of a specified pickup location and destination location along with a desired departure or arrival time and capacity demand. The aim of DARP is to minimize transportation cost while satisfying ...... routing problems for the vehicles using a routing heuristic. The algorithm is implemented in Java and tested on publicly available data sets. The new solution method has achieved solutions comparable with the current state-of-the-art methods....

Path planning for persistent surveillance applications using fixed-wing unmanned aerial vehicles

Science.gov (United States)

Keller, James F.

This thesis addresses coordinated path planning for fixed-wing Unmanned Aerial Vehicles (UAVs) engaged in persistent surveillance missions. While uniquely suited to this mission, fixed wing vehicles have maneuver constraints that can limit their performance in this role. Current technology vehicles are capable of long duration flight with a minimal acoustic footprint while carrying an array of cameras and sensors. Both military tactical and civilian safety applications can benefit from this technology. We make three main contributions: C1 A sequential path planner that generates a C 2 flight plan to persistently acquire a covering set of data over a user designated area of interest. The planner features the following innovations: • A path length abstraction that embeds kino-dynamic motion constraints to estimate feasible path length. • A Traveling Salesman-type planner to generate a covering set route based on the path length abstraction. • A smooth path generator that provides C 2 routes that satisfy user specified curvature constraints. C2 A set of algorithms to coordinate multiple UAVs, including mission commencement from arbitrary locations to the start of a coordinated mission and de-confliction of paths to avoid collisions with other vehicles and fixed obstacles. C3 A numerically robust toolbox of spline-based algorithms tailored for vehicle routing validated through flight test experiments on multiple platforms. A variety of tests and platforms are discussed. The algorithms presented are based on a technical approach with approximately equal emphasis on analysis, computation, dynamic simulation, and flight test experimentation. Our planner (C1) directly takes into account vehicle maneuverability and agility constraints that could otherwise render simple solutions infeasible. This is especially important when surveillance objectives elevate the importance of optimized paths. Researchers have developed a diverse range of solutions for persistent

An Improved Routing Optimization Algorithm Based on Travelling Salesman Problem for Social Networks

Directory of Open Access Journals (Sweden)

Naixue Xiong

2017-06-01

Full Text Available A social network is a social structure, which is organized by the relationships or interactions between individuals or groups. Humans link the physical network with social network, and the services in the social world are based on data and analysis, which directly influence decision making in the physical network. In this paper, we focus on a routing optimization algorithm, which solves a well-known and popular problem. Ant colony algorithm is proposed to solve this problem effectively, but random selection strategy of the traditional algorithm causes evolution speed to be slow. Meanwhile, positive feedback and distributed computing model make the algorithm quickly converge. Therefore, how to improve convergence speed and search ability of algorithm is the focus of the current research. The paper proposes the improved scheme. Considering the difficulty about searching for next better city, new parameters are introduced to improve probability of selection, and delay convergence speed of algorithm. To avoid the shortest path being submerged, and improve sensitive speed of finding the shortest path, it updates pheromone regulation formula. The results show that the improved algorithm can effectively improve convergence speed and search ability for achieving higher accuracy and optimal results.

A Branch-and-Price Algorithm for Two Multi-Compartment Vehicle Routing Problems

DEFF Research Database (Denmark)

Mirzaei, Samira; Wøhlk, Sanne

2017-01-01

by comparing the optimal costs of the two versions. Computational results are presented for instances with up to 100 customers and the algorithm can solve instances with up to 50 customers and 4 commodities to optimality. NOTE: An early version of the paper was made public on the website of the journal...

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.

A Location-Inventory-Routing Problem in Forward and Reverse Logistics Network Design

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Qunli Yuchi

2016-01-01

Full Text Available We study a new problem of location-inventory-routing in forward and reverse logistic (LIRP-FRL network design, which simultaneously integrates the location decisions of distribution centers (DCs, the inventory policies of opened DCs, and the vehicle routing decision in serving customers, in which new goods are produced and damaged goods are repaired by a manufacturer and then returned to the market to satisfy customers’ demands as new ones. Our objective is to minimize the total costs of manufacturing and remanufacturing goods, building DCs, shipping goods (new or recovered between the manufacturer and opened DCs, and distributing new or recovered goods to customers and ordering and storage costs of goods. A nonlinear integer programming model is proposed to formulate the LIRP-FRL. A new tabu search (NTS algorithm is developed to achieve near optimal solution of the problem. Numerical experiments on the benchmark instances of a simplified version of the LIRP-FRL, the capacitated location routing problem, and the randomly generated LIRP-FRL instances demonstrate the effectiveness and efficiency of the proposed NTS algorithm in problem resolution.

Vehicle Routing Problem with Backhaul, Multiple Trips and Time Window

Directory of Open Access Journals (Sweden)

Johan Oscar Ong

2011-01-01

Full Text Available Transportation planning is one of the important components to increase efficiency and effectiveness in the supply chain system. Good planning will give a saving in total cost of the supply chain. This paper develops the new VRP variants’, VRP with backhauls, multiple trips, and time window (VRPBMTTW along with its problem solving techniques by using Ant Colony Optimization (ACO and Sequential Insertion as initial solution algorithm. ACO is modified by adding the decoding process in order to determine the number of vehicles, total duration time, and range of duration time regardless of checking capacity constraint and time window. This algorithm is tested by using set of random data and verified as well as analyzed its parameter changing’s. The computational results for hypothetical data with 50% backhaul and mix time windows are reported.

Personal continuous route pattern mining

Institute of Scientific and Technical Information of China (English)

Qian YE; Ling CHEN; Gen-cai CHEN

2009-01-01

In the daily life, people often repeat regular routes in certain periods. In this paper, a mining system is developed to find the continuous route patterns of personal past trips. In order to count the diversity of personal moving status, the mining system employs the adaptive GPS data recording and five data filters to guarantee the clean trips data. The mining system uses a client/server architecture to protect personal privacy and to reduce the computational load. The server conducts the main mining procedure but with insufficient information to recover real personal routes. In order to improve the scalability of sequential pattern mining, a novel pattern mining algorithm, continuous route pattern mining (CRPM), is proposed. This algorithm can tolerate the different disturbances in real routes and extract the frequent patterns. Experimental results based on nine persons' trips show that CRPM can extract more than two times longer route patterns than the traditional route pattern mining algorithms.

A Hybrid Ant Colony Optimization Algorithm for the Extended Capacitated Arc Routing Problem.

Science.gov (United States)

Li-Ning Xing; Rohlfshagen, P; Ying-Wu Chen; Xin Yao

2011-08-01

The capacitated arc routing problem (CARP) is representative of numerous practical applications, and in order to widen its scope, we consider an extended version of this problem that entails both total service time and fixed investment costs. We subsequently propose a hybrid ant colony optimization (ACO) algorithm (HACOA) to solve instances of the extended CARP. This approach is characterized by the exploitation of heuristic information, adaptive parameters, and local optimization techniques: Two kinds of heuristic information, arc cluster information and arc priority information, are obtained continuously from the solutions sampled to guide the subsequent optimization process. The adaptive parameters ease the burden of choosing initial values and facilitate improved and more robust results. Finally, local optimization, based on the two-opt heuristic, is employed to improve the overall performance of the proposed algorithm. The resulting HACOA is tested on four sets of benchmark problems containing a total of 87 instances with up to 140 nodes and 380 arcs. In order to evaluate the effectiveness of the proposed method, some existing capacitated arc routing heuristics are extended to cope with the extended version of this problem; the experimental results indicate that the proposed ACO method outperforms these heuristics.

An IPv6 routing lookup algorithm using weight-balanced tree based on prefix value for virtual router

Science.gov (United States)

Chen, Lingjiang; Zhou, Shuguang; Zhang, Qiaoduo; Li, Fenghua

2016-10-01

Virtual router enables the coexistence of different networks on the same physical facility and has lately attracted a great deal of attention from researchers. As the number of IPv6 addresses is rapidly increasing in virtual routers, designing an efficient IPv6 routing lookup algorithm is of great importance. In this paper, we present an IPv6 lookup algorithm called weight-balanced tree (WBT). WBT merges Forwarding Information Bases (FIBs) of virtual routers into one spanning tree, and compresses the space cost. WBT's average time complexity and the worst case time complexity of lookup and update process are both O(logN) and space complexity is O(cN) where N is the size of routing table and c is a constant. Experiments show that WBT helps reduce more than 80% Static Random Access Memory (SRAM) cost in comparison to those separation schemes. WBT also achieves the least average search depth comparing with other homogeneous algorithms.

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 energy efficient distance-aware routing algorithm with multiple mobile sinks for wireless sensor networks.

Science.gov (United States)

Wang, Jin; Li, Bin; Xia, Feng; Kim, Chang-Seob; Kim, Jeong-Uk

2014-08-18

Traffic patterns in wireless sensor networks (WSNs) usually follow a many-to-one model. Sensor nodes close to static sinks will deplete their limited energy more rapidly than other sensors, since they will have more data to forward during multihop transmission. This will cause network partition, isolated nodes and much shortened network lifetime. Thus, how to balance energy consumption for sensor nodes is an important research issue. In recent years, exploiting sink mobility technology in WSNs has attracted much research attention because it can not only improve energy efficiency, but prolong network lifetime. In this paper, we propose an energy efficient distance-aware routing algorithm with multiple mobile sink for WSNs, where sink nodes will move with a certain speed along the network boundary to collect monitored data. We study the influence of multiple mobile sink nodes on energy consumption and network lifetime, and we mainly focus on the selection of mobile sink node number and the selection of parking positions, as well as their impact on performance metrics above. We can see that both mobile sink node number and the selection of parking position have important influence on network performance. Simulation results show that our proposed routing algorithm has better performance than traditional routing ones in terms of energy consumption.

An Energy Efficient Distance-Aware Routing Algorithm with Multiple Mobile Sinks for Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Jin Wang

2014-08-01

Full Text Available Traffic patterns in wireless sensor networks (WSNs usually follow a many-to-one model. Sensor nodes close to static sinks will deplete their limited energy more rapidly than other sensors, since they will have more data to forward during multihop transmission. This will cause network partition, isolated nodes and much shortened network lifetime. Thus, how to balance energy consumption for sensor nodes is an important research issue. In recent years, exploiting sink mobility technology in WSNs has attracted much research attention because it can not only improve energy efficiency, but prolong network lifetime. In this paper, we propose an energy efficient distance-aware routing algorithm with multiple mobile sink for WSNs, where sink nodes will move with a certain speed along the network boundary to collect monitored data. We study the influence of multiple mobile sink nodes on energy consumption and network lifetime, and we mainly focus on the selection of mobile sink node number and the selection of parking positions, as well as their impact on performance metrics above. We can see that both mobile sink node number and the selection of parking position have important influence on network performance. Simulation results show that our proposed routing algorithm has better performance than traditional routing ones in terms of energy consumption.

Torque Distribution Algorithm for an Independently Driven Electric Vehicle Using a Fuzzy Control Method

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Jinhyun Park

2015-08-01

Full Text Available The in-wheel electric vehicle is expected to be a popular next-generation vehicle because an in-wheel system can simplify the powertrain and improve driving performance. In addition, it also has an advantage in that it maximizes driving efficiency through independent torque control considering the motor efficiency. However, there is an instability problem if only the driving torque is controlled in consideration of only the motor efficiency. In this paper, integrated torque distribution strategies are proposed to overcome these problems. The control algorithm consists of various strategies for optimizing driving efficiency, satisfying driver demands, and considering tire slip and vehicle cornering. Fuzzy logic is used to determine the appropriate timing of intervention for each distribution strategy. A performance simulator for in-wheel electric vehicles was developed by using MATLAB/Simulink and CarSim to validate the control strategies. From simulation results under complex driving conditions, the proposed algorithm was verified to improve both the driving stability and fuel economy of the in-wheel vehicle.

Ecodriver. D23.2: Simulation and analysis document for on-line vehicle algorithms

NARCIS (Netherlands)

Seewald, P.; Orfila, O.; Saintpierre, G.

2014-01-01

This deliverable reports on the simulations and analysis of the on-line vehicle algorithms as well as the ecoDriver Android application. The simulation and field test results give an impression of how the algorithms will perform in the real world trials in SP3. Thus, it is possible to apply

SINS/CNS Nonlinear Integrated Navigation Algorithm for Hypersonic Vehicle

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Yong-jun Yu

2015-01-01

Full Text Available Celestial Navigation System (CNS has characteristics of accurate orientation and strong autonomy and has been widely used in Hypersonic Vehicle. Since the CNS location and orientation mainly depend upon the inertial reference that contains errors caused by gyro drifts and other error factors, traditional Strap-down Inertial Navigation System (SINS/CNS positioning algorithm setting the position error between SINS and CNS as measurement is not effective. The model of altitude azimuth, platform error angles, and horizontal position is designed, and the SINS/CNS tightly integrated algorithm is designed, in which CNS altitude azimuth is set as measurement information. GPF (Gaussian particle filter is introduced to solve the problem of nonlinear filtering. The results of simulation show that the precision of SINS/CNS algorithm which reaches 130 m using three stars is improved effectively.

Improved Genetic Algorithm Optimization for Forward Vehicle Detection Problems

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Longhui Gang

2015-07-01

Full Text Available Automated forward vehicle detection is an integral component of many advanced driver-assistance systems. The method based on multi-visual information fusion, with its exclusive advantages, has become one of the important topics in this research field. During the whole detection process, there are two key points that should to be resolved. One is to find the robust features for identification and the other is to apply an efficient algorithm for training the model designed with multi-information. This paper presents an adaptive SVM (Support Vector Machine model to detect vehicle with range estimation using an on-board camera. Due to the extrinsic factors such as shadows and illumination, we pay more attention to enhancing the system with several robust features extracted from a real driving environment. Then, with the introduction of an improved genetic algorithm, the features are fused efficiently by the proposed SVM model. In order to apply the model in the forward collision warning system, longitudinal distance information is provided simultaneously. The proposed method is successfully implemented on a test car and evaluation experimental results show reliability in terms of both the detection rate and potential effectiveness in a real-driving environment.

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 Emergency Material Vehicle Dispatching and Routing under Dynamic Constraints in an Earthquake Disaster Environment

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Jincheng Jiang

2017-05-01

Full Text Available Emergency material vehicle dispatching and routing (EMVDR is an important task in emergency relief after large-scale earthquake disasters. However, EMVDR is subject to dynamic disaster environment, with uncertainty surrounding elements such as the transportation network and relief materials. Accurate and dynamic emergency material dispatching and routing is difficult. This paper proposes an effective and efficient multi-objective multi-dynamic-constraint emergency material vehicle dispatching and routing model. Considering travel time, road capacity, and material supply and demand, the proposed EMVDR model is to deliver emergency materials from multiple emergency material depositories to multiple disaster points while satisfying the objectives of maximizing transport efficiency and minimizing the difference of material urgency degrees among multiple disaster points at any one time. Furthermore, a continuous-time dynamic network flow method is developed to solve this complicated model. The collected data from Ludian earthquake were used to conduct our experiments in the post-quake and the results demonstrate that: (1 the EMVDR model adapts to the dynamic disaster environment very well; (2 considering the difference of material urgency degree, the material loss ratio is −10.7%, but the variance of urgency degree decreases from 2.39 to 0.37; (3 the EMVDR model shows good performance in time and space, which allows for decisions to be made nearly in real time. This paper can provide spatial decision-making support for emergency material relief in large-scale earthquake disasters.

Simulation of the target-oriented driving of an autonomous vehicle in a labyrinthic environment by means of the KISMET software package

International Nuclear Information System (INIS)

Knueppel, H.; Kuehnapfel, U.; Smidt, D.

1991-10-01

By using the special capabilities of the KISMET software-package and hardware for geometric operations and graphical presentation, an algorithm for the collision-free target-oriented driving of an autonomous vehicle was developed, implemented and linked to KISMET. The algorithm employs a simple global route-planner. It creates the global path neglecting the finite vehicle dimensions as input to the sensor-based local route-planner. The local planner for each time step transforms the sensor pattern, received by a number of ultrasonic sensors, to the movement-pattern. The target oriented global information influences the local operations. Some examples and a video demonstrate, the target will be reached collision free and close to the shortest path even in a labyrinthic environment. (orig.) [de

Hybrid Swarm Intelligence Energy Efficient Clustered Routing Algorithm for Wireless Sensor Networks

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Rajeev Kumar

2016-01-01

Full Text Available Currently, wireless sensor networks (WSNs are used in many applications, namely, environment monitoring, disaster management, industrial automation, and medical electronics. Sensor nodes carry many limitations like low battery life, small memory space, and limited computing capability. To create a wireless sensor network more energy efficient, swarm intelligence technique has been applied to resolve many optimization issues in WSNs. In many existing clustering techniques an artificial bee colony (ABC algorithm is utilized to collect information from the field periodically. Nevertheless, in the event based applications, an ant colony optimization (ACO is a good solution to enhance the network lifespan. In this paper, we combine both algorithms (i.e., ABC and ACO and propose a new hybrid ABCACO algorithm to solve a Nondeterministic Polynomial (NP hard and finite problem of WSNs. ABCACO algorithm is divided into three main parts: (i selection of optimal number of subregions and further subregion parts, (ii cluster head selection using ABC algorithm, and (iii efficient data transmission using ACO algorithm. We use a hierarchical clustering technique for data transmission; the data is transmitted from member nodes to the subcluster heads and then from subcluster heads to the elected cluster heads based on some threshold value. Cluster heads use an ACO algorithm to discover the best route for data transmission to the base station (BS. The proposed approach is very useful in designing the framework for forest fire detection and monitoring. The simulation results show that the ABCACO algorithm enhances the stability period by 60% and also improves the goodput by 31% against LEACH and WSNCABC, respectively.

Self-tuning control algorithm design for vehicle adaptive cruise control system through real-time estimation of vehicle parameters and road grade

Science.gov (United States)

Marzbanrad, Javad; Tahbaz-zadeh Moghaddam, Iman

2016-09-01

The main purpose of this paper is to design a self-tuning control algorithm for an adaptive cruise control (ACC) system that can adapt its behaviour to variations of vehicle dynamics and uncertain road grade. To this aim, short-time linear quadratic form (STLQF) estimation technique is developed so as to track simultaneously the trend of the time-varying parameters of vehicle longitudinal dynamics with a small delay. These parameters are vehicle mass, road grade and aerodynamic drag-area coefficient. Next, the values of estimated parameters are used to tune the throttle and brake control inputs and to regulate the throttle/brake switching logic that governs the throttle and brake switching. The performance of the designed STLQF-based self-tuning control (STLQF-STC) algorithm for ACC system is compared with the conventional method based on fixed control structure regarding the speed/distance tracking control modes. Simulation results show that the proposed control algorithm improves the performance of throttle and brake controllers, providing more comfort while travelling, enhancing driving safety and giving a satisfactory performance in the presence of different payloads and road grade variations.

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 algorithm on simultaneous optimization of performance and mass parameters of open-cycle liquid-propellant engine of launch vehicles

Science.gov (United States)

Eskandari, M. A.; Mazraeshahi, H. K.; Ramesh, D.; Montazer, E.; Salami, E.; Romli, F. I.

2017-12-01

In this paper, a new method for the determination of optimum parameters of open-cycle liquid-propellant engine of launch vehicles is introduced. The parameters affecting the objective function, which is the ratio of specific impulse to gross mass of the launch vehicle, are chosen to achieve maximum specific impulse as well as minimum mass for the structure of engine, tanks, etc. The proposed algorithm uses constant integration of thrust with respect to time for launch vehicle with specific diameter and length to calculate the optimum working condition. The results by this novel algorithm are compared to those obtained from using Genetic Algorithm method and they are also validated against the results of existing launch vehicle.

Novel control algorithm of braking energy regeneration system for an electric vehicle during safety–critical driving maneuvers

International Nuclear Information System (INIS)

Lv, Chen; Zhang, Junzhi; Li, Yutong; Yuan, Ye

2015-01-01

Highlights: • Models of an electric vehicle with regenerative braking system (RBS) are built. • Control algorithm of RBS under safety–critical driving maneuvers is proposed. • Simulations and HIL tests of the proposed strategy are conducted. • Performance improvement of vehicle’s mean deceleration is up to 13.89%. • Test results verify the feasibility and effectiveness of the proposed method. - Abstract: This paper mainly focuses on control algorithm of the braking energy regeneration system of an electric bus under safety–critical driving situations. With the aims of guaranteeing vehicle stability in various types of tyre–road adhesion conditions, based on the characteristics of electrified powertrain, a novel control algorithm of regenerative braking system is proposed for electric vehicles during anti-lock braking procedures. First, the models of vehicle dynamics and main components including braking energy regenerative system of the case-study electric bus are built in MATLAB/Simulink. Then, based on the phase-plane method, the optimal brake torque is calculated for ABS control of vehicle. Next, a novel allocation strategy, wherein the target optimal brake torque is divided into two parts that are handled separately by the regenerative and friction brakes, is developed. Simulations of the proposed control strategy are conducted based on system models built using MATLAB/Simulink. The simulation results demonstrate that the developed strategy enables improved control in terms of vehicle stability and braking performance under different emergency driving conditions. To further verify the synthesized control algorithm, hardware-in-the-loop tests are also performed. The experimental results validate the simulation data and verify the feasibility and effectiveness of the developed control algorithm.

An energy efficient multiple mobile sinks based routing algorithm for wireless sensor networks

Science.gov (United States)

Zhong, Peijun; Ruan, Feng

2018-03-01

With the fast development of wireless sensor networks (WSNs), more and more energy efficient routing algorithms have been proposed. However, one of the research challenges is how to alleviate the hot spot problem since nodes close to static sink (or base station) tend to die earlier than other sensors. The introduction of mobile sink node can effectively alleviate this problem since sink node can move along certain trajectories, causing hot spot nodes more evenly distributed. In this paper, we mainly study the energy efficient routing method with multiple mobile sinks support. We divide the whole network into several clusters and study the influence of mobile sink number on network lifetime. Simulation results show that the best network performance appears when mobile sink number is about 3 under our simulation environment.

PSO-Based Algorithm Applied to Quadcopter Micro Air Vehicle Controller Design

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Huu-Khoa Tran

2016-09-01

Full Text Available Due to the rapid development of science and technology in recent times, many effective controllers are designed and applied successfully to complicated systems. The significant task of controller design is to determine optimized control gains in a short period of time. With this purpose in mind, a combination of the particle swarm optimization (PSO-based algorithm and the evolutionary programming (EP algorithm is introduced in this article. The benefit of this integration algorithm is the creation of new best-parameters for control design schemes. The proposed controller designs are then demonstrated to have the best performance for nonlinear micro air vehicle models.

FORMATION ALGORITHM OF DYNAMIC TURN FOR UNMANNED AERIAL VEHICLES ON APPROACH

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Igor A. Chekhov

2017-01-01

Full Text Available Great interest in using unmanned aerial vehicles has recently been shown, both from economic entities, and from national security, defense and law enforcement agencies. However, for using UAV for the civil purposes there is now a number of problems which are connected with the use of airspace and without solving them it is impossible to use the UAV fully. It should be noted that the level of flight safety, both for regular aircraft, and for the UAV, has the primary value. It is necessary to use modern methods of data processing and to have an opportunity to quickly and effectively control the current flight safety level. For this purpose the fullest information on the current movement of aircraft and unmanned aerial vehicles, and also on the structure of the used airspace has to be used. The problem of procedures and maneuvers development that resolve potential traffic conflict including the UAV, is extremely important for air traffic safety especially in the vicinity of the destination or landing aerodrome. The possibility of creation of an algorithm of dynamic turn formation and the choice of a trajectory on approach of unmanned aerial vehicles is considered in this article. The technology of automatic dependent surveillance broadcast was used when collecting statistical data. Implementation of the landing algorithm is executed based on the criteria of ensuring efficiency and flight safety. The developed software provides the use only of open data on the aircraft movement in terminal airspace. The suggested algorithm can be adapted for air traffic management of the UAV in any selected airspace.

Efficient distribution of toy products using ant colony optimization algorithm