Energy Technology Data Exchange (ETDEWEB)
Laporte, G.
1987-01-01
Location-routing problems involve simultaneously locating a number of facilities among candidate sites and establishing delivery routes to a set of users in such a way that the total system cost is minimized. This paper presents a survey of such problems. It includes some applications and examples of location-routing problems, a description of the main heuristics that have been developed for such problems, and reviews of various formulations and algorithms used in solving these problems. A more detailed review is given of exact algorithms for the vehicle routing problem, three-index vehicle flow formulations, and two-index vehicle flow formulations and algorithms for symmetrical and non-symmetrical problems. It is concluded that location-routing problem research is a fast-growing area, with most developments occurring over the past few years; however, research is relatively fragmented, often addresses problems which are too specific and contains several voids which have yet to be filled. A number of promising research areas are identified. 137 refs., 3 figs.
Modeling a four-layer location-routing problem
Directory of Open Access Journals (Sweden)
Mohsen Hamidi
2012-01-01
Full Text Available Distribution is an indispensable component of logistics and supply chain management. Location-Routing Problem (LRP is an NP-hard problem that simultaneously takes into consideration location, allocation, and vehicle routing decisions to design an optimal distribution network. Multi-layer and multi-product LRP is even more complex as it deals with the decisions at multiple layers of a distribution network where multiple products are transported within and between layers of the network. This paper focuses on modeling a complicated four-layer and multi-product LRP which has not been tackled yet. The distribution network consists of plants, central depots, regional depots, and customers. In this study, the structure, assumptions, and limitations of the distribution network are defined and the mathematical optimization programming model that can be used to obtain the optimal solution is developed. Presented by a mixed-integer programming model, the LRP considers the location problem at two layers, the allocation problem at three layers, the vehicle routing problem at three layers, and a transshipment problem. The mathematical model locates central and regional depots, allocates customers to plants, central depots, and regional depots, constructs tours from each plant or open depot to customers, and constructs transshipment paths from plants to depots and from depots to other depots. Considering realistic assumptions and limitations such as producing multiple products, limited production capacity, limited depot and vehicle capacity, and limited traveling distances enables the user to capture the real world situations.
A Memetic Algorithm for the Capacitated Location-Routing Problem
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Laila KECHMANE
2016-06-01
Full Text Available In this paper, a hybrid genetic algorithm is proposed to solve a Capacitated Location-Routing Problem. The objective is to minimize the total cost of the distribution in a network composed of depots and customers, both depots and vehicles have limited capacities, each depot has a homogenous vehicle fleet and customers’ demands are known and must be satisfied. Solving this problem involves making strategic decisions such as the location of depots, as well as tactical and operational decisions which include assigning customers to the opened depots and organization of the vehicle routing. To evaluate the performance of the proposed algorithm, its results are compared to those obtained by a greedy randomized adaptive search procedure, computational results shows that the algorithm gave good quality solutions.
Optimization of location routing inventory problem with transshipment
Ghani, Nor Edayu Abd; Shariff, S. Sarifah Radiah; Zahari, Siti Meriam
2015-05-01
Location Routing Inventory Problem (LRIP) is a collaboration of the three components in the supply chain. It is confined by location-allocation, vehicle routing and inventory management. The aim of the study is to minimize the total system cost in the supply chain. Transshipment is introduced in order to allow the products to be shipped to a customer who experiences a shortage, either directly from the supplier or from another customer. In the study, LRIP is introduced with the transshipment (LRIPT) and customers act as the transshipment points. We select the transshipment point by using the p-center and we present the results in two divisions of cases. Based on the analysis, the results indicated that LRIPT performed well compared to LRIP.
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.
Location-routing Problem with Fuzzy time windows and Traffic time
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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.
Green open location-routing problem considering economic and environmental costs
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Eliana M. Toro
2016-12-01
Full Text Available This paper introduces a new bi-objective vehicle routing problem that integrates the Open Location Routing Problem (OLRP, recently presented in the literature, coupled with the growing need for fuel consumption minimization, named Green OLRP (G-OLRP. Open routing problems (ORP are known to be NP-hard problems, in which vehicles start from the set of existing depots and are not required to return to the starting depot after completing their service. The OLRP is a strategic-level problem involving the selection of one or many depots from a set of candidate locations and the planning of delivery radial routes from the selected depots to a set of customers. The concept of radial paths allows us to use a set of constraints focused on maintaining the radiality condition of the paths, which significantly simplifies the set of constraints associated with the connectivity and capacity requirements and provides a suitable alternative when compared with the elimination problem of sub-tours traditionally addressed in the literature. The emphasis in the paper will be placed on modeling rather than solution methods. The model proposed is formulated as a bi-objective problem, considering the minimization of operational costs and the minimization of environmental effects, and it is solved by using the epsilon constraint technique. The results illustrate that the proposed model is able to generate a set of trade-off solutions leading to interesting conclusions about the relationship between operational costs and environmental impact.
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 variable neighborhood descent based heuristic to solve the capacitated location-routing problem
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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.
A Mathematical Model for the Industrial Hazardous Waste Location-Routing Problem
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Omid Boyer
2013-01-01
Full Text Available Technology progress is a cause of industrial hazardous wastes increasing in the whole world . Management of hazardous waste is a significant issue due to the imposed risk on environment and human life. This risk can be a result of location of undesirable facilities and also routing hazardous waste. In this paper a biobjective mixed integer programing model for location-routing industrial hazardous waste with two objectives is developed. First objective is total cost minimization including transportation cost, operation cost, initial investment cost, and cost saving from selling recycled waste. Second objective is minimization of transportation risk. Risk of population exposure within bandwidth along route is used to measure transportation risk. This model can help decision makers to locate treatment, recycling, and disposal centers simultaneously and also to route waste between these facilities considering risk and cost criteria. The results of the solved problem prove conflict between two objectives. Hence, it is possible to decrease the cost value by marginally increasing the transportation risk value and vice versa. A weighted sum method is utilized to combine two objectives function into one objective function. To solve the problem GAMS software with CPLEX solver is used. The problem is applied in Markazi province in Iran.
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.
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.
Cost Optimisation in Freight Distribution with Cross-Docking: N-Echelon Location Routing Problem
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Jesus Gonzalez-Feliu
2012-03-01
Full Text Available Freight transportation constitutes one of the main activities that influence the economy and society, as it assures a vital link between suppliers and customers and represents a major source of employment. Multi-echelon distribution is one of the most common strategies adopted by the transportation companies in an aim of cost reduction. Although vehicle routing problems are very common in operational research, they are essentially related to single-echelon cases. This paper presents the main concepts of multi-echelon distribution with cross-docks and a unified notation for the N-echelon location routing problem. A literature review is also presented, in order to list the main problems and methods that can be helpful for scientists and transportation practitioners.
A new approach on auxiliary vehicle assignment in capacitated location routing problem
Bashiri, Mahdi; Rasoulinejad, Zeinab; Fallahzade, Ehsan
2016-03-01
The location routing problem (LRP) considers locating depots and vehicle routing decisions simultaneously. In classic LRP the number of customers in each route depends on the capacity of the vehicle. In this paper a capacitated LRP model with auxiliary vehicle assignment is presented in which the length of each route is not restricted by main vehicle capacity. Two kinds of vehicles are considered: main vehicles with higher capacity and fixed cost and auxiliary vehicles with lower capacity and fixed cost. The auxiliary vehicles can be added to the transportation system as an alternative strategy to cover the capacity limitations and they are just used to transfer goods from depots to vehicles and cannot serve the customers by themselves. To show the applicability of the proposed model, some numerical examples derived from the well-known instances are used. Moreover the model has been solved by some meta-heuristics for large sized instances. The results show the efficiency of the proposed model and the solution approach, considering the classic model and the exact solution approach, respectively.
Routing and scheduling problems
DEFF Research Database (Denmark)
Reinhardt, Line Blander
be that the objects routed have an availability time window and a delivery time window or that locations on the path have a service time window. When routing moving transportation objects such as vehicles and vessels schedules are made in connection with the routing. Such schedules represent the time for the presence...... to a destination on a predefined network, the routing and scheduling of vessels in a liner shipping network given a demand forecast to be covered, the routing of manpower and vehicles transporting disabled passengers in an airport and the vehicle routing with time windows where one version studied includes edge...... of a connection between two locations. This could be an urban bus schedule where busses are routed and this routing creates a bus schedule which the passengers between locations use. In this thesis various routing and scheduling problems will be presented. The topics covered will be routing from an origin...
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Hossein Asefi
2015-09-01
Full Text Available Municipal solid waste management is one of the challenging issues in mega cities due to various interrelated factors such as operational costs and environmental concerns. Cost as one of the most significant constraints of municipal solid waste management can be effectively economized by efficient planning approaches. Considering diverse waste types in an integrated municipal solid waste system, a mathematical model of the location-routing problem is formulated and solved in this study in order to minimize the total cost of transportation and facility establishment.
A heuristic algorithm for a multi-product four-layer capacitated location-routing problem
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Mohsen Hamidi
2014-01-01
Full Text Available The purpose of this study is to solve a complex multi-product four-layer capacitated location-routing problem (LRP in which two specific constraints are taken into account: 1 plants have limited production capacity, and 2 central depots have limited capacity for storing and transshipping products. The LRP represents a multi-product four-layer distribution network that consists of plants, central depots, regional depots, and customers. A heuristic algorithm is developed to solve the four-layer LRP. The heuristic uses GRASP (Greedy Randomized Adaptive Search Procedure and two probabilistic tabu search strategies of intensification and diversification to tackle the problem. Results show that the heuristic solves the problem effectively.
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.
Lower and upper bounds for the two-echelon capacitated location-routing problem
Contardo, Claudio; Hemmelmayr, Vera; Crainic, Teodor Gabriel
2012-01-01
In this paper, we introduce two algorithms to address the two-echelon capacitated location-routing problem (2E-CLRP). We introduce a branch-and-cut algorithm based on the solution of a new two-index vehicle-flow formulation, which is strengthened with several families of valid inequalities. We also propose an adaptive large-neighbourhood search (ALNS) meta-heuristic with the objective of finding good-quality solutions quickly. The computational results on a large set of instances from the literature show that the ALNS outperforms existing heuristics. Furthermore, the branch-and-cut method provides tight lower bounds and is able to solve small- and medium-size instances to optimality within reasonable computing times. PMID:24511176
Lower and upper bounds for the two-echelon capacitated location-routing problem.
Contardo, Claudio; Hemmelmayr, Vera; Crainic, Teodor Gabriel
2012-12-01
In this paper, we introduce two algorithms to address the two-echelon capacitated location-routing problem (2E-CLRP). We introduce a branch-and-cut algorithm based on the solution of a new two-index vehicle-flow formulation, which is strengthened with several families of valid inequalities. We also propose an adaptive large-neighbourhood search (ALNS) meta-heuristic with the objective of finding good-quality solutions quickly. The computational results on a large set of instances from the literature show that the ALNS outperforms existing heuristics. Furthermore, the branch-and-cut method provides tight lower bounds and is able to solve small- and medium-size instances to optimality within reasonable computing times.
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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
Tavakkoli-Moghaddam, Reza; Forouzanfar, Fateme; Ebrahimnejad, Sadoullah
2013-07-01
This paper considers a single-sourcing network design problem for a three-level supply chain. For the first time, a novel mathematical model is presented considering risk-pooling, the inventory existence at distribution centers (DCs) under demand uncertainty, the existence of several alternatives to transport the product between facilities, and routing of vehicles from distribution centers to customer in a stochastic supply chain system, simultaneously. This problem is formulated as a bi-objective stochastic mixed-integer nonlinear programming model. The aim of this model is to determine the number of located distribution centers, their locations, and capacity levels, and allocating customers to distribution centers and distribution centers to suppliers. It also determines the inventory control decisions on the amount of ordered products and the amount of safety stocks at each opened DC, selecting a type of vehicle for transportation. Moreover, it determines routing decisions, such as determination of vehicles' routes starting from an opened distribution center to serve its allocated customers and returning to that distribution center. All are done in a way that the total system cost and the total transportation time are minimized. The Lingo software is used to solve the presented model. The computational results are illustrated in this paper.
Meysam Mousavi, S.; Tavakkoli-Moghaddam, Reza; Jolai, Fariborz
2013-10-01
This article considers the design of cross-docking systems under uncertainty in a model that consists of two phases: (1) a strategic-based decision-making process for selecting the location of cross-docks to operate, and (2) an operational-based decision-making process for vehicle routing scheduling with multiple cross-docks. This logistic system contains three echelons, namely suppliers, cross-docks and retailers, in an uncertain environment. In the first phase, a new multi-period cross-dock location model is introduced to determine the minimum number of cross-docks among a set of location sites so that each retailer demand should be met. Then, in the second phase, a new vehicle routing scheduling model with multiple cross-docks is formulated in which each vehicle is able to pickup from or deliver to more than one supplier or retailer, and the pickup and delivery routes start and end at the corresponding cross-dock. This article is the first attempt to introduce an integrated model for cross-docking systems design under a fuzzy environment. To solve the presented two-phase mixed-integer programming (MIP) model, a new fuzzy mathematical programming-based possibilistic approach is used. Furthermore, experimental tests are carried out to demonstrate the effectiveness of the presented model. The computational results reveal the applicability and suitability of the developed fuzzy possibilistic two-phase model in a variety of problems in the domain of cross-docking systems.
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Hao Yu
2016-05-01
Full Text Available Hazardous waste location-routing problems are of importance due to the potential risk for nearby residents and the environment. In this paper, an improved mathematical formulation is developed based upon a multi-objective mixed integer programming approach. The model aims at assisting decision makers in selecting locations for different facilities including treatment plants, recycling plants and disposal sites, providing appropriate technologies for hazardous waste treatment, and routing transportation. In the model, two critical factors are taken into account: system operating costs and risk imposed on local residents, and a compensation factor is introduced to the risk objective function in order to account for the fact that the risk level imposed by one type of hazardous waste or treatment technology may significantly vary from that of other types. Besides, the policy instruments for promoting waste recycling are considered, and their influence on the costs and risk of hazardous waste management is also discussed. The model is coded and calculated in Lingo optimization solver, and the augmented ε-constraint method is employed to generate the Pareto optimal curve of the multi-objective optimization problem. The trade-off between different objectives is illustrated in the numerical experiment.
Yu, Hao; Solvang, Wei Deng
2016-01-01
Hazardous waste location-routing problems are of importance due to the potential risk for nearby residents and the environment. In this paper, an improved mathematical formulation is developed based upon a multi-objective mixed integer programming approach. The model aims at assisting decision makers in selecting locations for different facilities including treatment plants, recycling plants and disposal sites, providing appropriate technologies for hazardous waste treatment, and routing transportation. In the model, two critical factors are taken into account: system operating costs and risk imposed on local residents, and a compensation factor is introduced to the risk objective function in order to account for the fact that the risk level imposed by one type of hazardous waste or treatment technology may significantly vary from that of other types. Besides, the policy instruments for promoting waste recycling are considered, and their influence on the costs and risk of hazardous waste management is also discussed. The model is coded and calculated in Lingo optimization solver, and the augmented ε-constraint method is employed to generate the Pareto optimal curve of the multi-objective optimization problem. The trade-off between different objectives is illustrated in the numerical experiment. PMID:27258293
Yu, Hao; Solvang, Wei Deng
2016-05-31
Hazardous waste location-routing problems are of importance due to the potential risk for nearby residents and the environment. In this paper, an improved mathematical formulation is developed based upon a multi-objective mixed integer programming approach. The model aims at assisting decision makers in selecting locations for different facilities including treatment plants, recycling plants and disposal sites, providing appropriate technologies for hazardous waste treatment, and routing transportation. In the model, two critical factors are taken into account: system operating costs and risk imposed on local residents, and a compensation factor is introduced to the risk objective function in order to account for the fact that the risk level imposed by one type of hazardous waste or treatment technology may significantly vary from that of other types. Besides, the policy instruments for promoting waste recycling are considered, and their influence on the costs and risk of hazardous waste management is also discussed. The model is coded and calculated in Lingo optimization solver, and the augmented ε-constraint method is employed to generate the Pareto optimal curve of the multi-objective optimization problem. The trade-off between different objectives is illustrated in the numerical experiment.
Rabbani, Masoud; Farrokhi-Asl, Hamed; Asgarian, Bahare
2017-10-01
It is observed that the separated design of location for depots and routing for servicing customers often reach a suboptimal solution. So, solving location and routing problem simultaneously could achieve better results. In this paper, waste collection problem is considered with regard to economic and societal objective functions. A non-dominated sorting genetic algorithm (NSGA-II) is used to locate depots and treatment facilities and design the routes starting from depots to serve customers. A new mathematical model is proposed and two objective functions including economic objective (opening cost of depots and treatment facility and transportation cost) and societal objective; that is, negative impact of treatment facilities which are close to towns are addressed in this study. A straightforward order based solution representation is applied for coding solutions of the problem and clustering approach is used to generate appropriate initial solutions. Moreover, three multi-objective decomposition methods including weighted sum, goal programming, and goal attainment are applied to validate the performance of the proposed algorithm. Number of test problems are conducted and the results obtained by algorithms are compared with respect to some comparison metrics. Finally, the experimental results show that the proposed hybrid NSGA-II outperforms all decomposition methods, but the computational times for decomposition methods are less than NSGA-II.
Rabbani, Masoud; Farrokhi-Asl, Hamed; Asgarian, Bahare
2016-10-01
It is observed that the separated design of location for depots and routing for servicing customers often reach a suboptimal solution. So, solving location and routing problem simultaneously could achieve better results. In this paper, waste collection problem is considered with regard to economic and societal objective functions. A non-dominated sorting genetic algorithm (NSGA-II) is used to locate depots and treatment facilities and design the routes starting from depots to serve customers. A new mathematical model is proposed and two objective functions including economic objective (opening cost of depots and treatment facility and transportation cost) and societal objective; that is, negative impact of treatment facilities which are close to towns are addressed in this study. A straightforward order based solution representation is applied for coding solutions of the problem and clustering approach is used to generate appropriate initial solutions. Moreover, three multi-objective decomposition methods including weighted sum, goal programming, and goal attainment are applied to validate the performance of the proposed algorithm. Number of test problems are conducted and the results obtained by algorithms are compared with respect to some comparison metrics. Finally, the experimental results show that the proposed hybrid NSGA-II outperforms all decomposition methods, but the computational times for decomposition methods are less than NSGA-II.
Locating Depots for Capacitated Vehicle Routing
DEFF Research Database (Denmark)
Gørtz, Inge Li; Nagarajan, Viswanath
2016-01-01
We study a location-routing problem in the context of capacitated vehicle routing. The input to the k-location capacitated vehicle routing problem (k-LocVRP) consists of a set of demand locations in a metric space and a fleet of k identical vehicles, each of capacity Q. The objective is to locate k...... depots, one for each vehicle, and compute routes for the vehicles so that all demands are satisfied and the total cost is minimized. Our main result is a constant-factor approximation algorithm for k-LocVRP. In obtaining this result, we introduce a common generalization of the k-median and minimum...... spanning tree problems (called k median forest), which might be of independent interest. We give a local-search based (3+ε)-approximation algorithm for k median forest, which leads to a (12+ε)-approximation algorithm for k-LocVRP, for any constant ε>0....
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Lin Zhou
2016-08-01
Full Text Available With the increasing interest in online shopping, the Last Mile delivery is regarded as one of the most expensive and pollutive—and yet the least efficient—stages of the e-commerce supply chain. To address this challenge, a novel location-routing problem with simultaneous home delivery and customer’s pickup is proposed. This problem aims to build a more effective Last Mile distribution system by providing two kinds of service options when delivering packages to customers. To solve this specific problem, a hybrid evolution search algorithm by combining genetic algorithm (GA and local search (LS is presented. In this approach, a diverse population generation algorithm along with a two-phase solution initialization heuristic is first proposed to give high quality initial population. Then, advantaged solution representation, individual evaluation, crossover and mutation operations are designed to enhance the evolution and search efficiency. Computational experiments based on a large family of instances are conducted, and the results obtained indicate the validity of the proposed model and method.
Cumulative Vehicle Routing Problems
Kara, &#;mdat; Kara, Bahar Yeti&#;; Yeti&#;, M. Kadri
2008-01-01
This paper proposes a new objective function and corresponding formulations for the vehicle routing problem. The new cost function defined as the product of the distance of the arc and the flow on that arc. We call a vehicle routing problem with this new objective function as the Cumulative Vehicle Routing Problem (CumVRP). Integer programming formulations with O(n2) binary variables and O(n2) constraints are developed for both collection and delivery cases. We show that the CumVRP is a gener...
Routing and scheduling problems
DEFF Research Database (Denmark)
Reinhardt, Line Blander
In today’s globalized society, transport contributes to our daily life in many different ways. The production of the parts for a shelf ready product may take place on several continents and our travel between home and work, vacation travel and business trips has increased in distance the last......, the effectiveness of the network is of importance aiming at satisfying as many costumer demands as possible at a low cost. Routing represent a path between locations such as an origin and destination for the object routed. Sometimes routing has a time dimension as well as the physical paths. This may...... to a destination on a predefined network, the routing and scheduling of vessels in a liner shipping network given a demand forecast to be covered, the routing of manpower and vehicles transporting disabled passengers in an airport and the vehicle routing with time windows where one version studied includes edge...
Vehicle Routing Problem Models
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Tonči Carić
2004-01-01
Full Text Available The Vehicle Routing Problem cannot always be solved exactly,so that in actual application this problem is solved heuristically.The work describes the concept of several concrete VRPmodels with simplified initial conditions (all vehicles are ofequal capacity and start from a single warehouse, suitable tosolve problems in cases with up to 50 users.
Locating Depots for Capacitated Vehicle Routing
Goertz, Inge Li
2011-01-01
We study a location-routing problem in the context of capacitated vehicle routing. The input 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 that all demands are satisfied and the total cost is minimized. Our main result is a constant-factor approximation algorithm for this problem. To achieve this result, we reduce to the k-median-forest problem, which generalizes both k-median and minimum spanning tree, and which might be of independent interest. We give a (3+c)-approximation algorithm for k-median-forest, which leads to a (12+c)-approximation algorithm for the above location-routing problem, for any constant c>0. The algorithm for k-median-forest is just t-swap local search, and we prove that it has locality gap 3+2/t; this generalizes the corresponding result known for k-median. Finally we consider the "non-uniform" k-median-forest problem which has different cost ...
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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.
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.
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
Fazayeli, Saeed; Eydi, Alireza; Kamalabadi, Isa Nakhai
2017-07-01
Nowadays, organizations have to compete with different competitors in regional, national and international levels, so they have to improve their competition capabilities to survive against competitors. Undertaking activities on a global scale requires a proper distribution system which could take advantages of different transportation modes. Accordingly, the present paper addresses a location-routing problem on multimodal transportation network. The introduced problem follows four objectives simultaneously which form main contribution of the paper; determining multimodal routes between supplier and distribution centers, locating mode changing facilities, locating distribution centers, and determining product delivery tours from the distribution centers to retailers. An integer linear programming is presented for the problem, and a genetic algorithm with a new chromosome structure proposed to solve the problem. Proposed chromosome structure consists of two different parts for multimodal transportation and location-routing parts of the model. Based on published data in the literature, two numerical cases with different sizes generated and solved. Also, different cost scenarios designed to better analyze model and algorithm performance. Results show that algorithm can effectively solve large-size problems within a reasonable time which GAMS software failed to reach an optimal solution even within much longer times.
Ghezavati, V. R.; Beigi, M.
2016-06-01
During the last decade, the stringent pressures from environmental and social requirements have spurred an interest in designing a reverse logistics (RL) network. The success of a logistics system may depend on the decisions of the facilities locations and vehicle routings. The location-routing problem (LRP) simultaneously locates the facilities and designs the travel routes for vehicles among established facilities and existing demand points. In this paper, the location-routing problem with time window (LRPTW) and homogeneous fleet type and designing a multi-echelon, and capacitated reverse logistics network, are considered which may arise in many real-life situations in logistics management. Our proposed RL network consists of hybrid collection/inspection centers, recovery centers and disposal centers. Here, we present a new bi-objective mathematical programming (BOMP) for LRPTW in reverse logistic. Since this type of problem is NP-hard, the non-dominated sorting genetic algorithm II (NSGA-II) is proposed to obtain the Pareto frontier for the given problem. Several numerical examples are presented to illustrate the effectiveness of the proposed model and algorithm. Also, the present work is an effort to effectively implement the ɛ-constraint method in GAMS software for producing the Pareto-optimal solutions in a BOMP. The results of the proposed algorithm have been compared with the ɛ-constraint method. The computational results show that the ɛ-constraint method is able to solve small-size instances to optimality within reasonable computing times, and for medium-to-large-sized problems, the proposed NSGA-II works better than the ɛ-constraint.
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.
Directory of Open Access Journals (Sweden)
Shuai Deng
2016-01-01
Full Text Available This paper presents a closed-loop location-inventory-routing problem model considering both quality defect returns and nondefect returns in e-commerce supply chain system. The objective is to minimize the total cost produced in both forward and reverse logistics networks. We propose a combined optimization algorithm named hybrid ant colony optimization algorithm (HACO to address this model that is an NP-hard problem. Our experimental results show that the proposed HACO is considerably efficient and effective in solving this model.
Locating Depots for Capacitated Vehicle Routing
DEFF Research Database (Denmark)
Gørtz, Inge Li; Nagarajan, Viswanath
2011-01-01
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...... 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...
Routing helicopters for crew exchanges on off-shore locations
Sierksma, G.; Tijssen, G.A.
1998-01-01
This paper deals with a vehicle routing problem with split demands, namely the problem of determining a flight schedule for helicopters to off-shore platform locations for exchanging crew people employed on these platforms. The problem is formulated as an LP model and solved by means of a column-gen
Solution to a two-phase tabu algorithm for location routing problem%定位路线问题的两阶段禁忌搜索算法研究
Institute of Scientific and Technical Information of China (English)
徐丽蕊; 李静
2011-01-01
Location routing problem is the integrated decision of location allocation problem and vehicle routing problem. This paper describes the location routing problem, sets up the mathematical model of this problem, and validates the model by Lingo 10. 0. Because this model is a NP-hard problem, to solve this problem, a two-phase tabu search algorithms was designed. At the first phase, the problems of location allocation to fix on the facility and custom allocation were solved by tabu search algorithms; at the second phase, the vehicle routing problem was solved by tabu search algorithms; by a large number of iterative from location to routing phases, the optimizing solution to the location routing can be obtained. Comparing with the related literature , the computing result shows that the designed algorithm is practicable and effective to solve this problem.%定位路线问题是定位配给和车辆路线问题的集成.分析了定位路线问题的含义,建立了此问题的数学模型,并用Lingo 10.0验证了模型的正确性.由于该模型属于NP-hard问题,设计了两阶段禁忌搜索算法:第一阶段用禁忌搜索算法求解定位配给问题,确定设施定位及客户分配;第二阶段用禁忌搜索算法求解车辆路线问题,经过两个阶段的多次迭代求得定位路线问题的优化解,通过实例计算验证该算法的可行性和有效性.
The Consistent Vehicle Routing Problem
Energy Technology Data Exchange (ETDEWEB)
Groer, Christopher S [ORNL; Golden, Bruce [University of Maryland; Edward, Wasil [American University
2009-01-01
In the small package shipping industry (as in other industries), companies try to differentiate themselves by providing high levels of customer service. This can be accomplished in several ways, including online tracking of packages, ensuring on-time delivery, and offering residential pickups. Some companies want their drivers to develop relationships with customers on a route and have the same drivers visit the same customers at roughly the same time on each day that the customers need service. These service requirements, together with traditional constraints on vehicle capacity and route length, define a variant of the classical capacitated vehicle routing problem, which we call the consistent VRP (ConVRP). In this paper, we formulate the problem as a mixed-integer program and develop an algorithm to solve the ConVRP that is based on the record-to-record travel algorithm. We compare the performance of our algorithm to the optimal mixed-integer program solutions for a set of small problems and then apply our algorithm to five simulated data sets with 1,000 customers and a real-world data set with more than 3,700 customers. We provide a technique for generating ConVRP benchmark problems from vehicle routing problem instances given in the literature and provide our solutions to these instances. The solutions produced by our algorithm on all problems do a very good job of meeting customer service objectives with routes that have a low total travel time.
Location and Routing of the Defense Courier Service Aerial Network
1991-03-01
The Vehicle Routing Problem ................ 8 Vehicle Routing Problem Modifications ...... .0 Multiple Depot Problems...several specific formulations are applicable to the DCS aerial network. Those addressed in this review include: 1) the Vehicle Routing Problem (VRP); 2...methodologies show great promise for adaptation to the DCS network. The Vehicle Routing Problem The Travelling Salesman Problem seeks the shortest route which
The Balanced Billing Cycle Vehicle Routing Problem
Energy Technology Data Exchange (ETDEWEB)
Groer, Christopher S [ORNL; Golden, Bruce [University of Maryland; Edward, Wasil [American University
2009-01-01
Utility companies typically send their meter readers out each day of the billing cycle in order to determine each customer s usage for the period. Customer churn requires the utility company to periodically remove some customer locations from its meter-reading routes. On the other hand, the addition of new customers and locations requires the utility company to add newstops to the existing routes. A utility that does not adjust its meter-reading routes over time can find itself with inefficient routes and, subsequently, higher meter-reading costs. Furthermore, the utility can end up with certain billing days that require substantially larger meter-reading resources than others. However, remedying this problem is not as simple as it may initially seem. Certain regulatory and customer service considerations can prevent the utility from shifting a customer s billing day by more than a few days in either direction. Thus, the problem of reducing the meterreading costs and balancing the workload can become quite difficult. We describe this Balanced Billing Cycle Vehicle Routing Problem in more detail and develop an algorithm for providing solutions to a slightly simplified version of the problem. Our algorithm uses a combination of heuristics and integer programming via a three-stage algorithm. We discuss the performance of our procedure on a real-world data set.
A Review of the Discrete Facility Location Problem
Institute of Scientific and Technical Information of China (English)
WANG Fei; XU Yu; LI Yi-xue
2006-01-01
In this paper we attempt to classify discrete facility location problems in the right perspective and propose discrete facility location problems that include: median problems, covering problems, center problems, multi-commodities problems and dynamic problems on the basis of former research by other scholars. We consider vehicle routing location problems, inventory-location problems and hub problems as a recent research field of discrete facility location problems according to literature from the last 10 years.
Optimization of Logistic Distribution Center Location and Vehicle Routing Problem%配送中心选址与车辆路径问题的优化
Institute of Scientific and Technical Information of China (English)
汤雅连
2014-01-01
为了克服蚁群算法(Ant Colony Optimization,ACO)搜索初期信息匮乏、信息素累积时间长、求解速度慢的缺点,结合具有快速全局搜索能力的遗传算法(genetic algorithm,GA),同时引入混沌搜索和平滑机制,采用混沌搜索产生初始种群可以克服生成大量非可行解的缺陷,加速染色体向最优解收敛,平滑机制有助于对搜索空间进行更有效的搜索,构成混沌蚁群优化算法(Chaos Ant Colony Optimization,CACO).建立物流配送中心选址(logistic distribution center location)与车辆路径问题(vehicle routing problem,VRP)的数学模型,分别应用CACO和GA求解,对50客户规模的问题模型仿真,结果表明CACO优于GA.
A Capacitated Facility Location Approach for the Tanker Employment Problem
2005-03-01
Depot (MD) Vehicle Routing Problem (VRP) ......................................... 14 2.5 Capacitated Facility Location Problem (CFLP) with Sole...service receiver groups. In this sense the problem can be viewed as a multi-depot vehicle routing problem . Anchor points are two stationary points...for future research. 2.4 Multi-Depot (MD) Vehicle Routing Problem (VRP) Another approach to the Tanker Employment Problem is to model it as a VRP
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...
Duality in constrained location problems
DEFF Research Database (Denmark)
Juel, Henrik; Love, Robert F.
1987-01-01
The dual of a facility location problem with general norms, distance constraints, and linear constraints is formulated.......The dual of a facility location problem with general norms, distance constraints, and linear constraints is formulated....
Duality in constrained location problems
DEFF Research Database (Denmark)
Juel, Henrik; Love, Robert F.
1987-01-01
The dual of a facility location problem with general norms, distance constraints, and linear constraints is formulated.......The dual of a facility location problem with general norms, distance constraints, and linear constraints is formulated....
A Genetic Algorithm on Inventory Routing Problem
Directory of Open Access Journals (Sweden)
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.
Location-Aided Reliable Routing for Opportunistic Networks
Institute of Scientific and Technical Information of China (English)
Yong Yang; Zhi Ren; Jibi Li
2012-01-01
In our study, we investigate the problem of location-based routing in opportunistic networks. Due to the uncertainty of end-to-end paths between sources and destinations, the classical location-based ad hoc routing protocols cannot adapt to the environment of opportunistic networks, which leads to the decrease of the delivery rate of data. To address it, we propose in this paper a novel location-aided routing protocol which is suitable for opportunistic networks. In our protocol, a node can send location information on demand by using prediction mechanism, and when sending a data packet, the node chooses multiple neighbors which are closer to the destination as next hops. If the candidate neighbors do not exist, the node carries the data till it meets a proper neighbor or the destination. Theoretical analysis and simulation results show that our proposed protocol outperforms DREAM (Distance Routing Effect Protocol Mobility) and one of its improved versions, BFDREAM (Boundary Forwarding DREAM), in terms of the delivery rate and overhead.
Route Elimination Heuristic for Vehicle Routing Problem with Time Windows
Directory of Open Access Journals (Sweden)
Sándor Csiszár
2005-11-01
Full Text Available The paper deals with the design of a route elimination (RE algorithm for thevehicle routing problem with time windows (VRPTW. The problem has two objectives, oneof them is the minimal number of routes the other is the minimal cost. To cope with theseobjectives effectively two-phase solutions are often suggested in the relevant literature. Inthe first phase the main focus is the route elimination, in the second one it is the costreduction. The algorithm described here is a part of a complete VRPWT study. The methodwas developed by studying the graph behaviour during the route elimination. For thispurpose a model -called “Magic Bricks” was developed. The computation results on theSolomon problem set show that the developed algorithm is competitive with the best ones.
Vehicle routing problem in investment fund allocation
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.
Hull properties in location problems
DEFF Research Database (Denmark)
Juel, Henrik; Love, Robert F.
1983-01-01
Some properties of the solution set for single and multifacility continuous location problems with lp distances are given. A set reduction algorithm is developed for problems in k-dimensional space having rectangular distances.......Some properties of the solution set for single and multifacility continuous location problems with lp distances are given. A set reduction algorithm is developed for problems in k-dimensional space having rectangular distances....
On green routing and scheduling problem
Touati, Nora
2012-01-01
The vehicle routing and scheduling problem has been studied with much interest within the last four decades. In this paper, some of the existing literature dealing with routing and scheduling problems with environmental issues is reviewed, and a description is provided of the problems that have been investigated and how they are treated using combinatorial optimization tools.
On green routing and scheduling problem
Touati, Nora; Jost, Vincent
2011-01-01
The vehicle routing and scheduling problem has been studied with much interest within the last four decades. In this paper, some of the existing literature dealing with routing and scheduling problems with environmental issues is reviewed, and a description is provided of the problems that have been investigated and how they are treated using combinatorial optimization tools.
Uncapacitated facility location problems: contributions
Directory of Open Access Journals (Sweden)
Galvão Roberto Diéguez
2004-01-01
Full Text Available The objective of the present paper is to review my personal contributions in the field of uncapacitated facility location problems. These contributions took place throughout my academic career, from the time I was a Ph.D. student at Imperial College to the present day. They cover approximately 30 years, from 1973 to 2003; they address: algorithms developed for the p-median problem and for a general formulation of uncapacitated location problems; the study of dynamic location models; covering and hierarchical location problems; queuing-based probabilistic location models. The contributions encompass theoretical developments, computational algorithms and practical applications. All work took place in an academic environment, with the invaluable collaboration of colleagues (both in Brazil and abroad and research students at COPPE. Each section in the paper is dedicated to a topic that involves a personal contribution. Every one of them is placed within the context of the existing literature.
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...... found in many optimal solutions to CVRP instances. An optimal solution to the PCVRP may therefore be useful in itself as a heuristic solution to the CVRP. Further, an attempt can be made to find an even better CVRP solution by solving a TSP, possibly leading to a non-pyramidal route, for each...... of the routes in the PCVRP solution. This paper develops an exact branch-and-cut-and-price (BCP) algorithm for the PCVRP. At the pricing stage, elementary routes can be computed in pseudo-polynomial time in the PCVRP, unlike in the CVRP. We have therefore implemented pricing algorithms that generate only...
Mamat, Nur Jumaadzan Zaleha; Jaaman, Saiful Hafizah; Ahmad, Rokiah@Rozita
2016-11-01
Two new methods adopted from methods commonly used in the field of transportation and logistics are proposed to solve a specific issue of investment allocation problem. Vehicle routing problem and capacitated vehicle routing methods are applied to optimize the fund allocation of a portfolio of investment assets. This is done by determining the sequence of the assets. As a result, total investment risk is minimized by this sequence.
Location Based Opportunistic Routing Protocol for Mobile Ad Hoc Networks
Directory of Open Access Journals (Sweden)
Jubin Sebastian E
2012-01-01
Full Text Available : Most existing ad hoc routing protocols are susceptible to node mobility, especially for large-scale networks. This paper proposes a Location Based Opportunistic Routing Protocol (LOR to addresses the problem of delivering data packets for highly dynamic mobile ad hoc networks in a reliable and timely manner.This protocol takes advantage of the stateless property of geographic routing and the broadcast nature of wireless medium. When a data packet is sent out, some of the neighbor nodes that have overheard the transmission will serve as forwarding candidates, and take turn to forward the packet if it is not relayed by the specific best forwarder within a certain period of time. By utilizing such in-the-air backup, communication is maintained without being interrupted. The additional latency incurred by local route recovery is greatly reduced and the duplicate relaying caused by packet reroute is also decreased. Simulation results on NS2 verified the effectiveness of the proposed protocol with improvement in throughput by 28%.
NSGIC GIS Inventory (aka Ramona) — This Bus Routes dataset as of unknown. It is described as 'Marta Bus Routes located in Transportation database'. Data by this publisher are often provided in State...
A model for routing problem in quay management problem
Zirour, Mourad; Oughalime, Ahmed; Liong, Choong-Yeun; Ismail, Wan Rosmanira; Omar, Khairuddin
2014-06-01
Quadratic Assignment Problem (QAP), like Vehicle Routing Problem, is one of those optimization problems that interests many researchers in the last decades. The Quay Management Problem is a specific problem which could be presented as a QAP which involves a double assignment of customers and products toward loading positions using lifting trucks. This study focuses on the routing problem while delivering the customers' demands. In this problem, lifting trucks will route around the storage sections to collect the products then deliver to the customers who are assigned to specific loading positions. The objective of minimizing the residence time for each customer is sought. This paper presents the problem and the proposed model.
Rich Vehicle Routing Problems and Applications
DEFF Research Database (Denmark)
Wen, Min
The Vehicle Routing Problem (VRP) is one of the most important and challenging optimization problems in the field of Operations Research. It was introduced by Dantzig and Ramser (1959) and defined as the problem of designing the optimal set of routes for a fleet of vehicles in order to serve...... a given set of customers. The VRP is a computationally hard combinatorial problem and has been intensively studied by numerous researchers in the last fifty years. Due to the significant economic benefit that can be achieved by optimizing the routing problems in practice, more and more attention has been...... given to various extensions of the VRP that arise in real life. These extensions are often called Rich Vehicle Routing Problems (RVRPs). In contrast to the research of classical VRP that focuses on the idealized models with unrealistic assumptions, the research of RVRPs considers those complicated...
On Constrained Facility Location Problems
Institute of Scientific and Technical Information of China (English)
Wei-Lin Li; Peng Zhang; Da-Ming Zhu
2008-01-01
Given m facilities each with an opening cost, n demands, and distance between every demand and facility,the Facility Location problem finds a solution which opens some facilities to connect every demand to an opened facility such that the total cost of the solution is minimized. The k-Facility Location problem further requires that the number of opened facilities is at most k, where k is a parameter given in the instance of the problem. We consider the Facility Location problems satisfying that for every demand the ratio of the longest distance to facilities and the shortest distance to facilities is at most w, where w is a predefined constant. Using the local search approach with scaling technique and error control technique, for any arbitrarily small constant ∈ > 0, we give a polynomial-time approximation algorithm for the ω-constrained Facility Location problem with approximation ratio 1 + √ω + 1 + ∈, which significantly improves the previous best known ratio (ω + 1)/α for some 1 ≤α≤ 2, and a polynomial-time approximation algorithm for the ω-constrained κ-Facility Location problem with approximation ratio ω + 1 + ∈. On the aspect of approximation hardness, we prove that unless NP (C) DTIME(nO(loglogn)), the ω-constrained Facility Location problem cannot be approximated within 1 + √ω-1,which slightly improves the previous best known hardness result 1.243 + 0.316 ln(ω - 1). The experimental results on the standard test instances of Facility Location problem show that our algorithm also has good performance in practice.
The routed inventory pooling problem
Bouma, Harmen Willem
2013-01-01
In supply chains vloeit een groot deel van de kosten voort uit voorraden en transport. Om deze reden wordt veel onderzoek gedaan naar technieken en concepten die de voorraad- en transportkosten helpen te verlagen. Twee populaire onderzoeksgebieden zijn Inventory Routing, waarbij het doel is optimale
Institute of Scientific and Technical Information of China (English)
罗耀波; 孙延明; 廖鹏
2014-01-01
Location routing problems is not only of great significance in integrated logistics network planning research , but also an important management decision that every large logistics company has to make .Based on the warehouse capacity and vehicle capacity constraints , the paper proposes a multi-depot location routing prob-lem model(MDLRP)with backhauls and soft time windows .The model takes full consideration of logistics distri-bution mode with the simultaneous delivery and pick-up and the customer service time requirements .Given the complexity of the MDLRP model , the paper proposes an improved hybrid genetic algorithm with iterated local search and recombination strategy to solve the model integrally .The performance of the heuristic is assessed by computational experiments .As can be seen from the solution , the model with its hybrid genetic algorithm is feasible and superior , and it can be provided to be an alternative tool for location and routing decision .%选址-路径问题（ location routing problems ， LRP）是集成物流网络研究中的难题，也是任何一个大型物流配送企业必须面对的管理决策问题。本文在仓库容量约束和车辆容量约束的基础上，结合送取货一体化的配送模式和客户服务时间要求，建立了带退货和软时间窗的多仓库选址-路径（ MDLRP）数学模型。针对MDLRP问题求解的复杂性，引入局部搜索算法和重组策略，设计了自适应混合遗传算法，对模型进行整体求解。最后进行数值实验，表明本文提出的模型和改进算法具有实用性和优越性，可为选址和车辆运输决策提供重要参考依据。
Routing problems based on hils system platform
Directory of Open Access Journals (Sweden)
Andrzej Adamski
2015-03-01
Full Text Available Background: The logistic systems are very complex socio-technical systems. In this paper the proposal of application of the hierarchical multi-layers system platform HILS approach for the solution of the complex vehicle routing problems is presented. The interactive system functional structure was proposed which by intelligent dedicated inter-layers interactions enables the professional solutions of these practical problems. To illustrate these capabilities the complex example of the real-time VRP-SPD-TW routing problem was presented in which upper layers offers the context-related real-time updating network specifications that stimulates the adequate routing parameters and specifications updating for problem solution in optimization layer. At the bottom dispatching control layer the DISCON (Dispatching CONtrol method from public transport was adopted to logistics applications in which the actual routing is treated as obligatory reference schedule to be stabilized. The intelligence aspects are related among others to HILS based decomposition, context-related trade-offs between routing modifications and corrective dispatching control capabilities e.g. priority or route guidance actions. Methods: Decomposition of the vehicle routing problem for the HILS layers tasks creating the ILS system hierarchical structure. Dedicated solution method for the VRP-SPD-TW routing problem. The recognition of the control preferences structure by AHP-Entropy methods. DISCON and PIACON multi-criteria interacting control methods. Results: Original formulation and solution of the vehicle routing problem by system-wide approach with essential practical advantages: consistency, lack of redundancy, essential reduction of dimension, dedicated formulation, multi-criteria approach, exploration of the integration and intelligence features supported by the intelligent PIACON-DISCON methods control activities Conclusions: The presented proposal creates the professional
Genetic algorithms for the vehicle routing problem
Volna, Eva
2016-06-01
The Vehicle Routing Problem (VRP) is one of the most challenging combinatorial optimization tasks. This problem consists in designing the optimal set of routes for fleet of vehicles in order to serve a given set of customers. Evolutionary algorithms are general iterative algorithms for combinatorial optimization. These algorithms have been found to be very effective and robust in solving numerous problems from a wide range of application domains. This problem is known to be NP-hard; hence many heuristic procedures for its solution have been suggested. For such problems it is often desirable to obtain approximate solutions, so they can be found fast enough and are sufficiently accurate for the purpose. In this paper we have performed an experimental study that indicates the suitable use of genetic algorithms for the vehicle routing problem.
Integrating routing decisions in public transportation problems
Schmidt, Marie E
2014-01-01
This book treats three planning problems arising in public railway transportation planning: line planning, timetabling, and delay management, with the objective to minimize passengers’ travel time. While many optimization approaches simplify these problems by assuming that passengers’ route choice is independent of the solution, this book focuses on models which take into account that passengers will adapt their travel route to the implemented planning solution. That is, a planning solution and passengers’ routes are determined and evaluated simultaneously. This work is technically deep, with insightful findings regarding complexity and algorithmic approaches to public transportation problems with integrated passenger routing. It is intended for researchers in the fields of mathematics, computer science, or operations research, working in the field of public transportation from an optimization standpoint. It is also ideal for students who want to gain intuition and experience in doing complexity proofs ...
Analytical Analysis of Vehicle Routing and Inventory Routing Problems
2007-11-02
The objective of the project is to perform analytical analyses of heuristics for the Vehicle Routing Problem ( VRP ) and apply the results in models...asymptotic optimal solution value of the VRP with capacity and time window constraints and used it to develop a new and efficient algorithm. (2) Obtained a...characterization of the effectiveness of set partitioning formulations for VRPs . (3) Characterized the worst case behavior of the linear programming
Uranium Critical Point Location Problem
Iosilevskiy, Igor
2013-01-01
Significant uncertainty of our present knowledge for uranium critical point parameters is under consideration. Present paper is devoted to comparative analysis of possible resolutions for the problem of uranium critical point location, as well as to discussion of plausible scheme of decisive experiment, which could resolve existing uncertainty. New calculations of gas-liquid coexistence in uranium by modern thermodynamic code are included in the analysis.
Locating Depots for Capacitated Vehicle Routing
DEFF Research Database (Denmark)
Gørtz, Inge Li; Nagarajan, Viswanath
2011-01-01
and parameter ρ ∈ R+, the goal in the k median forest problem is to find S ⊆ V with |S| = k minimizing: E u∈V d(u, S) + ρ · d(MST(V/S) ), where d(u, S) = minw∈S d(u,w) and MST(V/S) is a minimum spanning tree in the graph obtained by contracting S to a single vertex. We give a (3+E)-approximation algorithm for 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...... forest problem when there is a different (unrelated) cost function c for the MST part, i.e. the objective is Eu∈V d(u, S) + c(MST(V/S) ). We show that the locality gap for this problem is unbounded even under multi-swaps, which contrasts with the c = d case. Nevertheless, we obtain a constant...
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.
Institute of Scientific and Technical Information of China (English)
胡少龙; 胡志华; 曹杨
2013-01-01
针对单储位储存方式可能导致仓库存取通道拥挤和作业效率低的情形，提出了一种基于多候选储位的存取路径优化方法。首先分配了货物的存取储位，然后建立了多候选储位的车辆路径问题（ MLVRP）模型，并基于储位优先解码原则设计了遗传算法，最后通过算例证明该方法的有效性和算法的高效性。多候选储位的方法可以为取货任务至少节约18．4％（两个候选储位）和21．8％（三个候选储位）的路程，算法迭代10000次只需要434s。%With respect to the fact that every type of goods has only one storage location in warehouse will lead to crowded aisles and poor operational efficiency , this paper proposes an optimization approach for store and retriev-al routing problem when multi-candidate storages locations are assigned to each type of goods .First,the storage locations are allocated to goods .Then, a model is built for the vehicle routing problem with multi-candidate stor-age locations for each type of goods .A genetic algorithm based on priority-based decoding scheme is developed to solve the model .Finally , a case is given to illustrate the effectiveness of the proposed method and the efficiency of the algorithm.The solution that two-candidate and three candidate storage locations are allocated to each type of goods could at least save 18.4% and 21.8% distance for retrievals respectively .The algorithm iterated for 10000 times costs 434 seconds .
The Team Orienteering Arc Routing Problem
Archetti, Claudia; Speranza, M. Grazia; Corberan, Angel; Sanchís Llopis, José María; Plana, Isaac
2014-01-01
The team orienteering arc routing problem (TOARP) is the extension to the arc routing setting of the team orienteering problem. In the TOARP, in addition to a possible set of regular customers that have to be serviced, another set of potential customers is available. Each customer is associated with an arc of a directed graph. Each potential customer has a profit that is collected when it is serviced, that is, when the associated arc is traversed. A fleet of vehicles with a given maximum trav...
A Survey of Vehicle Routing Problem
Directory of Open Access Journals (Sweden)
Cao Wujun
2017-01-01
Full Text Available In recent years, vehicle routing problem (VRP has become an important content in logistics management research, and has been widely used in transportation system, logistics distribution system and express delivery system. In this paper, we discuss the classification of VRP, and summarize the common constraints of VRP, model algorithm and the main research results in recent years. Finally, we analyzes the future of VRP, and it is considered that the intelligent vehicle routing problem and intelligent heuristic algorithm will be an important field of future research.
VARIABLE RANGE ENERGY EFFICIENT LOCATION AIDED ROUTING FOR MANET
Directory of Open Access Journals (Sweden)
Nivedita N. Joshi
2011-07-01
Full Text Available A Mobile Ad-Hoc Network (MANET is a temporary, infrastructure-less and distributed network having mobile nodes. MANET has limited resources like bandwidth and energy. Due to limited battery power nodes die out early and affect the network lifetime. To make network energy efficient, we have modified position based Location Aided Routing (LAR1 for energy conservation in MANET. The proposed protocol is known as Variable Range Energy aware Location Aided Routing (ELAR1-VAR. The proposed scheme controls the transmission power of a node according to the distance between the nodes. It also includes energy information on route request packet and selects the energy efficient path to route data packets. The comparative analysis of proposed scheme and LAR1 is done by using the QualNet simulator. ELAR1-VAR protocol improves the network lifetime by reducing energy consumption by 20% for dense and mobile network while maintaining the packet delivery ratio above 90%.
Overview of Stochastic Vehicle Routing Problems
Institute of Scientific and Technical Information of China (English)
郭耀煌; 谢秉磊; 郭强
2002-01-01
Stochastic vehicle routing problems (VRPs) play important roles in logistics, though they have not been studied systematically yet. The paper summaries the definition, properties and classification of stochastic VRPs, makes further discussion about two strategies in stochastic VRPs, and at last overviews dynamic and stochastic VRPs.
Two Multivehicle Routing Problems with Unit-Time Windows
Frederickson, Greg N
2011-01-01
Two multivehicle routing problems are considered in the framework that a visit to a location must take place during a specific time window in order to be counted and all time windows are the same length. In the first problem, the goal is to visit as many locations as possible using a fixed number of vehicles. In the second, the goal is to visit all locations using the smallest number of vehicles possible. For the first problem, we present an approximation algorithm whose output path collects a reward within a constant factor of optimal for any fixed number of vehicles. For the second problem, our algorithm finds a 6-approximation to the problem on a tree metric, whenever a single vehicle could visit all locations during their time windows.
Heat exchanger leakage problem location
Directory of Open Access Journals (Sweden)
Jícha Miroslav
2012-04-01
Full Text Available Recent compact heat exchangers are very often assembled from numerous parts joined together to separate heat transfer fluids and to form the required heat exchanger arrangement. Therefore, the leak tightness is very important property of the compact heat exchangers. Although, the compact heat exchangers have been produced for many years, there are still technological problems associated with manufacturing of the ideal connection between the individual parts, mainly encountered with special purpose heat exchangers, e.g. gas turbine recuperators. This paper describes a procedure used to identify the leakage location inside the prime surface gas turbine recuperator. For this purpose, an analytical model of the leaky gas turbine recuperator was created to assess its performance. The results obtained are compared with the experimental data which were acquired during the recuperator thermal performance analysis. The differences between these two data sets are used to indicate possible leakage areas.
Heat exchanger leakage problem location
Hejčík, Jiří; Jícha, Miroslav
2012-04-01
Recent compact heat exchangers are very often assembled from numerous parts joined together to separate heat transfer fluids and to form the required heat exchanger arrangement. Therefore, the leak tightness is very important property of the compact heat exchangers. Although, the compact heat exchangers have been produced for many years, there are still technological problems associated with manufacturing of the ideal connection between the individual parts, mainly encountered with special purpose heat exchangers, e.g. gas turbine recuperators. This paper describes a procedure used to identify the leakage location inside the prime surface gas turbine recuperator. For this purpose, an analytical model of the leaky gas turbine recuperator was created to assess its performance. The results obtained are compared with the experimental data which were acquired during the recuperator thermal performance analysis. The differences between these two data sets are used to indicate possible leakage areas.
Location Estimation with Reactive Routing in Resource Constrained Sensor Networks
Sarangi, Sanat
2010-01-01
Routing algorithms for wireless sensor networks can be broadly divided into two classes - proactive and reactive. Proactive routing is suitable for a network with a fixed topology. On the other hand, reactive routing is more suitable for a set of mobile nodes where routes are created on demand and there is not much time to evaluate the worthiness of a route, the prime concern being reachability due to constantly changing node positions. Sensor networks route events of interest from source(s) to destination(s) where appropriate actions could be taken. However, with mobile sensor nodes, it is not only important to know the events but the location of the nodes generating the events. Most sensor nodes are not equipped with expensive GPS or accurate RSSI computation hardware to aid localization. Keeping these in view, we propose a modified reactive routing algorithm, with added support for localization, to localize mobile sensor nodes on the basis of information received from fixed sensor nodes during mutual excha...
Location of Urban Logistic Terminals as Hub Location Problem
Directory of Open Access Journals (Sweden)
Jasmina Pašagić Škrinjar
2012-09-01
Full Text Available In this paper the problems of locating urban logistic terminals are studied as hub location problems that due to a large number of potential nodes in big cities belong to hard non-polynomial problems, the so-called NP-problems. The hub location problems have found wide application in physical planning of transport and telecommunication systems, especially systems of fast delivery, networks of logistic and distribution centres and cargo traffic terminals of the big cities, etc. The paper defines single and multiple allocations and studies the numerical examples. The capacitated single allocation hub location problems have been studied, with the provision of a mathematical model of selecting the location for the hubs on the network. The paper also presents the differences in the possibilities of implementing the exact and heuristic methods to solve the actual location problems of big dimensions i.e. hub problems of the big cities.
Location-Based Self-Adaptive Routing Algorithm for Wireless Sensor Networks in Home Automation
Directory of Open Access Journals (Sweden)
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.
Fund allocation using capacitated vehicle routing problem
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.
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.
Energy Efficient Location Aided Routing Protocol for Wireless MANETs
Mikki, Mohammad A
2009-01-01
A Mobile Ad-Hoc Network (MANET) is a collection of wireless mobile nodes forming a temporary network without using any centralized access point, infrastructure, or centralized administration. In this paper we introduce an Energy Efficient Location Aided Routing (EELAR) Protocol for MANETs that is based on the Location Aided Routing (LAR). EELAR makes significant reduction in the energy consumption of the mobile nodes batteries by limiting the area of discovering a new route to a smaller zone. Thus, control packets overhead is significantly reduced. In EELAR a reference wireless base station is used and the network's circular area centered at the base station is divided into six equal sub-areas. At route discovery instead of flooding control packets to the whole network area, they are flooded to only the sub-area of the destination mobile node. The base station stores locations of the mobile nodes in a position table. To show the efficiency of the proposed protocol we present simulations using NS-2. Simulation...
Integrated Models and Approach for Location Inventory and Routing Problem%选址-库存-路径问题模型及其集成优化算法
Institute of Scientific and Technical Information of China (English)
杜丽敬; 李延晖
2014-01-01
设施选址、库存控制和车辆路径安排是物流系统优化中的三个关键问题，三者之间存在相互依赖的关系，应该根据这种关系来相应地进行综合优化与管理物流活动。以典型的单一生产基地、单一产品、采用不断审查的（ Q， r）库存策略的供应链二级分销网络为研究对象，建立了一个随机型选址-库存-路径问题优化模型；在将非线性混合整数规划转化为线性整数集合覆盖模型的基础上，采用列生成算法来获得一个近似最优解，再用分支定价法对初始解进行改进，以实现对整个问题“完全集成”的优化。最后，用随机生成的方式，产生了10至160个客户的计算实例，分析了运输费用和库存费用对总成本的影响，算法运算时间表明本文给出的算法能较快地求解这一复杂问题。%Facility location , inventory control and vehicle routes scheduling are critical and highly related prob-lems in logistics system .The decision makers need to optimize the three problems integrated and comprehensive-ly.We formulate a stochastic Location-Inventory-Routing Problem(LIRP) model using continuous review (Q, r) inventory policy in two level supply chain distribution systems , consisting of one supplier , a set of retailers and a single type of product .Restructuring the non-linear mixed integer programming LIRP model into a set covering model, an approximate optimum solution is obtained using column generation .To realize the “integrated optimi-zation”, Brand-and-Price algorithm is applied to improve the initial solution .At last , based on the several in-stances generated randomly with sizes ranging from 10 to 160 retailers, the proposed approach is tested and eval-uated.The computational results show the proposed approach can resolve this complex problem efficiently .
Use of Interactive Computer Graphics to Solve Routing Problems.
Gillett, B. E.; Lawrence, J. L.
1981-01-01
Discusses vehicle routing problems and solutions. Describes testing of an interactive computer graphics package combining several types of solutions that allows users with little or no experience to work out routing problems. (Author/RW)
Vehicle routing problem with time-varying speed
Institute of Scientific and Technical Information of China (English)
LIU Yun-zhong
2010-01-01
Vehicle routing problem with time-varying speed(VRPTS)is a generalization of vehicle routing problem in which the travel speed between two locations depends on the passing areas and the time of a day.This paper proposes a simple model for estimating time-varying travel speeds in VRPTS that relieves much bur den to the data-related problems.The study further presents three heuristics(saving technique,proximity priority searching technique,and insertion technique)for VRPTS,developed by extending and modifying the existing heuristics for conventional VRP.The results of computational experiments demonstrate that the proposed estimation model performs well and the saving technique is the best among the three heuristics.
The vehicle routing problem with backhauls
Energy Technology Data Exchange (ETDEWEB)
Goetschalckx, M.; Jacobs-Blecha, C.
1989-09-05
The Vehicle Routing Problem with Backhauls is a pickup/delivery problem where on each route all deliveries must be made before any pickups. A two-phased solution methodology is proposed. In the first phase, a high quality initial feasible solution is generated based on spacefilling curves. In the second phase, this solution is improved based on optimization of the subproblems identified in a mathematical model of the problem. An extensive computational analysis of several initial solution algorithms is presented, which identifies the tradeoffs between solution quality and computational requirements. The class of greedy algorithms is capacity oriented, while K-median algorithms focus on distance. It is concluded that the greedy and K-median algorithms generate equivalent tour lengths, but that the greedy procedure reduces the required number of trucks and increases the truck utilization. The effect of exchange improvement procedures as well as optimal procedures on solution quality and run time is demonstrated. Comparisons with the Clark-Wright method adapted to backhauls are also given. 4 figs., 26 refs.
Approximation algorithms for some vehicle routing problems
Bazgan, Cristina; Hassin, Refael; Monnot, Jérôme
2005-01-01
We study vehicle routing problems with constraints on the distance traveled by each vehicle or on the number of vehicles. The objective is either to minimize the total distance traveled by vehicles or to minimize the number of vehicles used. We design constant differential approximation algorithms for kVRP. Note that, using the differential bound for METRIC 3VRP, we obtain the randomized standard ratio . This is an improvement of the best-known bound of 2 given by Haimovich et al. (Vehicle Ro...
Bounds in the location-allocation problem
DEFF Research Database (Denmark)
Juel, Henrik
1981-01-01
Develops a family of stronger lower bounds on the objective function value of the location-allocation problem. Solution methods proposed to solve problems in location-allocation; Efforts to develop a more efficient bound solution procedure; Determination of the locations of the sources.......Develops a family of stronger lower bounds on the objective function value of the location-allocation problem. Solution methods proposed to solve problems in location-allocation; Efforts to develop a more efficient bound solution procedure; Determination of the locations of the sources....
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.
Implementation of a Locator-Based Route Switching Scheme for Improved Routing in Proxy Mobile IPv6
Directory of Open Access Journals (Sweden)
M. Okwori
2014-11-01
Full Text Available Proxy Mobile IPv6 (PMIPv6 is a promising IP mobility protocols that is being deployed in emerging wireless technologies. This however has a non-optimal packet route as a result of the triangular routing problem. This creates a bottle neck at the Local Mobility Anchor (LMA thereby increasing packet delays. This paper presents the implementation of a locator-based route switching scheme on OPNET Modeler. The Mobility Access Gateway (MAG and the LMA were enhanced by making them intelligent. This enables them to be able to check the position of the Corresponding Node (CN with respect to the Mobile Node (MN and also determine the available bandwidth on each link. From the checks made, a three-stage decision process is used to switch routing to the most optimal route that guarantees the best QoS. Node Models were developed for the MAG and LMA, network models were deployed and simulation tests were carried out. The results show that the developed scheme switched packets to a more optimal route according to the designed algorithm. The impact of this switching on differences between transmitted throughput at MN and the received throughput at CN was also evaluated. The receiver activity result shows a reduction in the bottleneck at the LMA-MAG link. The end-to-end delay results show over 50 milliseconds drop in packet delay as a result of the switching to a more optimal route. This shows that the packet delays result from the congestion at the LMA-MAG interface due to suboptimal routing.
Bounds in the location-allocation problem
DEFF Research Database (Denmark)
Juel, Henrik
1981-01-01
Develops a family of stronger lower bounds on the objective function value of the location-allocation problem. Solution methods proposed to solve problems in location-allocation; Efforts to develop a more efficient bound solution procedure; Determination of the locations of the sources....
Improvement In MAODV Protocol Using Location Based Routing Protocol
Directory of Open Access Journals (Sweden)
Kaur Sharnjeet
2016-01-01
Full Text Available Energy saving is difficult in wireless sensor network (WSN due to limited resources. Each node in WSN is constrained by their limited battery power for their energy. The energy is reduced as the time goes off due to the packet transmission and reception. Energy management techniques are necessary to minimize the total power consumption of all the nodes in the network in order to maximize its life span. Our proposed protocol Location based routing (LBR aimed to find a path which utilizes the minimum energy to transmit the packets between the source and the destination. The required energy for the transmission and reception of data is evaluated in MATLAB. LBR is implemented on Multicast Ad hoc On Demand Distance Vector Routing Protocol (MAODV to manage the energy consumption in the transmission and reception of data. Simulation results of LBR show the energy consumption has been reduced.
Time Dependent Heterogeneous Vehicle Routing Problem for Catering Service Delivery Problem
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.
The vehicle routing problem with time windows and temporal dependencies
DEFF Research Database (Denmark)
Dohn, Anders Høeg; Rasmussen, Matias Sevel; Larsen, Jesper
2011-01-01
In this article, we formulate the vehicle routing problem with time windows and temporal dependencies. The problem is an extension of the well studied vehicle routing problem with time windows. In addition to the usual constraints, a scheduled time of one visit may restrain the scheduling options...
Disruption management of the vehicle routing problem with vehicle breakdown
DEFF Research Database (Denmark)
Mu, Q; Fu, Z; Lysgaard, Jens
2011-01-01
This paper introduces a new class of problem, the disrupted vehicle routing problem (VRP), which deals with the disruptions that occur at the execution stage of a VRP plan. The paper then focuses on one type of such problem, in which a vehicle breaks down during the delivery and a new routing...
An approximate algorithm for solving the watchman route problem
Li, Fajie; Klette, Reinhard; Sommer, G; Klette, R
2008-01-01
The watchman route problem (WRP) was first introduced in 1988 and is defined as follows: How to calculate a shortest route completely contained inside a simple polygon such that any point inside this polygon is visible from at least one point on the route? So far the best known result for the WRP is
Exact methods for time constrained routing and related scheduling problems
DEFF Research Database (Denmark)
Kohl, Niklas
1995-01-01
This dissertation presents a number of optimization methods for the Vehicle Routing Problem with Time Windows (VRPTW). The VRPTW is a generalization of the well known capacity constrained Vehicle Routing Problem (VRP), where a fleet of vehicles based at a central depot must service a set of custo......This dissertation presents a number of optimization methods for the Vehicle Routing Problem with Time Windows (VRPTW). The VRPTW is a generalization of the well known capacity constrained Vehicle Routing Problem (VRP), where a fleet of vehicles based at a central depot must service a set...
Solving the time dependent vehicle routing problem by metaheuristic algorithms
Johar, Farhana; Potts, Chris; Bennell, Julia
2015-02-01
The problem we consider in this study is Time Dependent Vehicle Routing Problem (TDVRP) which has been categorized as non-classical VRP. It is motivated by the fact that multinational companies are currently not only manufacturing the demanded products but also distributing them to the customer location. This implies an efficient synchronization of production and distribution activities. Hence, this study will look into the routing of vehicles which departs from the depot at varies time due to the variation in manufacturing process. We consider a single production line where demanded products are being process one at a time once orders have been received from the customers. It is assumed that order released from the production line will be loaded into scheduled vehicle which ready to be delivered. However, the delivery could only be done once all orders scheduled in the vehicle have been released from the production line. Therefore, there could be lateness on the delivery process from awaiting all customers' order of the route to be released. Our objective is to determine a schedule for vehicle routing that minimizes the solution cost including the travelling and tardiness cost. A mathematical formulation is developed to represent the problem and will be solved by two metaheuristics; Variable Neighborhood Search (VNS) and Tabu Search (TS). These algorithms will be coded in C ++ programming and run using 56's Solomon instances with some modification. The outcome of this experiment can be interpreted as the quality criteria of the different approximation methods. The comparison done shown that VNS gave the better results while consuming reasonable computational efforts.
Solving Segment Routing Problems with Hybrid Constraint Programming Techniques
Hartert, Renaud; Schaus, Pierre; Vissicchio, Stefano; Bonaventure, Olivier; International Conference on Principles and Practice of Constraint Programming (CP2014)
2015-01-01
Segment routing is an emerging network technology that exploits the existence of several paths between a source and a destination to spread the traffic in a simple and elegant way. The major commercial network vendors already support segment routing, and several Internet actors are ready to use segment routing in their network. Unfortunately, by changing the way paths are computed, segment routing poses new op- timization problems which cannot be addressed with previous research contributions...
A Tabu Search Heuristic for the Vehicle Routing Problem
1994-01-01
The purpose of this paper is to describe TABUROUTE, a new tabu search heuristic for the vehicle routing problem with capacity and route length restrictions. The algorithm considers a sequence of adjacent solutions obtained by repeatedly removing a vertex from its current route and reinserting it into another route. This is done by means of a generalized insertion procedure previously developed by the authors. During the course of the algorithm, infeasible solutions are allowed. Numerical test...
Inferring Groups of Objects, Preferred Routes, and Facility Locations from Trajectories
DEFF Research Database (Denmark)
Ceikute, Vaida
In today’s society, GPS-enabled devices are used widely. A broad range of location-based services (LBS) allow users to receive and share information related to their positions. Thus, it is possible to accumulate GPS data, and it is expected that the amount of available GPS data will increase very...... on empirical studies with real route usage data and an existing online routing service. Finally, we use GPS trajectories as customer flows in a modern formulation of the facility location problem. We propose a practical framework that, given a road network, a set of trajectories, and a set of existing...... facilities, computes the optimal segment(s) for the location of a new facility. Customer flows are scored, and the score of a flow is distributed among the road segments that the flow covers according to a score distribution model. We propose two algorithms that adopt different approaches to compute...
OPTIMIZATION OF CAPACITATED VEHICLE ROUTING PROBLEM USING PSO
Directory of Open Access Journals (Sweden)
S.R.VENKATESAN
2011-10-01
Full Text Available This paper presents solution techniques for Capacitated Vehicle Routing Problem (CVRP using metaheuristics. Capacitated Vehicle Routing Problem is divided into set of customers called cluster, and find optimum travel distance of vehicle route. The CVRP is a combinatorial optimization problem; particle swarm optimization(PSO technique is adapted in this paper to solve this problem. The main problem is divided into subprograms/clusters and each subprogram is treated as travelling salesman problem and solved by usingparticle swarm optimization techniques (PSO. This paper presents a sweep, Clark and wright algorithm to form the clusters. This model is then solved by using a particle swarm optimization (PSO method to find optimum travel distance of vehicle route. Our analysis suggests that the proposed model enables users to establish route to serve all given customers with minimum distance of vehicles and maximum capacity.
The Vehicle Routing Problem with Time Windows and Temporal Dependencies
DEFF Research Database (Denmark)
Rasmussen, Matias Sevel; Dohn, Anders Høeg; Larsen, Jesper
The vehicle routing problem with time windows and temporal dependencies (VRPTWTD) is an extension of the vehicle routing problem with time windows (VRPTW). Given is a fixed set of customers with individual demands and with time windows specifying when each customer accepts service. The objective...... is to find routes for a number of vehicles, all starting and ending at a central depot in such a way that the total distance is minimized. The extension that we present here is concerned with temporal dependencies between customers. A temporal dependency which is often encountered in practical instances...... assignment and routing problem with synchronization constraints. The problem has been solved by column generation. The synchronized vehicle dispatching problem (SVDP), which is a dynamic vehicle routing problem with synchronization between vehicles. Constraint programming and local search are applied...
About some types of constraints in problems of routing
Petunin, A. A.; Polishuk, E. G.; Chentsov, A. G.; Chentsov, P. A.; Ukolov, S. S.
2016-12-01
Many routing problems arising in different applications can be interpreted as a discrete optimization problem with additional constraints. The latter include generalized travelling salesman problem (GTSP), to which task of tool routing for CNC thermal cutting machines is sometimes reduced. Technological requirements bound to thermal fields distribution during cutting process are of great importance when developing algorithms for this task solution. These requirements give rise to some specific constraints for GTSP. This paper provides a mathematical formulation for the problem of thermal fields calculating during metal sheet thermal cutting. Corresponding algorithm with its programmatic implementation is considered. The mathematical model allowing taking such constraints into account considering other routing problems is discussed either.
Genetic algorithm to solve constrained routing problem with applications for cruise missile routing
Latourell, James L.; Wallet, Bradley C.; Copeland, Bruce
1998-03-01
In this paper the use of a Genetic Algorithm to solve a constrained vehicle routing problem is explored. The problem is two-dimensional with obstacles represented as ellipses of uncertainty surrounding each obstacle point. A route is defined as a series of points through which the vehicle sequentially travels from the starting point to the ending point. The physical constraints of total route length and maximum turn angle are included and appear in the fitness function. In order to be valid, a route must go from start to finish without violating any constraint. The effects that different mutation rates and population sizes have on the algorithm's computation speed and ability to find a high quality route are also explored. Finally, possible applications of this algorithm to the problem of route planning for cruise missiles are discussed.
Mobility-Assisted on-Demand Routing Algorithm for MANETs in the Presence of Location Errors
Kwon, Sungoh
2014-01-01
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. PMID:24959628
Mobility-Assisted on-Demand Routing Algorithm for MANETs in the Presence of Location Errors
Directory of Open Access Journals (Sweden)
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.
Heuristic methods for a refuse collection vehicle routing problem
Energy Technology Data Exchange (ETDEWEB)
Mourao, M.C.; Almeida, M.T.
1994-12-31
The problem of generating the set of routes that minimizes the total time required to collect the household refuse in a particular quarter of Lisbon can be formulated as a Capacitated Arc Routing Problem with some side constraints. Our aim is to obtain approximate solutions, as the problem is known to be NP-hard. We present heuristic methods to generate feasible solutions and report their performance over a set of test problems.
INVERSE CENTER LOCATION PROBLEM ON A TREE
Institute of Scientific and Technical Information of China (English)
无
2008-01-01
This paper discusses the inverse center location problem restricted on a tree with different costs and bound constraints.The authors first show that the problem can be formulated as a series of combinatorial linear programs,then an O(|V|2 log |V|)time algorithm to solve the problem is presented.For the equal cost case,the authors further give an O(|V|)time algorithm.
Open Vehicle Routing Problem by Ant Colony Optimization
Directory of Open Access Journals (Sweden)
Er. Gurpreet Singh
2014-01-01
Full Text Available Vehicle routing problem (VRP is real-world combinatorial optimization problem which determine the optimal route of a vehicle. Generally, toprovide the efficientvehicle serving to the customer through different services by visiting the number of cities or stops. The VRP follows the Travelling Salesman Problem (TSP, in which each of vehicle visiting a set of cities such that every city is visited by exactly one vehicle only once. This work proposes the Ant Colony Optimization (ACO-TSP algorithm to eliminate the tour loop for Open Vehicle routing Problem (OVRP. A key aspect of this algorithm is to plan the routes of buses that must pick up and deliver the school students from various bus stops on time, especially in the case of far distance covered by the vehicle in a rural area and find out the efficient and safe vehicle route.
Inferring Groups of Objects, Preferred Routes, and Facility Locations from Trajectories
DEFF Research Database (Denmark)
Ceikute, Vaida
on empirical studies with real route usage data and an existing online routing service. Finally, we use GPS trajectories as customer flows in a modern formulation of the facility location problem. We propose a practical framework that, given a road network, a set of trajectories, and a set of existing......In today’s society, GPS-enabled devices are used widely. A broad range of location-based services (LBS) allow users to receive and share information related to their positions. Thus, it is possible to accumulate GPS data, and it is expected that the amount of available GPS data will increase very...... substantially in the years to come. The availability of such GPS data holds huge potential to improve existing LBS or lead to the creation of new ones. This thesis investigates the use of GPS data in three different areas. Specifically, from GPS data we obtain trajectories of moving objects, from which we can...
An integrated location inventory routing model in supply chain network designing under uncertainty
Directory of Open Access Journals (Sweden)
Hojat Angazi
2016-09-01
Full Text Available In this study an integrated model is proposed for the location inventory routing problem under uncertainty. This problem involves determining the location of distribution centers (DCs in a three echelon supply chain. The DCs receive orders from the customer and according to a continuous review inventory replenishment policy place orders to the supplier. The products are directly shipped from the supplier to the DCs. The vehicles start from the DCs to fulfill the demands of the customers. Determining the routing of the vehicles is one of the decisions involved in this problem. The demands of customers are stochastically distributed and the capacity of DCs are limited. If one of the DCs undergo a disruption and is unable to fulfill the demands of the customers, shortage may occur. Moreover in the proposed model the shortage is considered as partial backlogging. This means that if shortage occurs, some of the orders result in lost sales and other orders are fulfilled in the next period. In order to optimally solve the proposed model a nonlinear integer programming (INLP model is developed. However, since the problem is NP-hard, the mathematical formulation cannot be efficiently solved for large sized instances of the problem. Therefore an outer approximation method is developed to solve the problem more efficiently. The computational results show the efficiency of the proposed method.
ChordPlus:a scalable,decentralized object location and routing algorithm
Institute of Scientific and Technical Information of China (English)
柏海寰; 蒋俊杰; 汪为农
2004-01-01
Object location is a fundamental problem in distributed system such as grid computing and peer-to-peer environment. Chord is one of the typical scalable object location algorithms for peer-to-peer network. The simplicity, provable correctness and provable performance of Chord make it an attractive option for distributed lookup. However its lookup performance is not satisfying. Based on the decentralized object location mathematical model. This paper proposes ChordPlus, an improved Chord algorithm, by enlarging dimension size of space M (M = 2 in Chord) and utilizing data redundancy technology. ChordPlus is a scalable, fault-tolerant, completely decentralized and self-organizing object location and routing algorithm for overlay network. Results from theoretical analysis and simulation experiments show that increasing the dimension size of space or neighborhood set length can enhance the routing performance of ChordPlus. In a simulation network with 5 000 nodes, the average routing path length of ChordPlus is only as many as half that of Chord algorithm.
Cobweb heuristic for multi-objective vehicle routing problem
Joseph Okitonyumbe Y. F; Berthold Ulungu E.-L; Joel Kapiamba Nt.
2015-01-01
Solving a classical vehicle routing problem (VRP) by exact methods presents many difficulties for large dimension problem. Consequently, in multi-objective framework, heuristic or metaheuristic methods are required. Due to particular VRP structure, it seems that a dedicated heuristicis more suitable than a metaheuristic. The aim of this article is to collapse different heuristics solving classical VRP and adapt them for to solve the multi-objective vehicle routing problem (MOVRP). The so-call...
Cobweb Heuristic for solving Multi-Objective Vehicle Routing Problem
Okitonyumbe Y.F., Joseph; Ulungu, Berthold E.-L.; Kapiamba Nt., Joel
2015-01-01
Abstract Solving a classical vehicle routing problem (VRP) by exact methods presents many difficulties for large dimension problem. Consequently, in multi-objective framework, heuristic or metaheuristic methods are required. Due to particular VRP structure, it seems that a dedicated heuristic is more suitable than a metaheuristic. The aim of this article is to collapse different heuristics solving classical VRP and adapt them for to solve the multi-objective vehicle routing problem (MOVRP)...
Optimizing investment fund allocation using vehicle routing problem framework
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.
Colony location algorithm for assignment problems
Institute of Scientific and Technical Information of China (English)
Dingwei WANG
2004-01-01
A novel algorithm called Colony Location Algorithm (CLA) is proposed. It mimics the phenomena in biotic conmunity that colonies of species could be located in the places most suitable to their growth. The factors working on the species location such as the nutrient of soil, resource competition between species, growth and decline process, and effect on environment were considered in CLA via the nutrient function, growth and decline rates, environment evaluation and fertilization strategy.CLA was applied to solve the classical assignment problems. The computation results show that CLA can achieve the optimal solution with higher possibility and shorter running time.
The vehicle routing problem latest advances and new challenges
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...
Hub location problems in transportation networks
DEFF Research Database (Denmark)
Gelareh, Shahin; Nickel, Stefan
2011-01-01
In this paper we propose a 4-index formulation for the uncapacitated multiple allocation hub location problem tailored for urban transport and liner shipping network design. This formulation is very tight and most of the tractable instances for MIP solvers are optimally solvable at the root node....... also introduce fixed cost values for Australian Post (AP) dataset....
A Sweep Coverage Scheme Based on Vehicle Routing Problem
Directory of Open Access Journals (Sweden)
Li Shu
2013-04-01
Full Text Available As an emerging coverage problem in wireless sensor networks, sweep coverage which introducing mobile sensors to cover points of interest within certain time interval can satisfy monitoring request in some particular application scenarios with less number of nodes than the conventional static coverage approach. In this work, aiming to support dynamical POI coverage and data delivery simultaneously, a novel sweep coverage scheme, named VRPSC(Vehicle Routing Problem based Sweep Coverage, is proposed by modeling the minimum number of required sensors problem in sweep coverage as a Vehicle Routing Problem (VRP. In VRPSC, an insertion algorithm is first introduced to create the initial scanning routes for POIs, and then the Simulated Annealing is employed to optimize these routes. The simulation results show that the VRPSC scheme achieves better performance than existing schemes.
Study on model and algorithm of inventory routing problem
Wan, Fengjiao
Vehicle routing problem(VRP) is one of important research in the logistics system. Nowadays, there are many researches on the VRP, but their don't consider the cost of inventory. Thus, the conclusion doesn't meet reality. This paper studies on the inventory routing problem (IRP)and uses one target function to describe these two conflicting problems, which are very important in the logistics optimization. The paper establishes the model of single client and many clients' inventory routing problem. An optimizing iterative algorithm is presented to solve the model. According to the model we can confirm the best quantity, efficiency and route of delivery. Finally, an example is given to illustrate the efficiency of model and algorithm.
Solving the Vehicle Routing Problem using Genetic Algorithm
Directory of Open Access Journals (Sweden)
Abdul Kadar Muhammad Masum
2011-08-01
Full Text Available The main goal of this research is to find a solution of Vehicle Routing Problem using genetic algorithms. The Vehicle Routing Problem (VRP is a complex combinatorial optimization problem that belongs to the NP-complete class. Due to the nature of the problem it is not possible to use exact methods for large instances of the VRP. Genetic algorithms provide a search technique used in computing to find true or approximate solution to optimization and search problems. However we used some heuristic in addition during crossover or mutation for tuning the system to obtain better result.
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...
A matheuristic approach for the Pollution-Routing Problem
Kramer, Raphael; Subramanian, Anand; Vidal, Thibaut; Cabral, Lucídio dos Anjos Formiga
2014-01-01
This paper deals with the Pollution-Routing Problem (PRP), a Vehicle Routing Problem (VRP) with environmental considerations, recently introduced in the literature by [Bektas and Laporte (2011), Transport. Res. B-Meth. 45 (8), 1232-1250]. The objective is to minimize operational and environmental costs while respecting capacity constraints and service time windows. Costs are based on driver wages and fuel consumption, which depends on many factors, such as travel distance and vehicle load. Th...
A survey on multi trip vehicle routing problem
2008-01-01
The vehicle routing problem (VRP) and its variants are well known and greatly explored in the transportation literature. The vehicle routing problem can be considered as the scheduling of vehicles (trucks) to a set of customers under various side constraints. In most studies, a fundamental assumption is that a vehicle dispatched for service finishes its duty in that scheduling period after it returns back to the depot. Clearly, in many cases this assumption may not hold. Thus, in the last dec...
Classification of routing and scheduling problems in liner shipping
DEFF Research Database (Denmark)
Hjortshøj Kjeldsen, Karina
A classification scheme for routing and scheduling problems in liner shipping is developed and subsequently used to classify existing literature on the subject. Based on the classification the articles are grouped, and the main characteristics of each group and article are described. The grouping...... may serve as a catalyst towards developing a model or a group of models that covers the main problems within routing and scheduling in liner shipping....
Heuristic for vehicle routing problem with release and due dates
Johar, Farhana; Potts, Chris; Bennell, Julia
2014-06-01
This research is classifies as non-classical Vehicle Routing Problem (VRP) where the maximum release date of customer's demand of the route determine the vehicle departure time. Thus, there could be lateness on the delivery process from awaiting all customers' demand of the route to be released. A mathematical formulation is developed to represent the problem studied. Insertion method based on the cheapest cost is used to generate an initial solution. Then, Local Search technique is applied to improve the solution in term of minimization of total traveling and tardiness cost.
An Approximation Algorithm for the Capacitated Arc Routing Problem
DEFF Research Database (Denmark)
Wøhlk, Sanne
2008-01-01
In this paper we consider approximation of the Capacitated Arc Routing Problem, which is the problem of servicing a set of edges in a graph using a fleet of capacity constrained vehicles. We present a 7/2 - 3/W-approximation algorithm for the problem and prove that this algorithm outperforms...
Multicast Routing Problem Using Tree-Based Cuckoo Optimization Algorithm
Directory of Open Access Journals (Sweden)
Mahmood Sardarpour
2016-06-01
Full Text Available The problem of QoS multicast routing is to find a multicast tree with the least expense/cost which would meet the limitations such as band width, delay and loss rate. This is a NP-Complete problem. To solve the problem of multicast routing, the entire routes from the source node to every destination node are often recognized. Then the routes are integrated and changed into a single multicast tree. But they are slow and complicated methods. The present paper introduces a new tree-based optimization method to overcome such weaknesses. The recommended method directly optimizes the multicast tree. Therefore a tree-based typology including several spanning trees is created which combines the trees two by two. For this purpose, the Cuckoo Algorithm is used which is proved to be well converged and makes quick calculations. The simulation conducted on different types of network typologies proved that it is a practical and influential algorithm.
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 repres...... 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....
An Effective Hybrid Optimization Algorithm for Capacitated Vehicle Routing Problem
Institute of Scientific and Technical Information of China (English)
无
2006-01-01
Capacitated vehicle routing problem (CVRP) is an important combinatorial optimization problem. However, it is quite difficult to achieve an optimal solution with the traditional optimization methods owing to the high computational complexity. A hybrid algorithm was developed to solve the problem, in which an artificial immune clonal algorithm (AICA) makes use of the global search ability to search the optimal results and simulated annealing (SA) algorithm employs certain probability to avoid becoming trapped in a local optimum. The results obtained from the computational study show that the proposed algorithm is a feasible and effective method for capacitated vehicle routing problem.
Capacitated arc routing problem and its extensions in waste collection
Fadzli, Mohammad; Najwa, Nurul; Luis, Martino
2015-05-01
Capacitated arc routing problem (CARP) is the youngest generation of graph theory that focuses on solving the edge/arc routing for optimality. Since many years, operational research devoted to CARP counterpart, known as vehicle routing problem (VRP), which does not fit to several real cases such like waste collection problem and road maintenance. In this paper, we highlighted several extensions of capacitated arc routing problem (CARP) that represents the real-life problem of vehicle operation in waste collection. By purpose, CARP is designed to find a set of routes for vehicles that satisfies all pre-setting constraints in such that all vehicles must start and end at a depot, service a set of demands on edges (or arcs) exactly once without exceeding the capacity, thus the total fleet cost is minimized. We also addressed the differentiation between CARP and VRP in waste collection. Several issues have been discussed including stochastic demands and time window problems in order to show the complexity and importance of CARP in the related industry. A mathematical model of CARP and its new version is presented by considering several factors such like delivery cost, lateness penalty and delivery time.
Capacitated arc routing problem and its extensions in waste collection
Energy Technology Data Exchange (ETDEWEB)
Fadzli, Mohammad; Najwa, Nurul [Institut Matematik Kejuruteraan, Universiti Malaysia Perlis, Kampus Pauh Putra, 02600 Arau, Perlis (Malaysia); Luis, Martino [Othman Yeop Abdullah Graduate School of Business, Universiti Utara Malaysia, 06010 Sintok, Kedah (Malaysia)
2015-05-15
Capacitated arc routing problem (CARP) is the youngest generation of graph theory that focuses on solving the edge/arc routing for optimality. Since many years, operational research devoted to CARP counterpart, known as vehicle routing problem (VRP), which does not fit to several real cases such like waste collection problem and road maintenance. In this paper, we highlighted several extensions of capacitated arc routing problem (CARP) that represents the real-life problem of vehicle operation in waste collection. By purpose, CARP is designed to find a set of routes for vehicles that satisfies all pre-setting constraints in such that all vehicles must start and end at a depot, service a set of demands on edges (or arcs) exactly once without exceeding the capacity, thus the total fleet cost is minimized. We also addressed the differentiation between CARP and VRP in waste collection. Several issues have been discussed including stochastic demands and time window problems in order to show the complexity and importance of CARP in the related industry. A mathematical model of CARP and its new version is presented by considering several factors such like delivery cost, lateness penalty and delivery time.
An Approximation Algorithm for the Capacitated Arc Routing Problem
DEFF Research Database (Denmark)
Wøhlk, Sanne
2008-01-01
In this paper we consider approximation of the Capacitated Arc Routing Problem, which is the problem of servicing a set of edges in a graph using a fleet of capacity constrained vehicles. We present a 7/2 - 3/W-approximation algorithm for the problem and prove that this algorithm outperforms...... the only existing approximation algorithm for the problem. Furthermore, we give computational results showing that the new algorithm performs very well in practice....
DBLAR: A DISTANCE-BASED LOCATION-AIDED ROUTING FOR MANET
Institute of Scientific and Technical Information of China (English)
Wang Kun; Wu Meng
2009-01-01
In location-aided routing of Mobile Ad hoc NETworks (MANET), nodes mobility and the inaccuracy of location information may result in constant flooding, which will reduce the network performance. In this paper, a Distance-Based Location-Aided Routing (DBLAR) for MANET has been proposed. By tracing the location information of destination nodes and referring to distance change between nodes to adjust route discovery dynamically, the proposed routing algorithm can avoid flooding in the whole networks. Besides, Distance Update Threshold (DUT) is set up to reach the balance between real-time ability and update overhead of location information of nodes, meanwhile, the detection of relative distance vector can achieve the goal of adjusting forwarding condition. Simulation results reveal that DBLAR performs better than LAR1 in terms of packet successful delivery ratio, average end-to-end delay and routing-load, and the set of DUT and relative distance vector has a significant impact on this algorithm.
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.
Ant Colony Algorithm for Solving QoS Routing Problem
Institute of Scientific and Technical Information of China (English)
SUN Li-juan; WANG Liang-jun; WANG Ru-chuan
2004-01-01
Based on the state transition rule, the local updating rule and the global updating rule of ant colony algorithm, we propose an improved ant colony algorithm of the least-cost quality of service (QoS) unicast routing. The algorithm is used for solving the routing problem with delay, delay jitter, bandwidth, and packet loss-constrained. In the simulation, about 52.33% ants find the successful QoS routing , and converge to the best. It is proved that the algorithm is efficient and effective.
A Subpath Ejection Method for the Vehicle Routing Problem
1998-01-01
Generically, ejection chains are methods conceived to allow solution transformations to be efficiently carried out by modifying a variable number of their components at each step of a local search algorithm. We consider a subpath ejection chain method for the vehicle routing problem (VRP) under capacity and route length restrictions. The method undertakes the identification of a substructure named the flower reference structure which, besides coordinating moves during an ejection chain constr...
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...
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...
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...
Location-based route self-recovery for mobile ad hoc networks
Medidi, Sirisha; Wang, Jiong
2007-04-01
Mobile ad hoc network (MANET) is a radio packet network without dedicated infrastructures. In recent years it has received tremendous attention because of its self-configuration and self-maintenance capabilities. However, because of node mobility and shared wireless links, its routing protocol design presents nontrivial challenges such as broadcast storm, stale route and delay. This paper proposes a location-based route self-recovery technique for source-initiated routing protocols. The purpose of route self-recovery is to reduce overhead and delay during route maintenance as well as allowing continuous packet forwarding for fault resilience. The ns-2 based simulation shows throughput and overhead improvements of source-initiated routing with route self-recovery and in the case of highly dynamic environments and heavy traffic loads, it is more robust and scalable than other protocols.
Reliable Facility Location Problem with Facility Protection.
Tang, Luohao; Zhu, Cheng; Lin, Zaili; Shi, Jianmai; Zhang, Weiming
2016-01-01
This paper studies a reliable facility location problem with facility protection that aims to hedge against random facility disruptions by both strategically protecting some facilities and using backup facilities for the demands. An Integer Programming model is proposed for this problem, in which the failure probabilities of facilities are site-specific. A solution approach combining Lagrangian Relaxation and local search is proposed and is demonstrated to be both effective and efficient based on computational experiments on random numerical examples with 49, 88, 150 and 263 nodes in the network. A real case study for a 100-city network in Hunan province, China, is presented, based on which the properties of the model are discussed and some managerial insights are analyzed.
Dispersal routes reconstruction and the minimum cost arborescence problem.
Hordijk, Wim; Broennimann, Olivier
2012-09-01
We show that the dispersal routes reconstruction problem can be stated as an instance of a graph theoretical problem known as the minimum cost arborescence problem, for which there exist efficient algorithms. Furthermore, we derive some theoretical results, in a simplified setting, on the possible optimal values that can be obtained for this problem. With this, we place the dispersal routes reconstruction problem on solid theoretical grounds, establishing it as a tractable problem that also lends itself to formal mathematical and computational analysis. Finally, we present an insightful example of how this framework can be applied to real data. We propose that our computational method can be used to define the most parsimonious dispersal (or invasion) scenarios, which can then be tested using complementary methods such as genetic analysis.
A Study of Urgency Vehicle Routing Disruption Management Problem
Directory of Open Access Journals (Sweden)
Xuping Wang
2010-12-01
Full Text Available If a transit vehicle breaks down on a schedule trip, there are some vehicles in the system need to serve this trip and the former plan must be changed. For solving the urgency vehicle routing problem with disruption that may be vehicle breakdowns or traffic accidents in the logistics distribution system, through the analysis of the problem and the disruption measurement, the mathematics model is given based on the thought of disruption management. For the characteristics of the problem, a Lagrangian relaxation is given to simplify the model, and decompose the problem into two parts. The Lagrangian multiplier is given by subgradient method and the subproblems are solved by saving approach to gain the initial solution. A fast insertion algorithm is given to obtain a feasible solution for the primal problem. The results show that the algorithm designed in this paper performs very well for solving the urgency vehicle routing disruption management problem.
The Vehicle Routing Problem with Time Windows and Temporal Dependencies
DEFF Research Database (Denmark)
Rasmussen, Matias Sevel; Dohn, Anders Høeg; Larsen, Jesper
assignment and routing problem with synchronization constraints. The problem has been solved by column generation. The synchronized vehicle dispatching problem (SVDP), which is a dynamic vehicle routing problem with synchronization between vehicles. Constraint programming and local search are applied...... to arrive at high-quality feasible solutions. A problem from the Port of Singapore, where technicians are allocated to service jobs has previously been studied. For each job, a certain combination of technicians with individual skills is needed. The technicians must be present at the same time, and hence...... the schedule for each technician must respect a number of synchronization constraints with other schedules. The problem is solved using metaheuristics. Another application with synchronization between visits is in ground handling at airports. Teams drive around at the airport and are assigned tasks...
A Parallel Algorithm for the Vehicle Routing Problem
Energy Technology Data Exchange (ETDEWEB)
Groer, Christopher S [ORNL; Golden, Bruce [University of Maryland; Edward, Wasil [American University
2011-01-01
The vehicle routing problem (VRP) is a dicult and well-studied combinatorial optimization problem. We develop a parallel algorithm for the VRP that combines a heuristic local search improvement procedure with integer programming. We run our parallel algorithm with as many as 129 processors and are able to quickly nd high-quality solutions to standard benchmark problems. We assess the impact of parallelism by analyzing our procedure's performance under a number of dierent scenarios.
Directory of Open Access Journals (Sweden)
S. Mangai
2011-01-01
Full Text Available Problem statement: Routing and security are the main challenges for ad hoc networks due to dynamic topology as well as resource constraints. A designed protocol must provide scalable routing with better security. Lack of any central coordination and shared wireless medium makes them more vulnerable to attacks than wired networks. And also resource constraints such as limited energy and size also play an important role in the protocols designed for security. Approach: In this study, Improved Location aided Cluster based Routing Protocol (ILCRP for GPS enabled MANETs was analysed in MANETs with malicious nodes and an Intrusion Detection System was used to increase the packet delivery ratio. ILCRP makes use of location aided routing in the presence of cluster based routing Protocol. Results: Use of location information with security against attacks results in high packet delivery ratio for the cluster based routing protocol. Simulations are performed using NS2 by varying the number of nodes. Conclusion: The results illustrate ILCRP provides higher delivery ratio with IDS.
In-route skyline querying for location-based services
DEFF Research Database (Denmark)
Xuegang, Huang; Jensen, Kristian S.
2005-01-01
With the emergence of an infrastructure for location-aware mobile services, the processing of advanced, location-based queries that are expected to underlie such services is gaining in relevance, While much work has assumed that users move in Euclidean space, this paper assumes that movement is c...
MULTI-VEHICLE COVERING TOUR PROBLEM: BUILDING ROUTES FOR URBAN PATROLLING
Directory of Open Access Journals (Sweden)
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.
Parallelization of the Vehicle Routing Problem with Time Windows
1999-01-01
This dissertation presents a number of algorithms for solving the Vehicle Routing Problem with Time Windows (VRPTW). The VRPTW is a generalization of the well known capacity constrained Vehicle Routing Problem (VRP). In the VRP a fleet of vehicles based at a central depot must service a set of customers. In the VRPTW each customer has a time window. Service of a customer must begin within the interval given by the time window. The objective is to minimize some aspect of operating costs (e.g. ...
Metaheuristics applied to vehicle routing. A case study. Parte 1: formulating the problem
Directory of Open Access Journals (Sweden)
Guillermo González Vargas
2010-04-01
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.
Multi-depot Vehicle Routing Problem with Pickup and Delivery Requests
Sombuntham, Pandhapon; Kachitvichyanukul, Voratas
2010-10-01
This paper considers a multi-depot vehicle routing problem with pickup and delivery requests. In the problem of interest, each location may have goods for both pickup and delivery with multiple delivery locations that may not be the depots. These characteristics are quite common in industrial practice. A particle swarm optimization algorithm with multiple social learning structures is proposed for solving the practical case of multi-depot vehicle routing problem with simultaneous pickup and delivery and time window. A new decoding procedure is implemented using the PSO class provided in the ETLib object library. Computational experiments are carried out using the test instances for the pickup and delivery problem with time windows (PDPTW) as well as a newly generated instance. The preliminary results show that the proposed algorithm is able to provide good solutions to most of the test problems.
Institute of Scientific and Technical Information of China (English)
王海燕; 张岐山
2013-01-01
废弃物处理设施是典型的“Semi-desirable”设施,其选址相关的决策需要考虑成本、负效应等多个相互冲突的目标.废弃物中转站的选址和路径优化是一类周期性选址-路径问题(PLRP),目前缺乏对这类问题的多目标优化的研究.以多目标城市废弃物收运网络周期性选址-路径问题为研究对象,提出基于扩散距离的负效应测度方法;建立考虑负效应和成本的双目标混合整数规划模型;设计DRECWA-LS算法,结合启发式优化策略,求解收运计划对应的周期性选址-路径问题,并采用扩展邻域搜索策略的多目标进化算法实现对可行收运计划的深度搜索,同步求解收运计划、中转站选址-分配及车辆路径三个问题.算例结果显示:算法能成功求解较大规模问题,具有较高的求解质量和运算效率.%Waste disposal facilities are kinds of typical "semi-desirable facilities".Some incompatible objectives such as cost and obnoxious effect etc.should be considered in the process of location and other related decisions of these facilities.The location-routing problem in waste logistics network in cities is one kind of typical periodic location routing problem (PLRP),for different population centers can be visited by different frequency in certain period,however,the multi-objective optimization of this problem is short of research.A multi-objective PLRP is studied in this paper,which combines the practical situation of waste logistics network in cities.A new method is proposed measuring negative effect based on the concept of dispersion distance; a mixed integer programming model concerning two objectives of average total cost and average negative effect is raised; a multi-objective evolutionary algorithm is devised to solve locationallocation problem,visiting scheduling problem and vehicle routing problem simultaneously.The global algorithm strengthens an extension local search deepening the search of feasible
A novel heuristic algorithm for capacitated vehicle routing problem
Kır, Sena; Yazgan, Harun Reşit; Tüncel, Emre
2017-02-01
The vehicle routing problem with the capacity constraints was considered in this paper. It is quite difficult to achieve an optimal solution with traditional optimization methods by reason of the high computational complexity for large-scale problems. Consequently, new heuristic or metaheuristic approaches have been developed to solve this problem. In this paper, we constructed a new heuristic algorithm based on the tabu search and adaptive large neighborhood search (ALNS) with several specifically designed operators and features to solve the capacitated vehicle routing problem (CVRP). The effectiveness of the proposed algorithm was illustrated on the benchmark problems. The algorithm provides a better performance on large-scaled instances and gained advantage in terms of CPU time. In addition, we solved a real-life CVRP using the proposed algorithm and found the encouraging results by comparison with the current situation that the company is in.
Particle Swarm Optimization with Genetic Operators for Vehicle Routing Problem
Directory of Open Access Journals (Sweden)
P. V. PURANIK
2012-07-01
Full Text Available Vehicle Routing Problem (VRP is to find shortest route thereby minimizing total cost. VRP is a NP-hard and Combinatorial optimization problem. Such problems increase exponentially with the problem size. Various derivative based optimization techniques are employed for optimization. Derivative based optimization techniques are difficult to evaluate. Therefore parallel search algorithm emerged to solve VRP. In this work, a particle swarm optimization (PSO algorithm and Genetic algorithm (GA with crossover and mutation operator are applied to two typical functions to deal with the problem of VRP efficiently using MATLAB software. Before solving VRP, optimization of functions using PSO and GA are checked. In this paper capacitate VRP with time window (CVRPTW is proposed. The computational result shows generation of input for VRP, optimization of Rastrigin function, Rosenbrock function using PSO and GA.
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.
New exact algorithms for the vehicle routing problem
Energy Technology Data Exchange (ETDEWEB)
Mingozzi, A.; Galdacci, R.; Christofides, N.; Hadjiconstantinou, E.
1994-12-31
We consider the problem in which a fleet of M vehicles stationed at a central depot is to be optimally routed to supply customers with known demands subject to vehicle capacity constraints. This problem is referred as the Vehicle Routing Problem (VRP). In this paper we present two exact branch and bound algorithms for solving the VRP based on a Set Partitioning formulation of the problem. The first algorithm is based on a bounding procedure that finds a heuristic solution of the dual of the LP-relaxation of the Set Partitioning formulation without generating the entire set partitioning matrix. The dual solution obtained is then used to limit the set of the feasible routes containing the optimal VRP solution. The resulting Set Partitioning problem is solved by using a branch and bound method. The second algorithm is based on a lower bound that makes use of a new surrogate relaxation of the Set Partitioning problem. The two algorithms can solve both symmetric and asymmetric VRPS. Computational results are presented for a number of problems derived from the literature.
A Survey of the Routing and Wavelength Assignment Problem
DEFF Research Database (Denmark)
Gamst, Mette
When transmitting data in an all-optical network, data connections must be established in such a way that two or more connections never share a wavelength on the same fi ber. The NP-hard Routing and Wavelength Assignment (RWA) problem consists of finding paths and wavelengths for a set of data...
Meta Heuristic Algorithms for Vehicle Routing Problem with Stochastic Demands
Directory of Open Access Journals (Sweden)
Geetha Shanmugam
2011-01-01
Full Text Available Problem statement: The shipment of goods from manufacturer to the consumer is a focal point of distribution logistics. In reality, the demand of consumers is not known a priori. This kind of distribution is dealt by Stochastic Vehicle Routing Problem (SVRP which is a NP-hard problem. In this proposed work, VRP with stochastic demand is considered. A probability distribution is considered as a random variable for stochastic demand of a customer. Approach: In this study, VRPSD is resolved using Meta heuristic algorithms such as Genetic Algorithm (GA, Particle Swarm Optimization (PSO and Hybrid PSO (HPSO. Dynamic Programming (DP is used to find the expected cost of each route generated by GA, PSO and HPSO. Results: The objective is to minimize the total expected cost of a priori route. The fitness value of a priori route is calculated using DP. In proposed HPSO, the initial particles are generated based Nearest Neighbor Heuristic (NNH. Elitism is used in HPSO for updating the particles. The algorithm is implemented using MATLAB7.0 and tested with problems having different number of customers. The results obtained are competitive in terms of execution time and memory usage. Conclusion: The computational time is reduced as polynomial time as O(nKQ time and the memory required is O(nQ. The ANOVA test is performed to compare the proposed HPSO with other heuristic algorithms.
Periodic Sweep Coverage Scheme Based on Periodic Vehicle Routing Problem
Directory of Open Access Journals (Sweden)
Li Shu
2014-03-01
Full Text Available We provide a sweep coverage algorithm for routing mobile sensors that communicate with a central data sink. This algorithm improves on its predecessors by reducing the number of unnecessary scans when different points of interest (POIs have different requirements for the time interval within which they must be scanned (sweep period. Most sweep coverage algorithms seek to minimize the number of sensors required to cover a given collection of POIs. When POIs have different sweep period requirements, existing algorithms will produce solutions in which sensors visit some POIs much more frequently than is necessary. We define this as the POI Over-Coverage problem. In order to address this problem we develop a Periodic Sweep Coverage (PSC scheme based on a well-known solution to the Periodic Vehicle Routing Problem (PVRP. Our algorithm seeks a route for the mobile sensors that minimizes the number of unnecessary visits to each POI. To verify and test the proposed scheme we implemented a C++ simulation and ran scenarios with a variety of POI topologies (number and distribution of the POIs and the speed at which sensors could travel. The simulation results show that the PSC algorithm outperforms other sweep coverage algorithms such as CSweep and Vehicle Routing Problem Sweep Coverage (VRPSC on both the average number of sensors in a solution and in the computational time required to find a solution. Our results also demonstrate that the PSC scheme is more suitable for the sweep coverage scenarios in which higher speed mobile sensors are used.
Genetic Algorithm for Vehicle Routing Problem with Backhauls
Directory of Open Access Journals (Sweden)
W.Nurfahizul Ifwah. WA
2012-07-01
Full Text Available The Vehicle Routing Problem with Backhauls (VRPB is an extension of the classical Vehicle Routing Problem (VRP that includes both a set of customers to whom products are to be delivered and a set of suppliers whose goods need to be transported back to the distribution center. In addition, on each route all deliveries have to be made before any goods can be picked up to avoid rearranging the loads on the vehicle. The main objective for VRPB is to determine the network route to minimize the total cost, distance or time. There are a few methods that can be identified to solve this VRPB. The objective of this research is to present a heuristic method, called Genetic Algorithm (GA, for the VRPB. In brief, GA is a system developing methods that use the natural principle of a genetic population and involved three main processes that is crossover, mutation and inversion. GA implementation on the 68 nodes problems taken from Goetschalckx and Jacobs- Blecha is done by using Microsoft C++ Programming. Solutions to the problem are presented and performance comparison is conducted with the existing best solution. Several parameters in GA will be tested such as population size, crossover point and also the choice of operators used.
Classification of Ship Routing and Scheduling Problems in Liner Shipping
DEFF Research Database (Denmark)
Kjeldsen, Karina Hjortshøj
2011-01-01
This article provides a classification scheme for ship routing and scheduling problems in liner shipping in line with the current and future operational conditions of the liner shipping industry. Based on the classification, the literature is divided into groups whose main characteristics...
Practical inventory routing: A problem definition and an optimization method
Geiger, Martin Josef
2011-01-01
The global objective of this work is to provide practical optimization methods to companies involved in inventory routing problems, taking into account this new type of data. Also, companies are sometimes not able to deal with changing plans every period and would like to adopt regular structures for serving customers.
STUDI TENTANG TRAVELLING SALESMAN DAN VEHICLE ROUTING PROBLEM DENGAN TIME WINDOWS
I Nyoman Sutapa; I Gede Agus Widyadana; Christine Christine
2003-01-01
The article shows the study of model development of travelling salesman problem. Three models are studied, i.e. travelling salesman problem with time windows, vehicle routing problem, and vehicle routing problem with time windows. Abstract in Bahasa Indonesia : Dalam artikel ini dipaparkan kajian mengenai pengembangan model travelling salesman problem. Ada tiga model yang dikaji yaitu travelling salesman problem dengan time windows, vehicle routing problem, serta vehicle routing problem denga...
Anonymity Preserving Routing In Location Privacy Schemes In Wireless Sensor Networks
Directory of Open Access Journals (Sweden)
R Regin
2015-12-01
Full Text Available Location privacy measures need to be developed to prevent the opponent from determining the physical locations of source sensors and sinks. An opponent can easily intercept network traffic due to the use of a broadcast medium for routing packets and get detailed information such as packet transmission time and frequency to perform traffic analysis and infer the locations of monitored objects and data sinks. On the other hand, sensors usually have limited processing speed and energy supplies. It is very expensive to apply traditional anonymous communication techniques for hiding the communication between sensor nodes and sinks. The existing source-location privacy protects the location of monitored objects to increase the number of messages sent by the source before the object is located by the attacker. The flooding technique has the source node send each packet through numerous paths to a sink making it difficult for an opponent to trace the source. The locations of sinks can be protected from a local eavesdropper by hashing the ID field in the packet header. But opponent can track sinks by carrying out time correlation and rate monitoring attacks. Besides protection some source nodes are transferring relatively large amounts of data in existing system. As a result, these nodes run out of battery faster due to improper position of nodes and sinks. Thus in the proposed system the sinks should be located as optimally as possible to reduce traffic flow and energy consumption for sensor nodes. Hence Sink placement problem is resolved for minimizing the delay as well as maximizing the lifetime of a WSN. Thus proposed system is efficient in terms of overhead and functionality when compared to existing system.
A node-disjoint multi-path routing protocol based on location ...
African Journals Online (AJOL)
user
Keywords: Multi-path Routing Protocol, Mobile Ad hoc Networks, Location Prediction, Node ... stress the need to use similar paths for multi-path data propagation. ..... maintained for every source with which the destination is in communication.
Routing Protocol with Optimal Location of Aggregation Point in Wireless Sensor Networks
Institute of Scientific and Technical Information of China (English)
无
2006-01-01
A wireless sensor network is typically composed of hundreds, even thousands of tiny sensors used to monitor physical phenomena. As data collected by the sensors are often redundant, data aggregation is important for conserving energy. In this paper, we present a new routing protocol with optimal data aggregation. This routing protocol has good performance due to its optimal selection of aggregation point locations. This paper details the optimal selection of aggregation point locations.
Directory of Open Access Journals (Sweden)
Jasmine Norman
2010-07-01
Full Text Available A pervasive network consists of heterogeneous devices with different computing, storage, mobility and connectivity properties working together to solve real-world problems. The emergence of wireless sensor networks has enabled new classes of applications in pervasive world that benefit a large number of fields. Routing in wireless sensor networks is a demanding task. This demand has led to a number of routing protocols which efficiently utilize the limited resources available at the sensor nodes. Most of these protocols either support stationary sensor networks or mobile networks. This paper proposes an energy efficient routing protocol for heterogeneous sensor networks with the goal of finding the nearest base station or sink node. Hence the problem of routing is reduced to finding the nearest base station problem in heterogeneous networks. The protocol HLAODV when compared with popular routing protocols AODV and DSR is energy efficient. Also the mathematical model of the proposed system and its properties are studied.
The Vehicle Routing Problem with Limited Vehicle Capacities
Directory of Open Access Journals (Sweden)
Fernando Taracena Sanz
2013-09-01
Full Text Available The vehicle routing problem (VRP has been an important research topic during the last decades because of his vital role in the productive systems efficiency. Most of the work done in this area has been directed to solve large scale problems which may not apply for small companies which are a very important engine of the world economy. This paper approaches the problem when limited vehicle resources are present and road transportation is used. This study assumes variable customer orders. Variable volume and weight vehicle capacities are considered and the proposed algorithm develops the vehicle delivery routes and the set of customer orders to deliver per vehicle minimizing a cost objective function. In sampling small company’s logistics costs, big cost savings are found when using the proposed method.
Mass Transport Vehicle Routing Problem (MTVRP) and the Associated Network Design Problem (MTNDP)
2005-01-01
This research studies a new class of dynamic problem MTVRP where n vehicles are routed in real time in a fast varying environment to pickup and deliver m passengers when both n and m are big. The problem is very relevant to future transportation options involving large scale real-time routing of shared-ride fleet transit vehicles. Traditionally, dynamic routing solutions were found as static approximations for smaller-scale problems or using local heuristics for the larger-scale ones. General...
The time-dependent prize-collecting arc routing problem
DEFF Research Database (Denmark)
Black, Dan; Eglese, Richard; Wøhlk, Sanne
2013-01-01
A new problem is introduced named the Time-Dependent Prize-Collecting Arc Routing Problem (TD-PARP). It is particularly relevant to situations where a transport manager has to choose between a number of full truck load pick-ups and deliveries on a road network where travel times change...... with the time of day. 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 information. Both algorithms are capable of finding good solutions, though...
Ant colony optimization for the real-time train routing selection problem
SAMA, Marcella; Pellegrini, Paola; D'Ariano, Andrea; Rodriguez, Joaquin; Pacciarelli, Dario
2016-01-01
This paper deals with the real-time problem of scheduling and routing trains in a railway network. In the related literature, this problem is usually solved starting from a subset of routing alternatives and computing the near-optimal solution of the simplified routing problem. We study how to select the best subset of routing alternatives for each train among all possible alternatives. The real-time train routing selection problem is formulated as an integer linear programming formulation an...
Dynamic Air Route Open-Close Problem for Airspace Management
Institute of Scientific and Technical Information of China (English)
无
2007-01-01
Dynamic airspace management plans and assigns airspace resources to airspace users on demand to increase airspace capacity. Although many studies of air traffic flow management (ATFM) have sought to optimally allocate air traffic to get the best use of given airspace resources, few studies have focused on how to build an efficient air traffic network or how to adjust the current network in real time. This paper presents an integer program model named the dynamic air route open-close problem (DROP). DROP has a cost-based objective function which takes into account constraints such as the shortest occupancy time of routes, which are not considered in ATFM models. The aim of DROP is to determine which routes will be opened to a certain user during a given time period. Simulation results show that DROP can facilitate utilization of air routes. DROP, a simplified version of an air traffic network constructing problem, is the first step towards realizing dynamic airspace management. The combination of ATFM and DROP can facilitate decisions toward more reasonable, efficient use of limited airspace resources.
Optimization of Multiple Vehicle Routing Problems using Approximation Algorithms
Nallusamy, R; Dhanalaksmi, R; Parthiban, P
2010-01-01
This paper deals with generating of an optimized route for multiple Vehicle routing Problems (mVRP). We used a methodology of clustering the given cities depending upon the number of vehicles and each cluster is allotted to a vehicle. k- Means clustering algorithm has been used for easy clustering of the cities. In this way the mVRP has been converted into VRP which is simple in computation compared to mVRP. After clustering, an optimized route is generated for each vehicle in its allotted cluster. Once the clustering had been done and after the cities were allocated to the various vehicles, each cluster/tour was taken as an individual Vehicle Routing problem and the steps of Genetic Algorithm were applied to the cluster and iterated to obtain the most optimal value of the distance after convergence takes place. After the application of the various heuristic techniques, it was found that the Genetic algorithm gave a better result and a more optimal tour for mVRPs in short computational time than other Algorit...
Optimization of Multiple Vehicle Routing Problems Using Approximation Algorithms
Directory of Open Access Journals (Sweden)
R. Nallusamy
2009-12-01
Full Text Available This paper deals with generating of an optimized route for multiple Vehicle routing Problems (mVRP. We used a methodology of clustering the given cities depending upon the number of vehicles and eachcluster is allotted to a vehicle. k- Means clustering algorithm has been used for easy clustering of the cities. In this way the mVRP has been converted into VRP which is simple in computation compared to mVRP. After clustering, an optimized route is generated for each vehicle in its allotted cluster. Once the clustering had been done and after the cities were allocated to the various vehicles, each cluster/tour was taken as an individual Vehicle Routing problem and the steps of Genetic Algorithm were applied to the cluster and iterated to obtain the most optimal value of the distance after convergence takes place. After the application of the variousheuristic techniques, it was found that the Genetic algorithm gave a better result and a more optimal tour for mVRPs in short computational time than other Algorithms due to the extensive search and constructive nature of the algorithm.
STUDI TENTANG TRAVELLING SALESMAN DAN VEHICLE ROUTING PROBLEM DENGAN TIME WINDOWS
Directory of Open Access Journals (Sweden)
I Nyoman Sutapa
2003-01-01
Full Text Available The article shows the study of model development of travelling salesman problem. Three models are studied, i.e. travelling salesman problem with time windows, vehicle routing problem, and vehicle routing problem with time windows. Abstract in Bahasa Indonesia : Dalam artikel ini dipaparkan kajian mengenai pengembangan model travelling salesman problem. Ada tiga model yang dikaji yaitu travelling salesman problem dengan time windows, vehicle routing problem, serta vehicle routing problem dengan time windows. Kata-kunci: travelling salesman problem, vehicle routing problem, time windows.
Performansi Algoritma CODEQ dalam Penyelesaian Vehicle Routing Problem
Directory of Open Access Journals (Sweden)
Annisa Kesy Garside
2014-01-01
Full Text Available Genetic Algorithm, Tabu Search, Simulated Annealing, and Ant Colony Optimization showed a good performance in solving vehicle routing problem. However, the generated solution of those algorithms was changeable regarding on the input parameter of each algorithm. CODEQ is a new, parameter free meta-heuristic algorithm that had been successfully used to solve constrained optimization problems, integer programming, and feed-forward neural network. The purpose of this research are improving CODEQ algorithm to solve vehicle routing problem and testing the performance of the improved algorithm. CODEQ algorithm is started with population initiation as initial solution, generated of mutant vector for each parent in every iteration, replacement of parent by mutant when fitness function value of mutant is better than parent’s, generated of new vector for each iteration based on opposition value or chaos principle, replacement of worst solution by new vector when fitness function value of new vector is better, iteration ceasing when stooping criterion is achieved, and sub-tour determination based on vehicle capacity constraint. The result showed that the average deviation of the best-known and the best-test value is 6.35%. Therefore, CODEQ algorithm is good in solving vehicle routing problem.
Enhanced ant colony optimization for inventory routing problem
Wong, Lily; Moin, Noor Hasnah
2015-10-01
The inventory routing problem (IRP) integrates and coordinates two important components of supply chain management which are transportation and inventory management. We consider a one-to-many IRP network for a finite planning horizon. The demand for each product is deterministic and time varying as well as a fleet of capacitated homogeneous vehicles, housed at a depot/warehouse, delivers the products from the warehouse to meet the demand specified by the customers in each period. The inventory holding cost is product specific and is incurred at the customer sites. The objective is to determine the amount of inventory and to construct a delivery routing that minimizes both the total transportation and inventory holding cost while ensuring each customer's demand is met over the planning horizon. The problem is formulated as a mixed integer programming problem and is solved using CPLEX 12.4 to get the lower and upper bound (best integer) for each instance considered. We propose an enhanced ant colony optimization (ACO) to solve the problem and the built route is improved by using local search. The computational experiments demonstrating the effectiveness of our approach is presented.
ACTIVITY-BASED COSTING FOR VEHICLE ROUTING PROBLEMS
Directory of Open Access Journals (Sweden)
A. J. Moolman
2012-01-01
Full Text Available
ENGLISH ABSTRACT:Activity-based costing (ABC is a costing model that identifies activity costs in an organisation. It assigns the cost of activity resources to generate the actual cost of products in order to eliminateunprofitable products and to lowerthe prices of overpriced ones. The vehicle routing problem (VRP is a combinatorial optimisation and nonlinear programming problem that seeks to service a number of customers with a fleet of vehicles in a cost-effective manner. In this article we propose a new approach to determine costing for vehicle routing type problems. The methodology incorporates the predictive sharing of a resource by clustering producers.
AFRIKAANSE OPSOMMING: ‘Activity-based costing’ (ABC is ’n kostemodel wat die aktiwiteitskoste in ’n organisasie identifiseer. Dit allokeer die koste van die bronne sodat die ware koste van die vervaardiging en dienste van die produk bereken kan word om winsgewendheid te bepaal. Die ‘vehicle routing problem’ (VRP is ’n kombinatoriese optimisering en nie-lineêre programmeringsprobleem wat verskeie kliënte met ’n vloot voertuie in die mees koste- effektiewe manier bedien. Die artikel bespreek ’n nuwe metode om die kombinasie van probleme op te los. Die metode maak gebruik van groeperingsalgoritmes om meer akkurate voertuig deling te voorspel.
Solving Arc Routing Problems Using the Lin-Kernighan-Helsgaun Algorithm
DEFF Research Database (Denmark)
Helsgaun, Keld
It is well known that many arc routing problems can be transformed into the Equality Generalized Traveling Salesman Problem (E-GTSP), which in turn can be transformed into a standard Asymmetric Traveling Salesman Problem (TSP). This opens up the possibility of solving arc routing problems using...... and general routing problem instances....
Analysis of the single-vehicle cyclic inventory routing problem
Aghezzaf, El-Houssaine; Zhong, Yiqing; Raa, Birger; Mateo, Manel
2012-11-01
The single-vehicle cyclic inventory routing problem (SV-CIRP) consists of a repetitive distribution of a product from a single depot to a selected subset of customers. For each customer, selected for replenishments, the supplier collects a corresponding fixed reward. The objective is to determine the subset of customers to replenish, the quantity of the product to be delivered to each and to design the vehicle route so that the resulting profit (difference between the total reward and the total logistical cost) is maximised while preventing stockouts at each of the selected customers. This problem appears often as a sub-problem in many logistical problems. In this article, the SV-CIRP is formulated as a mixed-integer program with a nonlinear objective function. After a thorough analysis of the structure of the problem and its features, an exact algorithm for its solution is proposed. This exact algorithm requires only solutions of linear mixed-integer programs. Values of a savings-based heuristic for this problem are compared to the optimal values obtained for a set of some test problems. In general, the gap may get as large as 25%, which justifies the effort to continue exploring and developing exact and approximation algorithms for the SV-CIRP.
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...... for obtaining optimal solutions to the problem and present computational results based on a set of standard benchmark instances....
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
-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......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...
Parallelization of the Vehicle Routing Problem with Time Windows
DEFF Research Database (Denmark)
Larsen, Jesper
1999-01-01
of customers. In the VRPTW each customer has a time window. Service of a customer must begin within the interval given by the time window. The objective is to minimize some aspect of operating costs (e.g. total distance traveled, number of vehicles needed or a combination of parameters). Since the late 80's......This dissertation presents a number of algorithms for solving the Vehicle Routing Problem with Time Windows (VRPTW). The VRPTW is a generalization of the well known capacity constrained Vehicle Routing Problem (VRP). In the VRP a fleet of vehicles based at a central depot must service a set...... obtained using Lagrange relaxation. This dissertation is divided into three parts. First the theoretical framework is described. Thereafter a number of techniques to improve the performance of the column-generation framework are proposed and analyzed. Finally a parallel algorithm based on the sequential...
The Military Inventory Routing Problem with Direct Delivery
2014-03-27
3 1.1.2 Vendor Managed Inventory Replenishment ( VMI ) . . . . . . . . . . . . . . 7 1.2 The Military Inventory Routing Problem...within the IRP and VRP in the literature. A focused review of the vendor managed inventory replen- ishment ( VMI ) business practice appears in Section...formulation to build the base sequence. 1.1.2 Vendor Managed Inventory Replenishment ( VMI ). Vendor managed inventory ( VMI ) replenishment is a business
Dynamic vehicle routing problems: Three decades and counting
DEFF Research Database (Denmark)
Psaraftis, Harilaos N.; Wen, Min; Kontovas, Christos A.
2016-01-01
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...... linkages of methodology to technological advances and analysis of worst case or average case performance of heuristics....
Vehicle Coordinated Strategy for Vehicle Routing Problem with Fuzzy Demands
Directory of Open Access Journals (Sweden)
Chang-shi Liu
2016-01-01
Full Text Available The vehicle routing problem with fuzzy demands (VRPFD is considered. A fuzzy reasoning constrained program model is formulated for VRPFD, and a hybrid ant colony algorithm is proposed to minimize total travel distance. Specifically, the two-vehicle-paired loop coordinated strategy is presented to reduce the additional distance, unloading times, and waste capacity caused by the service failure due to the uncertain demands. Finally, numerical examples are presented to demonstrate the effectiveness of the proposed approaches.
Electric Vehicle Routing Problems : models and solution approaches
Montoya, Jose-Alejandro
2016-01-01
Electric vehicles (evs) are one of the most promising technologies to reduce the greenhouse gas emissions. For this reason, the use of evs in service operations has dramatically increased in recent years. Despite their environmental benefits, evs still face technical constraints such as short autonomy and long charging times. Taking into account these constraints when planning ev operations leads to a new breed of vehicle routing problems (vrps), known as electricVrps (evrps). In addition, to...
Cluster Based Location-Aided Routing Protocol for Large Scale Mobile Ad Hoc Networks
Wang, Yi; Dong, Liang; Liang, Taotao; Yang, Xinyu; Zhang, Deyun
Routing algorithms with low overhead, stable link and independence of the total number of nodes in the network are essential for the design and operation of the large-scale wireless mobile ad hoc networks (MANET). In this paper, we develop and analyze the Cluster Based Location-Aided Routing Protocol for MANET (C-LAR), a scalable and effective routing algorithm for MANET. C-LAR runs on top of an adaptive cluster cover of the MANET, which can be created and maintained using, for instance, the weight-based distributed algorithm. This algorithm takes into consideration the node degree, mobility, relative distance, battery power and link stability of mobile nodes. The hierarchical structure stabilizes the end-to-end communication paths and improves the networks' scalability such that the routing overhead does not become tremendous in large scale MANET. The clusterheads form a connected virtual backbone in the network, determine the network's topology and stability, and provide an efficient approach to minimizing the flooding traffic during route discovery and speeding up this process as well. Furthermore, it is fascinating and important to investigate how to control the total number of nodes participating in a routing establishment process so as to improve the network layer performance of MANET. C-LAR is to use geographical location information provided by Global Position System to assist routing. The location information of destination node is used to predict a smaller rectangle, isosceles triangle, or circle request zone, which is selected according to the relative location of the source and the destination, that covers the estimated region in which the destination may be located. Thus, instead of searching the route in the entire network blindly, C-LAR confines the route searching space into a much smaller estimated range. Simulation results have shown that C-LAR outperforms other protocols significantly in route set up time, routing overhead, mean delay and packet
The dual of a generalized minimax location problem
DEFF Research Database (Denmark)
Juel, Henrik; Love, Robert F.
1992-01-01
This paper develops the dual formulation of a generalized minimax facility location problem which has distance and linear constraints......This paper develops the dual formulation of a generalized minimax facility location problem which has distance and linear constraints...
The dual of a generalized minimax location problem
DEFF Research Database (Denmark)
Juel, Henrik; Love, Robert F.
1992-01-01
This paper develops the dual formulation of a generalized minimax facility location problem which has distance and linear constraints......This paper develops the dual formulation of a generalized minimax facility location problem which has distance and linear constraints...
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. ...
Robust Optimisation Approach for Vehicle Routing Problems with Uncertainty
Directory of Open Access Journals (Sweden)
Liang Sun
2015-01-01
Full Text Available We formulated a solution procedure for vehicle routing problems with uncertainty (VRPU for short with regard to future demand and transportation cost. Unlike E-SDROA (expectation semideviation robust optimisation approach for solving the proposed problem, the formulation focuses on robust optimisation considering situations possibly related to bidding and capital budgets. Besides, numerical experiments showed significant increments in the robustness of the solutions without much loss in solution quality. The differences and similarities of the robust optimisation model and existing robust optimisation approaches were also compared.
Dynamic vehicle routing problems: Three decades and counting
DEFF Research Database (Denmark)
Psaraftis, Harilaos N.; Wen, Min; Kontovas, Christos A.
2016-01-01
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 a real explosion in related papers. Our paper sheds more light into work in this area over more than 3 decades by developing a taxonomy...... 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 nature of the dynamic element, (10...
Directory of Open Access Journals (Sweden)
Shyamala Ramachandran
2011-01-01
Full Text Available Problem statement: Wireless sensor networks have been used in many applications, such as home automation, military surveillances and entity tracking systems. The sensor nodes have low computational capabilities and are highly resource constrained. Routing protocols of wireless sensor networks are prone to various routing attacks, such as black hole, rushing, wormhole, Sybil and denial of service attacks. Approach: The objective of this study was to examine the effects of wormhole in conjunction with Sybil attack on a location based-Geographic Multicast Routing (GMR protocol. Results: The NS-2 based simulation was used in analyzing the wormhole in conjunction with Sybil attack on GMR. Conclusion: It is found that, the Sybil attack degrades the network performance by 24% and the wormhole attack by 20%.
TSP based Evolutionary optimization approach for the Vehicle Routing Problem
Kouki, Zoulel; Chaar, Besma Fayech; Ksouri, Mekki
2009-03-01
Vehicle Routing and Flexible Job Shop Scheduling Problems (VRP and FJSSP) are two common hard combinatorial optimization problems that show many similarities in their conceptual level [2, 4]. It was proved for both problems that solving techniques like exact methods fail to provide good quality solutions in a reasonable amount of time when dealing with large scale instances [1, 5, 14]. In order to overcome this weakness, we decide in the favour of meta heuristics and we focalize on evolutionary algorithms that have been successfully used in scheduling problems [1, 5, 9]. In this paper we investigate the common properties of the VRP and the FJSSP in order to provide a new controlled evolutionary approach for the CVRP optimization inspired by the FJSSP evolutionary optimization algorithms introduced in [10].
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.
Dijkstra, Arjan; Roodbergen, Kees Jan
2017-01-01
Order picking is one of the most time-critical processes in warehouses. We focus on the combined effects of routing methods and storage location assignment on process performance. We present exact formulas for the average route length under any storage location assignment for four common routing
Ant Colony Optimization for Capacitated Vehicle Routing Problem
Directory of Open Access Journals (Sweden)
H. V. Seow
2012-01-01
Full Text Available Problem statement: The Capacitated Vehicle Routing Problem (CVRP is a well-known combinatorial optimization problem which is concerned with the distribution of goods between the depot and customers. It is of economic importance to businesses as approximately 10-20% of the final cost of the goods is contributed by the transportation process. Approach: This problem was tackled using an Ant Colony Optimization (ACO combined with heuristic approaches that act as the route improvement strategies. The proposed ACO utilized a pheromone evaporation procedure of standard ant algorithm in order to introduce an evaporation rate that depends on the solutions found by the artificial ants. Results: Computational experiments were conducted on benchmark data set and the results obtained from the proposed algorithms shown that the application of combination of two different heuristics in the ACO had the capability to improve the ants solutions better than ACO embedded with only one heuristic. Conclusion: ACO with swap and 3-opt heuristic has the capability to tackle the CVRP with satisfactory solution quality and run time. It is a viable alternative for solving the CVRP.
Bus Stops Location and Bus Route Planning Using Mean Shift Clustering and Ant Colony in West Jakarta
Supangat, Kenny; Eko Soelistio, Yustinus
2017-03-01
Traffic Jam has been a daily problem for people in Jakarta which is one of the busiest city in Indonesia up until now. Even though the official government has tried to reduce the impact of traffic issues by developing a new public transportation which takes up a lot of resources and time, it failed to diminish the problem. The actual concern to this problem actually lies in how people move between places in Jakarta where they always using their own vehicle like cars, and motorcycles that fill most of the street in Jakarta. Among much other public transportations that roams the street of Jakarta, Buses is believed to be an efficient transportation that can move many people at once. However, the location of the bus stop is now have moved to the middle of the main road, and its too far for the nearby residence to access to it. This paper proposes an optimal location of optimal bus stops in West Jakarta that is experimentally proven to have a maximal distance of 350 m. The optimal location is estimated by means of mean shift clustering method while the optimal routes are calculated using Ant Colony algorithm. The bus stops locations rate of error is 0.07% with overall route area of 32 km. Based on our experiments, we believe our proposed bus stop plan can be an interesting alternative to reduce traffic congestion in West Jakarta.
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 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....
The dynamic multi-period vehicle routing problem
DEFF Research Database (Denmark)
Wen, Min; Cordeau, Jean-Francois; Laporte, Gilbert
2010-01-01
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...... planning horizon. The multi-objective aspect of the problem is handled through a scalar technique approach. Computational results show that the proposed approach can yield high quality solutions within reasonable running times....... 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...
General heuristics algorithms for solving capacitated arc routing problem
Fadzli, Mohammad; Najwa, Nurul; Masran, Hafiz
2015-05-01
In this paper, we try to determine the near-optimum solution for the capacitated arc routing problem (CARP). In general, NP-hard CARP is a special graph theory specifically arises from street services such as residential waste collection and road maintenance. By purpose, the design of the CARP model and its solution techniques is to find optimum (or near-optimum) routing cost for a fleet of vehicles involved in operation. In other words, finding minimum-cost routing is compulsory in order to reduce overall operation cost that related with vehicles. In this article, we provide a combination of various heuristics algorithm to solve a real case of CARP in waste collection and benchmark instances. These heuristics work as a central engine in finding initial solutions or near-optimum in search space without violating the pre-setting constraints. The results clearly show that these heuristics algorithms could provide good initial solutions in both real-life and benchmark instances.
A green vehicle routing problem with customer satisfaction criteria
Afshar-Bakeshloo, M.; Mehrabi, A.; Safari, H.; Maleki, M.; Jolai, F.
2016-08-01
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.
A Self-organizing Location and Mobility-Aware Route Optimization Protocol for Bluetooth Wireless
Directory of Open Access Journals (Sweden)
Sheikh Tahir Bakhsh
2016-06-01
Full Text Available Bluetooth allows multi-hop ad-hoc networks that contain multiple interconnected piconets in a common area to form a scatternet. Routing is one of the technical issues in a scatternet because nodes can arrive and leave at arbitrary times; hence node mobility has a serious impact on network performance. Bluetooth network is built in an ad-hoc fashion, therefore, a fully connected network does not guarantee. Moreover, a partially connected network may not find the shortest route between source and destination. In this paper, a new Self-organizing Location and Mobility-aware Route Optimization (LMRO protocol is proposed for Bluetooth scatternet, which is based on node mobility and location. The proposed protocol considered the shortest route ahead of the source and destination nodes through nodes location information. In addition, proposed protocol guarantees network connectivity through executing Self-organizing procedure for the damaged route by considering signal strength. The proposed LMRO protocol predicts node mobility through the signal strength and activates an alternate link before the main link breaks. Simulation results show that the LMRO protocol has reduced the average hop count by 20%-50% and increased network throughput by 30%-40% compared to existing protocols.
A Cost Assessment of the Dayton Public Schools Vehicle Routing Problem
2009-03-01
A COST ASSESMENT OF THE DAYTON PUBLIC SCHOOLS VEHICLE ROUTING PROBLEM THESIS...PUBLIC SCHOOLS VEHICLE ROUTING PROBLEM THESIS Presented to the Faculty Department of Operational Sciences Graduate School of... VEHICLE ROUTING PROBLEM Frankie L. Woods Jr., BS Captain, USAF Approved: ____________________________________ Dr
Large scale stochastic inventory routing problems with split delivery and service level constraints
Y. Yu (Yugang); C. Chu (Chengbin); H.X. Chen (Haoxun); F. Chu (Feng)
2010-01-01
textabstractA stochastic inventory routing problem (SIRP) is typically the combination of stochastic inventory control problems and NP-hard vehicle routing problems, which determines delivery volumes to the customers that the depot serves in each period, and vehicle routes to deliver the volumes. Th
Large scale stochastic inventory routing problems with split delivery and service level constraints
Y. Yu (Yugang); C. Chu (Chengbin); H.X. Chen (Haoxun); F. Chu (Feng)
2012-01-01
textabstractA stochastic inventory routing problem (SIRP) is typically the combination of stochastic inventory control problems and NP-hard vehicle routing problems, which determines delivery volumes to the customers that the depot serves in each period, and vehicle routes to deliver the volumes. Th
Y. Yu (Yugang); C. Chu (Chengbin); H.X. Chen (Haoxun); F. Chu (Feng)
2010-01-01
textabstractA stochastic inventory routing problem (SIRP) is typically the combination of stochastic inventory control problems and NP-hard vehicle routing problems, for a depot to determine delivery volumes to its customers in each period, and vehicle routes to distribute the delivery volumes. This
Cooperative vehicle routing problem: an opportunity for cost saving
Zibaei, Sedighe; Hafezalkotob, Ashkan; Ghashami, Seyed Sajad
2016-02-01
In this paper, a novel methodology is proposed to solve a cooperative multi-depot vehicle routing problem. We establish a mathematical model for multi-owner VRP in which each owner (i.e. player) manages single or multiple depots. The basic idea consists of offering an option that owners cooperatively manage the VRP to save their costs. We present cooperative game theory techniques for cost saving allocations which are obtained from various coalitions of owners. The methodology is illustrated with a numerical example in which different coalitions of the players are evaluated along with the results of cooperation and cost saving allocation methods.
Considering lost sale in inventory routing problems for perishable goods
DEFF Research Database (Denmark)
Mirzaei, Samira; Seifi, Abbas
2015-01-01
, the average optimality gaps are less than 10.9% and 13.4% using linear and exponential lost sale functions, respectively. Furthermore, we show that the optimality gaps found by CPLEX grow exponentially with the problem size while those obtained by the proposed meta-heuristic algorithm increase linearly....... is considered as lost sale. The proposed model balances the transportation cost, the cost of inventory holding and lost sale. In addition to the usual inventory routing constraints, we consider the cost of lost sale as a linear or an exponential function of the inventory age. The proposed model is solved...
On The Problem of Constructing Routes, Part I: Preface
Directory of Open Access Journals (Sweden)
Gertsbakh Ilya B.
2017-09-01
Full Text Available This is a preface of the translation of the 1967 paper by Linis and Maksim, “On the problem of constructing routes” (in Russian (in the Proceedings of the Institute of Civil Aviation Engineering, Issue 102, pp. 36-45. It marks 50-year to the deficit function (DF model initially developed in this 1967 work; the DF model then paved the way to further research of vehicle-fleet management in terms of optimal routing and scheduling. The merit of this translation is to describe the roots of the DF modelling to enable further studies to emerge with more contributions.
Locating phase transitions in computationally hard problems
Indian Academy of Sciences (India)
B Ashok; T K Patra
2010-09-01
We discuss how phase-transitions may be detected in computationally hard problems in the context of anytime algorithms. Treating the computational time, value and utility functions involved in the search results in analogy with quantities in statistical physics, we indicate how the onset of a computationally hard regime can be detected and the transit to higher quality solutions be quantified by an appropriate response function. The existence of a dynamical critical exponent is shown, enabling one to predict the onset of critical slowing down, rather than finding it after the event, in the specific case of a travelling salesman problem (TSP). This can be used as a means of improving efficiency and speed in searches, and avoiding needless computations.
Location Based Throughput Maximization Routing in Energy Constrained Mobile Ad-hoc Network
Directory of Open Access Journals (Sweden)
V. Sumathy
2006-01-01
Full Text Available In wireless Ad-hoc network, power consumption becomes an important issue due to limited battery power. One of the reasons for energy expenditure in this network is irregularly distributed node pattern, which impose large interference range in certain area. To maximize the lifetime of ad-hoc mobile network, the power consumption rate of each node must be evenly distributed and the over all transmission range of each node must be minimized. Our protocol, Location based throughput maximization routing in energy constrained Ad-hoc network finds routing paths, which maximize the lifetime of individual nodes and minimize the total transmission energy consumption. The life of the entire network is increased and the network throughput is also increased. The reliability of the path is also increased. Location based energy constrained routing finds the distance between the nodes. Based on the distance the transmission power required is calculated and dynamically reduces the total transmission energy.
Capacitated Dynamic Facility Location Problem Based on Tabu Search Algorithm
Institute of Scientific and Technical Information of China (English)
KUANG Yi-jun; ZHU Ke-jun
2007-01-01
Facility location problem is a kind of NP-Hard combinational problem. Considering ever-changing demand sites, demand quantity and releasing cost, we formulate a model combining tabu search and FCM (fuzzy clustering method) to solve the eapacitated dynamic facility location problem. Some results are achieved and they show that the proposed method is effective.
Periodic capacitated arc routing problem applied in a real context
Directory of Open Access Journals (Sweden)
Guilherme Vinicyus Batista
2015-09-01
Full Text Available A good inspection and maintenance planning in railways is essential to ensure the flow of trains and avoid possible accidents. This inspection should be performed periodically by vehicle traveling on rails collecting data and identifying gaps that need to be corrected. The aim of this paper is to present a mathematical model based on binary linear programming, capable of solving this problem, which is a real application of Periodic Capacitated Arc Routing Problem (PCARP. In the PCARP each arc of a network has a demand over a well-defined time horizon and routes must be created for each car so that it covers all the requests in the best way possible without exceeding the vehicles capacity at service. The proposed application has different characteristics to those already proposed in the literature because the vehicle does not need to come back to the depot at the end of the day and the service can be delayed if necessary. The result is satisfactory, covering the demands with a synchronized movement of vehicles.
Hybrid Ant Algorithm and Applications for Vehicle Routing Problem
Xiao, Zhang; Jiang-qing, Wang
Ant colony optimization (ACO) is a metaheuristic method that inspired by the behavior of real ant colonies. ACO has been successfully applied to several combinatorial optimization problems, but it has some short-comings like its slow computing speed and local-convergence. For solving Vehicle Routing Problem, we proposed Hybrid Ant Algorithm (HAA) in order to improve both the performance of the algorithm and the quality of solutions. The proposed algorithm took the advantages of Nearest Neighbor (NN) heuristic and ACO for solving VRP, it also expanded the scope of solution space and improves the global ability of the algorithm through importing mutation operation, combining 2-opt heuristics and adjusting the configuration of parameters dynamically. Computational results indicate that the hybrid ant algorithm can get optimal resolution of VRP effectively.
STRATEGY OF SOLUTION FOR THE INVENTORY ROUTING PROBLEM BASED ON SEPARABLE CROSS DECOMPOSITION
Directory of Open Access Journals (Sweden)
M. Elizondo-Cortés
2005-08-01
Full Text Available The Inventory-Routing Problem (IRP involves a central warehouse, a fleet of trucks wlth finlte capacity, a set of customers, and a known storage capacity. The objective is to determine when to serve each customer, as well as what route each truck should take, with the lowest expense. IRP is a NP-hard problem, this means that searching for solutions can take a very long time. A three-phase strategy is used to solve the problem. This strategy is constructedn by answering the key questions: Which customers should be attended in a planned period? What volume of n products should be delivered to each customer? And, which route should be followed by each truck? The second phase uses Cross Separable Decomposition to solve an Allocation Problem, in order to answer questions two and three, solving a location problem. The result is a very efficient ranking algorithm O(n3 for large cases of the lRP.
An evolutionary algorithm for a real vehicle routing problem
Directory of Open Access Journals (Sweden)
Adamidis, P.
2012-01-01
Full Text Available The NP-hard Vehicle Routing Problem (VRP is central in the optimisation of distribution networks. Its main objective is to determine a set of vehicle trips of minimum total cost. The ideal schedule will efficiently exploit the company's recourses, service all customers and satisfy the given (mainly daily constraints. There have been many attempts to solve this problem with conventional techniques but applied to small-scale simplified problems. This is due to the complexity of the problem and the large volume of data to be processed. Evolutionary Algorithms are search and optimization techniques that are capable of confronting that kind of problems and reach a good feasible solution in a reasonable period of time. In this paper we develop an Evolutionary Algorithm in order to solve the VRP of a specific transportation company in Volos, Greece with different vehicle capacities. The algorithm has been tested with different configurations and constraints, and proved to be effective in reaching a satisfying solution for the company's needs.
Institute of Scientific and Technical Information of China (English)
Bin Jiang; Chao Yang; Takao Terano
2015-01-01
This paper proposes an adaptive agent model with a hybrid routing selection strategy for studying the road⁃network congestion problem. We focus on improving those severely congested links. Firstly, a multi⁃agent system is built, where each agent stands for a vehicle, and it makes its routing selection by considering the shortest path and the minimum congested degree of the target link simultaneously. The agent⁃based model captures the nonlinear feedback between vehicle routing behaviors and road⁃network congestion status. Secondly, a hybrid routing selection strategy is provided, which guides the vehicle routes adapting to the real⁃time road⁃network congestion status. On this basis, we execute simulation experiments and compare the simulation results of network congestion distribution, by Floyd agent with shortest path strategy and our proposed adaptive agent with hybrid strategy. The simulation results show that our proposed model has reduced the congestion degree of those seriously congested links of road⁃network. Finally, we execute our model on a real road map. The results finds that those seriously congested roads have some common features such as located at the road junction or near the unique road connecting two areas. And, the results also show an effectiveness of our model on reduction of those seriously congested links in this actual road network. Such a bottom⁃up congestion control approach with a hybrid congestion optimization perspective will have its significance for actual traffic congestion control.
National Research Council Canada - National Science Library
Hanan Ouhader; Malika El Kyal
2017-01-01
This article investigates the potential economic, environmental, and social effects of combining depot location and vehicle routing decisions in urban road freight transportation under horizontal collaboration...
Wang, Na; Zeng, Jiwen
2017-03-17
Wireless sensor networks are deployed to monitor the surrounding physical environments and they also act as the physical environments of parasitic sensor networks, whose purpose is analyzing the contextual privacy and obtaining valuable information from the original wireless sensor networks. Recently, contextual privacy issues associated with wireless communication in open spaces have not been thoroughly addressed and one of the most important challenges is protecting the source locations of the valuable packages. In this paper, we design an all-direction random routing algorithm (ARR) for source-location protecting against parasitic sensor networks. For each package, the routing process of ARR is divided into three stages, i.e., selecting a proper agent node, delivering the package to the agent node from the source node, and sending it to the final destination from the agent node. In ARR, the agent nodes are randomly chosen in all directions by the source nodes using only local decisions, rather than knowing the whole topology of the networks. ARR can control the distributions of the routing paths in a very flexible way and it can guarantee that the routing paths with the same source and destination are totally different from each other. Therefore, it is extremely difficult for the parasitic sensor nodes to trace the packages back to the source nodes. Simulation results illustrate that ARR perfectly confuses the parasitic nodes and obviously outperforms traditional routing-based schemes in protecting source-location privacy, with a marginal increase in the communication overhead and energy consumption. In addition, ARR also requires much less energy than the cloud-based source-location privacy protection schemes.
Wang, Na; Zeng, Jiwen
2017-01-01
Wireless sensor networks are deployed to monitor the surrounding physical environments and they also act as the physical environments of parasitic sensor networks, whose purpose is analyzing the contextual privacy and obtaining valuable information from the original wireless sensor networks. Recently, contextual privacy issues associated with wireless communication in open spaces have not been thoroughly addressed and one of the most important challenges is protecting the source locations of the valuable packages. In this paper, we design an all-direction random routing algorithm (ARR) for source-location protecting against parasitic sensor networks. For each package, the routing process of ARR is divided into three stages, i.e., selecting a proper agent node, delivering the package to the agent node from the source node, and sending it to the final destination from the agent node. In ARR, the agent nodes are randomly chosen in all directions by the source nodes using only local decisions, rather than knowing the whole topology of the networks. ARR can control the distributions of the routing paths in a very flexible way and it can guarantee that the routing paths with the same source and destination are totally different from each other. Therefore, it is extremely difficult for the parasitic sensor nodes to trace the packages back to the source nodes. Simulation results illustrate that ARR perfectly confuses the parasitic nodes and obviously outperforms traditional routing-based schemes in protecting source-location privacy, with a marginal increase in the communication overhead and energy consumption. In addition, ARR also requires much less energy than the cloud-based source-location privacy protection schemes. PMID:28304367
Variable neighbourhood simulated annealing algorithm for capacitated vehicle routing problems
Xiao, Yiyong; Zhao, Qiuhong; Kaku, Ikou; Mladenovic, Nenad
2014-04-01
This article presents the variable neighbourhood simulated annealing (VNSA) algorithm, a variant of the variable neighbourhood search (VNS) combined with simulated annealing (SA), for efficiently solving capacitated vehicle routing problems (CVRPs). In the new algorithm, the deterministic 'Move or not' criterion of the original VNS algorithm regarding the incumbent replacement is replaced by an SA probability, and the neighbourhood shifting of the original VNS (from near to far by k← k+1) is replaced by a neighbourhood shaking procedure following a specified rule. The geographical neighbourhood structure is introduced in constructing the neighbourhood structures for the CVRP of the string model. The proposed algorithm is tested against 39 well-known benchmark CVRP instances of different scales (small/middle, large, very large). The results show that the VNSA algorithm outperforms most existing algorithms in terms of computational effectiveness and efficiency, showing good performance in solving large and very large CVRPs.
Dry Port Location Problem: A Hybrid Multi-Criteria Approach
Directory of Open Access Journals (Sweden)
BENTALEB Fatimazahra
2016-03-01
Full Text Available Choosing a location for a dry port is a problem which becomes more essential and crucial. This study deals with the problem of locating dry ports. On this matter, a model combining multi-criteria (MACBETH and mono-criteria (BARYCENTER methods to find a solution to dry port location problem has been proposed. In the first phase, a systematic literature review was carried out on dry port location problem and then a methodological classification was presented for this research. In the second phase, a hybrid multi-criteria approach was developed in order to determine the best dry port location taking different criteria into account. A Computational practice and a qualitative analysis from a case study in the Moroccan context have been provided. The results show that the optimal location is very convenient with the geographical region and the government policies.
Driver's workload comparison in waste collection vehicle routing problem
Benjamin, Aida Mauziah; Abdul-Rahman, Syariza
2016-10-01
This paper compares the workload of the drivers for a waste collection benchmark problem. The problem involves ten data sets with different number of customers to be served and different number of disposal facilities available. Previous studies proposed a heuristic algorithm, namely Different Initial Customer (DIC) to solve the problem by constructing initial vehicles routes for the drivers with two main objectives; to minimize the total distance travelled and to minimize the total number of vehicles needed to collect the waste. The results from DIC compared well with other solutions in the literature. However, the balance of the workload among the vehicle drivers is not considered in the solutions. Thus in this paper, we evaluate the quality of the solutions in terms of the total number of customers served by each driver. Then the computational result is compared in terms of the total distance travelled which have been presented in a previous study. Comparison results show that the workload of the drivers are unbalance in terms of these two factors that may cause dissatisfaction among the drivers as well as to the managament.
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.
Group Search Optimizer for the Mobile Location Management Problem
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Dan Wang
2014-01-01
Full Text Available We propose a diversity-guided group search optimizer-based approach for solving the location management problem in mobile computing. The location management problem, which is to find the optimal network configurations of management under the mobile computing environment, is considered here as an optimization problem. The proposed diversity-guided group search optimizer algorithm is realized with the aid of diversity operator, which helps alleviate the premature convergence problem of group search optimizer algorithm, a successful optimization algorithm inspired by the animal behavior. To address the location management problem, diversity-guided group search optimizer algorithm is exploited to optimize network configurations of management by minimizing the sum of location update cost and location paging cost. Experimental results illustrate the effectiveness of the proposed approach.
Group Search Optimizer for the Mobile Location Management Problem
Wang, Dan; Xiong, Congcong; Huang, Wei
2014-01-01
We propose a diversity-guided group search optimizer-based approach for solving the location management problem in mobile computing. The location management problem, which is to find the optimal network configurations of management under the mobile computing environment, is considered here as an optimization problem. The proposed diversity-guided group search optimizer algorithm is realized with the aid of diversity operator, which helps alleviate the premature convergence problem of group search optimizer algorithm, a successful optimization algorithm inspired by the animal behavior. To address the location management problem, diversity-guided group search optimizer algorithm is exploited to optimize network configurations of management by minimizing the sum of location update cost and location paging cost. Experimental results illustrate the effectiveness of the proposed approach. PMID:25180199
Nafezi, Nima
2013-01-01
In this dissertation, we discussed a type of vehicle routing problem called vehicle routing problem with intermediate facilities with consideration of the impact of adding intermediate facilities to the problem. To study how IFs change the result of the problem, we firstly present a simple model based on clustering algorithm along with finding the shortest route between clusters, implementing Clarke and Wright’s algorithm within each cluster. Then we determine a set of design of experiments w...
Damanik, Donna
2016-01-01
Model to choose vehicle route is known as Vehicle Routing Problem (VRP). VRP is related to optimal routing problem that involve more than one vehicle of each capacity to serve costumer’s demand. Capacitated Vehicle Routing Problem is one of VRP form which each of vehicle has finite capacity. Solution in this research use Clarke and Wright’s Savings Algorithm. This algorithm may get a route depand to vehicle capacity and customer’s demand. Data that use in this research is di...
Differential Evolution Algorithm for Route Optimization Problems of Engineering Networks
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O. G. Monahov
2015-01-01
Full Text Available The paper considers problems of structure optimization of engineering networks to provide a minimum total cost of engineering networks in construction and operation. The mathematical statement of the problem in terms of the hyper-network theory takes into account the interdependence of indicators of hyper-network elements, a layout area and a projected network. A digital model of terrain presents the placement area of engineering networks (a territory. In our case, it will be a weighted mesh (graph of primary network of dedicated vertices-consumers and a vertex-source for the utilities. The edges weights will be determined by the costs of construction and operation of the route between the given vertices of the network. The initial solution of the problem of minimizing the total cost will be using the minimum spanning tree, obtained on a weighted complete graph the vertices of which are defined by vertices-consumers and the vertexsource for the utilities, and the weights of edges are the distance between the vertices on the given weighted graph of the primary network. The work offers a method of differential evolution to solve the problem in hyper-network formulation that improves the initial solution by the mapping the edges of the secondary network in the primary network using additional Steiner points. As numerical experiments have shown, a differential evolution algorithm allows us to reduce the average total cost for a given engineering network compared to the initial solution by 5% - 15%, depending on the configuration, parameters, and layout area.
A Mixed Integer Linear Program for Solving a Multiple Route Taxi Scheduling Problem
Montoya, Justin Vincent; Wood, Zachary Paul; Rathinam, Sivakumar; Malik, Waqar Ahmad
2010-01-01
Aircraft movements on taxiways at busy airports often create bottlenecks. This paper introduces a mixed integer linear program to solve a Multiple Route Aircraft Taxi Scheduling Problem. The outputs of the model are in the form of optimal taxi schedules, which include routing decisions for taxiing aircraft. The model extends an existing single route formulation to include routing decisions. An efficient comparison framework compares the multi-route formulation and the single route formulation. The multi-route model is exercised for east side airport surface traffic at Dallas/Fort Worth International Airport to determine if any arrival taxi time savings can be achieved by allowing arrivals to have two taxi routes: a route that crosses an active departure runway and a perimeter route that avoids the crossing. Results indicate that the multi-route formulation yields reduced arrival taxi times over the single route formulation only when a perimeter taxiway is used. In conditions where the departure aircraft are given an optimal and fixed takeoff sequence, accumulative arrival taxi time savings in the multi-route formulation can be as high as 3.6 hours more than the single route formulation. If the departure sequence is not optimal, the multi-route formulation results in less taxi time savings made over the single route formulation, but the average arrival taxi time is significantly decreased.
The p-median Facility Location Problem and Solution Approaches
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Mehmet BASTI
2012-05-01
Full Text Available In today’s globalized and increasingly competitive environment, organizations’ need to implement successful strategies for supply chain management has become indispensable. Transportation costs within the supply chain comprise an important part of the organizations’ expenses. For this reason, the strategic selection of location is an issue that directly affects supply chain performance and costs. At this stage, it becomes very important to apply the latest and the best methods to the facility location problem. The focus of this study is the p-median problem and its solution techniques, one of the location allocation problems aimed at minimizing the costs arising from shipments between facilities and demand points.
An approximation algorithm for the pickup and delivery vehicle routing problem on trees
Katoh, Naoki; Yano, Taihei
2006-01-01
This paper presents an approximation algorithm for a vehicle routing problem on a tree-shaped network with a single depot where there are two types of demands, pickup demand and delivery demand. Customers are located on nodes of the tree, and each customer has a positive demand of pickup and/or delivery. Demands of customers are served by a fleet of identical vehicles with unit capacity. Each vehicle can serve pickup and delivery demands. It is assumed that the demand of a customer is splitta...
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Sanjaya Gajurel
2008-03-01
Full Text Available In this paper we develop a Directional Antenna Multi-path Location Aided Routing (DA-MLAR scheme with On Demand Transmission Power (ODTP support. The routing approach is based on multiple objectives. DAMLAR is a reactive routing protocol that minimizes the protocol overhead of other reactive routing protocols. DAMLAR also improves the packet delivery ratio and end-toend delay. The targeted application contexts include MANET with energy awareness, and communications in space networks, where efficient and reliable packet delivery is very challenging due to the high bit error rate, intermittent connectivity, limited bandwidth, and energy. By using different transmission power based on the calculated distance from the current sender node to the destination node or the next hop node, DA-MLAR-ODTP gets the best of the directional and omni-directional modes. Compared to DA-MLAR, on demand transmission power mode further improves the packet delivery ratio by up to 37% and dwindles end-to-end delay by up to 57% with approximately the same amount of energy consumption. The multiple objective optimization is based on using a Normalized Weighted Additive Utility Function (NWAUF approach that shows comparison of different objective performances with and without on demand transmission power capability. Simulation experiments were conducted. They show that is the developed technique strengthens the reliability of communication systems for given targeted objectives.
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.
Kok, A. Leendert; Meyer, C. Manuel; Kopfer, Herbert; Schutten, J. Marco J.
2009-01-01
In practice, apart from the problem of vehicle routing, schedulers also face the problem of nding feasible driver schedules complying with complex restrictions on drivers' driving and working hours. To address this complex interdependent problem of vehicle routing and break scheduling, we propose a
Kok, A. Leendert; Meyer, C. Manuel; Kopfer, Herbert; Schutten, J. Marco J.
2009-01-01
In practice, apart from the problem of vehicle routing, schedulers also face the problem of finding feasible driver schedules complying with complex restrictions on drivers' driving and working hours. To address this complex interdependent problem of vehicle routing and break scheduling, we propose
A new approach to geographic routing for location aided cluster based MANETs
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Tamilarasi Angamuthu
2011-01-01
Full Text Available Abstract Routing has been the main challenge for ad hoc networks due to dynamic topology as well as resource constraints. Completely GPS(Global Positioning System free as well as GPS scarce positioning systems for wireless, mobile, ad-hoc networks has been proposed recently by many authors. High computational overhead and high mobility of the nodes typically require completely GPS enabled MANETs for higher performance. In this article, Improved Location aided Cluster based Routing Protocol (ILCRP for GPS enabled MANETs has been evaluated for performance metrics such as end to end delay, control overhead, and packet delivery ratio. Use of cluster based routing as well as exact location information of the nodes in ILCRP reduces the control overhead resulting in higher packet delivery ratio. GPS utility in nodes reduces the end to end delay even during its high mobility. Simulations are performed using NS2 by varying the mobility (speed of nodes as well as number of the nodes. The results illustrate that ILCRP performs better compared to other protocols.
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 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...
Parallel Approximation Algorithms for Facility-Location Problems
Blelloch, Guy E.; Tangwongsan, Kanat
2010-01-01
This paper presents the design and analysis of parallel approximation algorithms for facility-location problems, including $\\NC$ and $\\RNC$ algorithms for (metric) facility location, $k$-center, $k$-median, and $k$-means. These problems have received considerable attention during the past decades from the approximation algorithms community, concentrating primarily on improving the approximation guarantees. In this paper, we ask, is it possible to parallelize some of the beautiful results from...
Capacitated vehicle routing problem with sequence-based pallet loading and axle weight constraints
2016-01-01
In this paper, we introduce and study the capacitated vehicle routing problem with sequence-based pallet loading and axle weight constraints. To the best of our knowledge, it is the first time that axle weight restrictions are incorporated in a vehicle routing model. The aim of this paper is to demonstrate that incorporating axle weight restrictions in a vehicle routing model is possible and necessary for a feasible route planning. Axle weight limits impose a great challenge for transportatio...
Multi-trip vehicle routing and scheduling problem with time window in real life
Sze, San-Nah; Chiew, Kang-Leng; Sze, Jeeu-Fong
2012-09-01
This paper studies a manpower scheduling problem with multiple maintenance operations and vehicle routing considerations. Service teams located at a common service centre are required to travel to different customer sites. All customers must be served within given time window, which are known in advance. The scheduling process must take into consideration complex constraints such as a meal break during the team's shift, multiple travelling trips, synchronisation of service teams and working shifts. The main objective of this study is to develop a heuristic that can generate high quality solution in short time for large problem instances. A Two-stage Scheduling Heuristic is developed for different variants of the problem. Empirical results show that the proposed solution performs effectively and efficiently. In addition, our proposed approximation algorithm is very flexible and can be easily adapted to different scheduling environments and operational requirements.
Route Selection Problem Based on Hopfield Neural Network
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N. Kojic
2013-12-01
Full Text Available Transport network is a key factor of economic, social and every other form of development in the region and the state itself. One of the main conditions for transport network development is the construction of new routes. Often, the construction of regional roads is dominant, since the design and construction in urban areas is quite limited. The process of analysis and planning the new roads is a complex process that depends on many factors (the physical characteristics of the terrain, the economic situation, political decisions, environmental impact, etc. and can take several months. These factors directly or indirectly affect the final solution, and in combination with project limitations and requirements, sometimes can be mutually opposed. In this paper, we present one software solution that aims to find Pareto optimal path for preliminary design of the new roadway. The proposed algorithm is based on many different factors (physical and social with the ability of their increase. This solution is implemented using Hopfield's neural network, as a kind of artificial intelligence, which has shown very good results for solving complex optimization problems.
Baron, Danielle M; Ramirez, Alejandro J; Bulitko, Vadim; Madan, Christopher R; Greiner, Ariel; Hurd, Peter L; Spetch, Marcia L
2015-01-01
Visiting multiple locations and returning to the start via the shortest route, referred to as the traveling salesman (or salesperson) problem (TSP), is a valuable skill for both humans and non-humans. In the current study, pigeons were trained with increasing set sizes of up to six goals, with each set size presented in three distinct configurations, until consistency in route selection emerged. After training at each set size, the pigeons were tested with two novel configurations. All pigeons acquired routes that were significantly more efficient (i.e., shorter in length) than expected by chance selection of the goals. On average, the pigeons also selected routes that were more efficient than expected based on a local nearest-neighbor strategy and were as efficient as the average route generated by a crossing-avoidance strategy. Analysis of the routes taken indicated that they conformed to both a nearest-neighbor and a crossing-avoidance strategy significantly more often than expected by chance. Both the time taken to visit all goals and the actual distance traveled decreased from the first to the last trials of training in each set size. On the first trial with novel configurations, average efficiency was higher than chance, but was not higher than expected from a nearest-neighbor or crossing-avoidance strategy. These results indicate that pigeons can learn to select efficient routes on a TSP problem.
Erfani, Seyed Mohammad Hassan; Danesh, Shahnaz; Karrabi, Seyed Mohsen; Shad, Rouzbeh
2017-07-01
One of the major challenges in big cities is planning and implementation of an optimized, integrated solid waste management system. This optimization is crucial if environmental problems are to be prevented and the expenses to be reduced. A solid waste management system consists of many stages including collection, transfer and disposal. In this research, an integrated model was proposed and used to optimize two functional elements of municipal solid waste management (storage and collection systems) in the Ahmadabad neighbourhood located in the City of Mashhad - Iran. The integrated model was performed by modelling and solving the location allocation problem and capacitated vehicle routing problem (CVRP) through Geographic Information Systems (GIS). The results showed that the current collection system is not efficient owing to its incompatibility with the existing urban structure and population distribution. Application of the proposed model could significantly improve the storage and collection system. Based on the results of minimizing facilities analyses, scenarios with 100, 150 and 180 m walking distance were considered to find optimal bin locations for Alamdasht, C-metri and Koohsangi. The total number of daily collection tours was reduced to seven as compared to the eight tours carried out in the current system (12.50% reduction). In addition, the total number of required crews was minimized and reduced by 41.70% (24 crews in the current collection system vs 14 in the system provided by the model). The total collection vehicle routing was also optimized such that the total travelled distances during night and day working shifts was cut back by 53%.
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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.
Solving the Generalized Vehicle Routing Problem with an ACS-based Algorithm
Pop, Petrica Claudiu; Pintea, Camelia; Zelina, Ioana; Dumitrescu, Dan
2009-04-01
Ant colony system is a metaheuristic algorithm inspired by the behavior of real ants and was proposed by Dorigo et al. as a method for solving hard combinatorial optimization problems. In this paper we show its successful application to solving a network design problem: Generalized Vehicle Routing Problem. The Generalized Vehicle Routing Problem (GVRP) is the problem of designing optimal delivery or collection routes, subject to capacity restrictions, from a given depot to a number of predefined, mutually exclusive and exhaustive clusters. Computational results for several benchmark problems are reported.
A localization property for facility location problems with arbitrary norms
DEFF Research Database (Denmark)
Juel, Henrik; Love, Robert F.
1988-01-01
In an earlier article (1983), the authors showed that, for facilities-location problems characterized by generalized distance norms and any even number of existing facilities, the optimal location of the new facility is at the intersection of the lines joining the pairs of facilities if these lines...... intersect at a single point. In this article the authors extend this concept to show that, for a more general class of problems, the optimal location is one of a set of points which is specified by the existing facilities...
A localization property for facility location problems with arbitrary norms
DEFF Research Database (Denmark)
Juel, Henrik; Love, Robert F.
1988-01-01
In an earlier article (1983), the authors showed that, for facilities-location problems characterized by generalized distance norms and any even number of existing facilities, the optimal location of the new facility is at the intersection of the lines joining the pairs of facilities if these lines...... intersect at a single point. In this article the authors extend this concept to show that, for a more general class of problems, the optimal location is one of a set of points which is specified by the existing facilities...
A hybrid nested partitions algorithm for banking facility location problems
Xia, Li
2010-07-01
The facility location problem has been studied in many industries including banking network, chain stores, and wireless network. Maximal covering location problem (MCLP) is a general model for this type of problems. Motivated by a real-world banking facility optimization project, we propose an enhanced MCLP model which captures the important features of this practical problem, namely, varied costs and revenues, multitype facilities, and flexible coverage functions. To solve this practical problem, we apply an existing hybrid nested partitions algorithm to the large-scale situation. We further use heuristic-based extensions to generate feasible solutions more efficiently. In addition, the upper bound of this problem is introduced to study the quality of solutions. Numerical results demonstrate the effectiveness and efficiency of our approach. © 2010 IEEE.
An Efficient Algorithm for Capacitated Multifacility Location Problems
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Chansiri Singhtaun
2007-01-01
Full Text Available In this paper, a squared-Euclidean distance multifacility location problem with inseparable demands under balanced transportation constraints is analyzed. Using calculus to project the problem onto the space of allocation variables, the problem becomes minimizing concave quadratic integer programming problem. The algorithm based on extreme point ranking method combining with logical techniques is developed. The numerical experiments are randomly generated to test efficiency of the proposed algorithm compared with a linearization algorithm. The results show that the proposed algorithm provides a better solution on average with less processing time for all various sizes of problems.
Combining Nearest Neighbor Search with Tabu Search for Large-Scale Vehicle Routing Problem
Du, Lingling; He, Ruhan
The vehicle routing problem is a classical problem in operations research, where the objective is to design least cost routes for a fleet of identical capacitated vehicles to service geographically scattered customers. In this paper, we present a new and effective hybrid metaheuristic algorithm for large-scale vehicle routing problem. The algorithm combines the strengths of the well-known Nearest Neighbor Search and Tabu Search into a two-stage procedure. More precisely, Nearest Neighbor Search is used to construct initial routes in the first stage and the Tabu Search is utilized to optimize the intra-route and the inter-route in the second stage. The presented algorithm is specifically designed for large-scale problems. The computational experiments were carried out on a standard benchmark and a real dataset with 6772 tobacco customers. The results demonstrate that the suggested method is highly competitive.
DEFF Research Database (Denmark)
Larsen, Jesper
2002-01-01
Two ideas for using structural information for solving the Vehicle Routing Problem with Time Windows (VRPTW) is presented. The VRPTW is a generalization of the well known capacity constrained Vehicle Routing Problem (VRP). Both techniques are based on solving the VRPTW using a Branch...
A Branch-and-Price Algorithm for Two Multi-Compartment Vehicle Routing Problems
DEFF Research Database (Denmark)
Mirzaei, Samira; Wøhlk, Sanne
2016-01-01
Despite the vast body of literature on vehicle routing problems, little attention has been paid to multi-compartment vehicle routing problems that investigate transportation of different commodities on the same vehicle, but in different compartments. In this project, we present two strategically...
A branch-and-cut algorithm for the capacitated open vehicle routing problem
DEFF Research Database (Denmark)
Letchford, A.N.; Lysgaard, Jens; Eglese, R.W.
2007-01-01
In open vehicle routing problems, the vehicles are not required to return to the depot after completing service. In this paper, we present the first exact optimization algorithm for the open version of the well-known capacitated vehicle routing problem (CVRP). The algorithm is based on branch-and...
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.
A Hybrid TCNN Optimization Approach for the Capacity Vehicle Routing Problem
Institute of Scientific and Technical Information of China (English)
无
2006-01-01
A novel approximation algorithm was proposed for the problem of finding the minimum total cost of all routes in Capacity Vehicle Routing Problem (CVRP). CVRP can be partitioned into three parts: the selection of vehicles among the available vehicles, the initial routing of the selected fleet and the routing optimization. Fuzzy Cmeans (FCM) can group the customers with close Euclidean distance into the same vehicle according to the principle of similar feature partition. Transiently chaotic neural network (TCNN) combines local search and global search, possessing high search efficiency. It will solve the routes to near optimality. A simple tabu search (TS)procedure can improve the routes to more optimality. The computations on benchmark problems and comparisons with other results in literatures show that the proposed algorithm is a viable and effective approach for CVRP.
A branch-and-cut-and-price algorithm for the cumulative capacitated vehicle routing problem
DEFF Research Database (Denmark)
Wøhlk, Sanne; Lysgaard, Jens
2014-01-01
The paper considers the Cumulative Capacitated Vehicle Routing Problem (CCVRP), which is a variation of the well-known Capacitated Vehicle Routing Problem (CVRP). In this problem, the traditional objective of minimizing total distance or time traveled by the vehicles is replaced by minimizing the...... the sum of arrival times at the customers. A branch-and-cut-and-price algorithm for obtaining optimal solutions to the problem is proposed. Computational results based on a set of standard CVRP benchmarks are presented....
A Library of Local Search Heuristics for the Vehicle Routing Problem
Energy Technology Data Exchange (ETDEWEB)
Groer, Christopher S [ORNL; Golden, Bruce [University of Maryland; Edward, Wasil [American University
2010-01-01
The vehicle routing problem (VRP) is a difficult and well-studied combinatorial optimization problem. Real-world instances of the VRP can contain hundreds and even thousands of customer locations and can involve many complicating constraints, necessitating the use of heuristic methods. We present a software library of local search heuristics that allow one to quickly generate good solutions to VRP instances. The code has a logical, object-oriented design and uses efficient data structures to store and modify solutions. The core of the library is the implementation of seven local search operators that share a similar interface and are designed to be extended to handle additional options with minimal code change. The code is well-documented, is straightforward to compile, and is freely available for download at http://sites.google.com/site/vrphlibrary/ . The distribution of the code contains several applications that can be used to generate solutions to instances of the capacitated VRP.
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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.
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Masoud Rabbani
2013-09-01
Full Text Available Integration of various logistical components in supply chain management, such as transportation, inventory control and facility location are becoming common practice to avoid sub-optimization in nowadays’ competitive environment. The integration of transportation and inventory decisions is known as inventory routing problem (IRP in the literature. The problem aims to determine the delivery quantity for each customer and the network routes to be used in each period, so that the total inventory and transportation costs are to be minimized. On the contrary of conventional IRP that each retailer can only provide its demand from the supplier, in this paper, a new multi-period, multi-item IRP model with considering lateral trans-shipment, back-log and financial decisions is proposed as a business model in a distinct organization. The main purpose of this paper is applying an applicable inventory routing model with considering real world setting and solving it with an appropriate method.
Goal-programming model of the stochastic vehicle-routing problem
Energy Technology Data Exchange (ETDEWEB)
Zare-Mehrjerdi, Y.
1986-01-01
This research proposes a Goal Programming (GP) model of the Stochastic Vehicle Routing Problem (SVRP). The SVRP examined considers the multiple-vehicle, single-depot-node routing problem in which customer demand and travel and unload times are random variables having known distribution functions. The problem formulation of the SVRP is divided into two major stages which are referred to as Route Construction Stage (RCS) and Route Improvement Stage (RIS). The RCS of the SVRP is required in order to partition a set of stations into feasible sets of routes, one for each vehicle, using an appropriate heuristic approach. The RIS of the problem is required in order to sequence the stations on each vehicle route to meet the customer's and decision maker's requirements by applying a GP method. Two problems discuss the GP formulation of the RIS, which is used for improving the arrangement of stations on each vehicle route based on the customer's and decision maker's criteria. The formulation of the RCS of the problem is divided into two sections according to the type of criteria that is to be minimized. A substantial improvement in the results of the SVRP can be obtained by integrating the customer's and decision maker's requirements with the SVRP in order to determine the final arrangement of stations for each vehicle route.
A Problem-Reduction Evolutionary Algorithm for Solving the Capacitated Vehicle Routing Problem
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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.
Logistics distribution centers location problem and algorithm under fuzzy environment
Yang, Lixing; Ji, Xiaoyu; Gao, Ziyou; Li, Keping
2007-11-01
Distribution centers location problem is concerned with how to select distribution centers from the potential set so that the total relevant cost is minimized. This paper mainly investigates this problem under fuzzy environment. Consequentially, chance-constrained programming model for the problem is designed and some properties of the model are investigated. Tabu search algorithm, genetic algorithm and fuzzy simulation algorithm are integrated to seek the approximate best solution of the model. A numerical example is also given to show the application of the algorithm.
The solution of location problems with certain existing facility structures
DEFF Research Database (Denmark)
Juel, Henrik; Love, Robert F.
1983-01-01
It is known that in the Euclidean distance case, the optimal minisum location of a new facility in relation to four existing facilities is at the intersection of the two lines joining two pairs of the facilities. The authors extend this concept to minisum problems having any even number of existi...
Properties and solution methods for large location-allocation problems
DEFF Research Database (Denmark)
Juel, Henrik; Love, Robert F.
1982-01-01
Location-allocation with l$ _p$ distances is studied. It is shown that this structure can be expressed as a concave minimization programming problem. Since concave minimization algorithms are not yet well developed, five solution methods are developed which utilize the special properties of the l...
The solution of location problems with certain existing facility structures
DEFF Research Database (Denmark)
Juel, Henrik; Love, Robert F.
1983-01-01
It is known that in the Euclidean distance case, the optimal minisum location of a new facility in relation to four existing facilities is at the intersection of the two lines joining two pairs of the facilities. The authors extend this concept to minisum problems having any even number of existing...... facilities and characterized by generalized distance norms...
Fault-tolerant Concave Facility Location Problem with Uniform Requirements
Institute of Scientific and Technical Information of China (English)
Xing WANG; Da-Chuan XU; Zheng-Hai HUANG
2012-01-01
In this paper,we consider the fault-tolerant concave facility location problem (FTCFL) with uniform requirements. By investigating the structure of the FTCFL,we obtain a modified dual-fitting bifactor approximation algorithm.Combining the scaling and greedy argumentation technique,the approximation factor is proved to be 1.52.
On Nash equilibria of a competitive location problem
Sáiz, M.E.; Hendrix, E.M.T.; Pelegrín, B.
2011-01-01
The location-quality decision of a facility for two competing suppliers in a new market is described by a Huff-like attraction model where the profit that can be reached by each supplier depends on the actions of its competitor. We study the profit maximization problem of the suppliers under binary
Problems in the Information Dissemination of the Internet Routing
Institute of Scientific and Technical Information of China (English)
ZHAO YiXin(赵邑新); YIN Xia(尹霞); WU JianPing(吴建平)
2003-01-01
Internet routing is achieved by a set of nodes running distributed algorithms -routing protocols. However, many nodes are resistless to wrong messages or improper operations,unable to detect or correct them. Thus a wrong message or an improper operation can easilysweep almost the whole Internet. Such a fragile Internet routing comes from the features of thesealgorithms and protocols. Besides, the strategies taken by the network equipment manufacturersand administrators also are of important influence. When determining the options or selectionsin the implementation/operation, they always pay more attention to the expense of a single nodeor a single area and make some simplifications in implementations and configurations while caringless about the influence on the whole network. This paper tries to illustrate such a scheme is notreasonable at all and suggests the consideration from the view of the overall optimization. Fromthree typical cases involved in the Internet routing, a general model is abstracted, which makes theresults signiflcative for more Internet related aspects. This paper evaluates the complexity of thetheoretical analysis, then acquires the effect of error information on the whole network through thesimulation on the Internet topology. It is shown that even very little error information can incursevere impact on the Internet. And it will take much more efforts of downstream nodes to makeremedies. This result is intuitively revealed through the comparisons in the charts and the visualpresentations. Then a hierarchical solution to establish the upgrade plan is given, which helps toupgrade the nodes of the network in a most efficient and economical way.
A Learning Automata Based Algorithm For Solving Capacitated Vehicle Routing Problem
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Mir Mohammad Alipour
2012-03-01
Full Text Available This paper presents an approximate algorithm based on distributed learning automata for solving capacitated vehicle routing problem. The vehicle routing problem (VRP is an NP-hard problem and capacitated vehicle routing problem variant (CVRP is considered here. This problem is one of the NP-hard problems and for this reason many approximate algorithms have been designed for solving it. Distributed learning automata that is a general searching tool and is a solving tool for variety of NP-complete problems, is used to solve this problem and tested on fourteen benchmark problems. Our results were compared to the best known results. The results of comparison have shown the efficiency of the proposed algorithm.
Congestion Service Facilities Location Problem with Promise of Response Time
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Dandan Hu
2013-01-01
Full Text Available In many services, promise of specific response time is advertised as a commitment by the service providers for the customer satisfaction. Congestion on service facilities could delay the delivery of the services and hurts the overall satisfaction. In this paper, congestion service facilities location problem with promise of response time is studied, and a mixed integer nonlinear programming model is presented with budget constrained. The facilities are modeled as M/M/c queues. The decision variables of the model are the locations of the service facilities and the number of servers at each facility. The objective function is to maximize the demands served within specific response time promised by the service provider. To solve this problem, we propose an algorithm that combines greedy and genetic algorithms. In order to verify the proposed algorithm, a lot of computational experiments are tested. And the results demonstrate that response time has a significant impact on location decision.
Sarwono, A. A.; Ai, T. J.; Wigati, S. S.
2017-01-01
Vehicle Routing Problem (VRP) is a method for determining the optimal route of vehicles in order to serve customers starting from depot. Combination of the two most important problems in distribution logistics, which is called the two dimensional loading vehicle routing problem, is considered in this paper. This problem combines the loading of the freight into the vehicles and the successive routing of the vehicles along the route. Moreover, an additional feature of last-in-first-out loading sequencesis also considered. In the sequential two dimensional loading capacitated vehicle routing problem (sequential 2L-CVRP), the loading must be compatible with the trip sequence: when the vehicle arrives at a customer i, there must be no obstacle (items for other customers) between the item of i and the loading door (rear part) of the vehicle. In other words, it is not necessary to move non-i’s items whenever the unloading process of the items of i. According with aforementioned conditions, a program to solve sequential 2L-CVRP is required. A nearest neighbor algorithm for solving the routing problem is presented, in which the loading component of the problem is solved through a collection of 5 packing heuristics.
Layered Formulation for the Robust Vehicle Routing Problem with Time Windows
2012-01-01
International audience; This paper studies the vehicle routing problem with time windows where travel times are uncertain and belong to a predetermined polytope. The objective of the problem is to find a set of routes that services all nodes of the graph and that are feasible for all values of the travel times in the uncertainty polytope. The problem is motivated by maritime transportation where delays are frequent and must be taken into account. We present an extended formulation for the veh...
An Adaptable Variable Neighborhood Search for the Vehicle Routing Problem with Order Outsourcing
2014-01-01
In practice, many package transportation companies lower their costs by hiring outside carriers to serve orders that cannot be served efficiently by their own trucks. The problem which takes the order outsource option into account is the Vehicle Routing Problem with Private Fleet and Common Carrier. In this variant of the Vehicle Routing Problem, orders are either delivered by an outside carrier, the common carrier, which receives an order specific price for this or by the own fleet, the priv...
Solving the vehicle routing problem by a hybrid meta-heuristic algorithm
Yousefikhoshbakht, Majid; Khorram, Esmaile
2012-01-01
The vehicle routing problem (VRP) is one of the most important combinational optimization problems that has nowadays received much attention because of its real application in industrial and service problems. The VRP involves routing a fleet of vehicles, each of them visiting a set of nodes such that every node is visited by exactly one vehicle only once. So, the objective is to minimize the total distance traveled by all the vehicles. This paper presents a hybrid two-phase algorithm called s...
Distributed and Location-Based Multicast Routing Algorithms for Wireless Sensor Networks
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Hakki Bagci
2009-01-01
Full Text Available Multicast routing protocols in wireless sensor networks are required for sending the same message to multiple different destinations. In this paper, we propose two different distributed algorithms for multicast routing in wireless sensor networks which make use of location information of sensor nodes. Our first algorithm groups the destination nodes according to their angular positions and forwards the multicast message toward each group in order to reduce the number of total branches in multicast tree which also reduces the number of messages transmitted. Our second algorithm calculates an Euclidean minimum spanning tree at the source node by using the positions of the destination nodes. The multicast message is forwarded to destination nodes according to the calculated MST. This helps in reducing the total energy consumed for delivering the message to all destinations by decreasing the number of total transmissions. Evaluation results show that the algorithms we propose are scalable and energy efficient, so they are good candidates to be used for multicasting in wireless sensor networks.
Noniterative Solution of Some Fermat-Weber Location Problems
Directory of Open Access Journals (Sweden)
Reuven Chen
2011-01-01
Full Text Available The Fermat-Weber problem of optimally locating a service facility in the Euclidean continuous two-dimensional space is usually solved by the iterative process first suggested by Weiszfeld or by later versions thereof. The methods are usually rather efficient, but exceptional problems are described in the literature in which the iterative solution is exceedingly long. These problems are such that the solution either coincides with one of the demand points or nearly coincides with it. We describe a noniterative direct alternative, based on the insight that the gradient components of the individual demand points can be considered as pooling forces with respect to the solution point. It is demonstrated that symmetrical problems can thus be optimally solved with no iterations, in analogy to finding the equilibrium point in statics. These include a well-known ill-conditioned problem and its variants, which can now be easily solved to optimality using geometrical considerations.
Tabu Search Algorithm to Solve the Intermodal Terminal Location Problem
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E. Karimi∗
2015-03-01
Full Text Available Establishment of appropriate terminals is effective as the main gate entrance to international, national and local transportation network for economic performance, traffic safety and reduction of environmental pollution. This paper focuses on intermodal terminal location problem. The main objective of this problem is to determine which of the terminals of a set of candidate terminals should be opened such that the total cost be minimized. In this problem, demands of customers will ship directly (without the use of terminals between the origin and destination of customers, or intermodaly (by using two terminals or even by combination of both methods. Since this problem is NP-hard, metaheuristics algorithms such as tabu search (TS is used to solve it. The algorithm is compared with greedy randomized adaptive search procedure (GRASP on instance of this problem. Results show the efficiency of TS in comparision with GRASP.
LOPP: A Location Privacy Protected Anonymous Routing Protocol for Disruption Tolerant Network
Lu, Xiaofeng; Hui, Pan; Towsley, Don; Pu, Juhua; Xiong, Zhang
In this paper, we propose an anonymous routing protocol, LOPP, to protect the originator's location privacy in Delay/Disruption Tolerant Network (DTN). The goals of our study are to minimize the originator's probability of being localized (Pl) and maximize the destination's probability of receiving the message (Pr). The idea of LOPP is to divide a sensitive message into k segments and send each of them to n different neighbors. Although message fragmentation could reduce the destination's probability to receive a complete message, LOPP can decrease the originator's Pl. We validate LOPP on a real-world human mobility dataset. The simulation results show that LOPP can decrease the originator's Pl by over 54% with only 5.7% decrease in destination's Pr. We address the physical localization issue of DTN, which was not studied in the literature.
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
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 In-Transit Vigilant Covering Tour Problem of Routing Unmanned Ground Vehicles
2012-08-01
15 Figure 2. A classic VRP ...17 Figure 3. Solution for a VRP ........................................................................................18 Figure 4. Solution...of NP-hard problems, such as the Traveling Salesman Problem (TSP), Vehicle Routing Problem ( VRP ), and Covering Salesman Problem (CSP) etc. We will
DEFF Research Database (Denmark)
Cetin, Bilge Kartal; Prasad, Neeli R.; Prasad, Ramjee
2011-01-01
of the maximum lifetime routing problem that considers the operation modes of the node. Solution of the linear programming gives the upper analytical bound for the network lifetime. In order to illustrate teh application of the optimization model, we solved teh problem for different parameter settings...... protocols, and the energy model for transmission. In this paper, we tackle the routing challenge for maximum lifetime of the sensor network. We introduce a novel linear programming approach to the maximum lifetime routing problem. To the best of our knowledge, this is the first mathematical programming...
The Linehaul-Feeder Vehicle Routing Problem with Virtual Depots and Time Windows
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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.
A Cluster Based Scatter Search Heuristic for the Vehicle Routing Problem
Wendolsky, Rolf; Scheuerer, Stephan
2006-01-01
The Vehicle Routing Problem (VRP) is one of the most studied problems in the field of Operations Research. Closely related to the VRP is the Capacitated Clustering Problem (CCP). The VRP can be considered as an 'extension' of the CCP in the way that for each cluster in the CCP solution, additionally a route through all cluster customers and the depot has to be constructed to generate the routing information. In a previous study the Scatter Search methodology was used to solve the CCP. This al...
Hybrid discrete particle swarm optimization algorithm for capacitated vehicle routing problem
Institute of Scientific and Technical Information of China (English)
无
2006-01-01
Capacitated vehicle routing problem (CVRP) is an NP-hard problem. For large-scale problems, it is quite difficult to achieve an optimal solution with traditional optimization methods due to the high computational complexity. A new hybrid approximation algorithm is developed in this work to solve the problem. In the hybrid algorithm, discrete particle swarm optimization (DPSO) combines global search and local search to search for the optimal results and simulated annealing (SA) uses certain probability to avoid being trapped in a local optimum. The computational study showed that the proposed algorithm is a feasible and effective approach for capacitated vehicle routing problem, especially for large scale problems.
SURVEI PENANGANAN BROADCAST STORM PROBLEM PADA PROTOKOL ROUTING AODV DI MANET
Directory of Open Access Journals (Sweden)
Indera Zainul Muttaqien
2015-07-01
Full Text Available Komunikasi multi-hop pada lingkungan MANET dapat melibatkan broadcast paket dalam proses route discovery. Protokol routing pada MANET akan melakukan broadcast paket RREQ dan menjalarkannya ke node tujuan secepat dan seefisien mungkin, dimana paket RREQ dari rute yang optimal adalah paket RREQ yang terlebih dahulu sampai ke tujuan. Aktifitas broadcast yang tidak terkontrol dapat menyebabkan suatu kondisi yang disebut broadcast storm problem. Broadcast storm problem dapat berdampak pada terganggunya kinerja dari protokol routing akibat adanya packet redundancy, contention, dan collision. Broadcast storm problem dapat ditangani dengan membatasi jumlah node yang dapat melakukan broadcast. Tujuan utama dari pembuatan makalah ini adalah merangkum beberapa mekanisme terbaru yang telah diakukan oleh para peneliti untuk menangani broadcast storm problem. Kami juga menyajikan perbandingan dari mekanisme tersebut berdasarkan karakteristik dari mekanisme ditinjau dari kesesuaian dengan beberapa skema penanganan broadcast storm problem yang diajukan oleh peneliti sebelumnya, kebutuhan informasi tertentu antar node, lingkungan uji coba dan apakah mekanisme ini dapat diterapkan pada protokol routing lainnya.
Optimization of Capacitated Vehicle Routing Problem by Nested Particle Swarm Optimization
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Karuppusamy Kanthavel
2011-01-01
Full Text Available Problem statement: Vehicle routing problem determines the optimum route for each vehicle as a sequence of visiting cities. The problem has been defined as NP-hard and exact solution is relatively difficult to achieve for real time large scale models. Though several attempts to solve the problem were made in the literature, new approaches may be tried to solve the problem to further reduce computational efforts. Approach: In this context this study focuses on maximum utilization of loading capacity and determines the optimum set of vehicle routes for Capacitated Vehicle Routing Problem (CVRP by a Nested Particle Swarm Optimization (NPSO technique. The algorithm is implemented as Master PSO and slave PSO for the identification of candidate list and route sequence in nested form to optimize the model. Results: Benchmarking data set of capacitated vehicle routing is considered for the evaluations. The total distance of set vehicle route obtained by the new approach is compared with the best known solution and other existing techniques. Conclusions/Recommendations: The NPSO produces significant results and computational performance than the existing PSO algorithms. This newly proposed NPSO algorithm develops the vehicle schedule without any local optimization technique.
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...
A savings based method for real-life vehicle routing problems
A. Poot; G. Kant; A.P.M. Wagelmans (Albert)
1999-01-01
textabstractThis paper describes a Savings Based algorithm for the Extended Vehicle Routing Problem. This algorithm is compared with a Sequential Insertion algorithm on real-life data. Besides the traditional quality measures such as total distance traveled and total workload, we compare the routing
The vehicle routing problem with time windows: State-of-the-art exact solution methods
DEFF Research Database (Denmark)
Desaulniers, Guy; Desrosiers, Jacques; Spoorendonk, Simon
2011-01-01
The vehicle routing problem with time windows (VRPTW) consists of finding least-cost vehicle routes to service given customers exactly once each while satisfying the vehicle capacity and customer time windows. The VRPTW has been widely studied. We present here a short survey on the successful exact...
Exact methods for time constrained routing and related scheduling problems
DEFF Research Database (Denmark)
Kohl, Niklas
1995-01-01
real difference is how the coordinating master problem - a concave non-differentiable maximization problem - is solved. We show how the constrained shortest path problem can be solved efficiently, and present a number of different strategies for solving the master problem. The lower bound obtainable...
Uncapacitated facility location problem with self-serving demands
Directory of Open Access Journals (Sweden)
E Monabbati
2013-12-01
Full Text Available In classical uncapacitated facility location problems (UFLP the goal is to satisfy requirements of some demand points by setting up some servers, among potential facility locations, such that the total cost including service costs and fixed costs are minimized. In this paper a generalization of UFLP is considered in which some demand points, called self-serving, could be served exclusively by a new server at that point. Numerical experiments show that near optimal solutions are achieved by the proposed method.
Two-Phase Heuristic for the Vehicle Routing Problem with Time Windows
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Sándor Csiszár
2007-08-01
Full Text Available The subject of the paper is a complete solution for the vehicle routing problemwith time windows, an industrial realization of an NP hard combinatorial optimizationproblem. The primary objective –the minimization of the number of routes- is aimed in thefirst phase, the secondary objective –the travel distance minimization- is going to berealized in the second phase by tabu search. The initial route construction applies aprobability density function for seed selection. Guided Route Elimination procedure wasalso developed. The solution was tested on the Solomon Problem Set and seems to be verycompeitive with the best heuristics published in the latest years (2003-2005.
Directory of Open Access Journals (Sweden)
V.PURUSHOTHAM REDDY
2011-02-01
Full Text Available In computer networks the routing is based on shortest path routing algorithms. Based on its advantages, an alternative method is used known as Genetic Algorithm based routing algorithm, which is highly scalable and insensitive to variations in network topology. Here we propose a coarse-grained parallel genetic algorithm to solve the shortest path routing problem with the primary goal of computation time reduction along with the use of migration scheme. This algorithm is developed and implemented on an MPI cluster. The effects of migration and its performance is studied in this paper.
The storage location assignment problem: application in an agribusiness company
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Helton C. Gomes
2015-09-01
Full Text Available The goal of this work is propose an efficient storage scheme for a company in the agribusiness sector. The company studied herein is located in the Alto Paranaíba region of Minas Gerais, and exports coffee beans. Efficient storage can provide improvements in the use of space, operational resources, and staff time, as well as facilitating the order picking process. To accomplish this, the problem was mathematically modeled as a Storage Location Assignment Problem (SLAP, aimed at minimizing handling costs and maximizing space utilization and storage efficiency. The mathematical model using the company data was solved using the CPLEX solver, version 12.1. The results obtained were compared with the actual company scenario, and several advantages were observed.
A branch-and-cut algorithm for the vehicle routing problem with multiple use of vehicles
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İsmail Karaoğlan
2015-06-01
Full Text Available This paper addresses the vehicle routing problem with multiple use of vehicles (VRPMUV, an important variant of the classic vehicle routing problem (VRP. Unlike the classical VRP, vehicles are allowed to use more than one route in the VRPMUV. We propose a branch-and-cut algorithm for solving the VRPMUV. The proposed algorithm includes several valid inequalities from the literature for the purpose of improving its lower bounds, and a heuristic algorithm based on simulated annealing and a mixed integer programming-based intensification procedure for obtaining the upper bounds. The algorithm is evaluated in terms of the test problems derived from the literature. The computational results which follow show that, if there were 120 customers on the route (in the simulation, the problem would be solved optimally in a reasonable amount of time.
Developing a chaotic pattern of dynamic Hazmat routing problem
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Abbas Mahmoudabadi
2014-03-01
Full Text Available The present paper proposes an iterative procedure based on chaos theory on dynamic risk definition to determine the best route for transporting hazardous materials (Hazmat. In the case of possible natural disasters, the safety of roads may be seriously affected. So the main objective of this paper is to simultaneously improve the travel time and risk to satisfy the local and national authorities in the transportation network. Based on the proposed procedure, four important risk components including accident information, population, environment, and infrastructure aspects have been presented under linguistic variables. Furthermore, the extent analysis method was utilized to convert them to crisp values. To apply the proposed procedure, a road network that consists of fifty nine nodes and eighty two-way edges with a pre-specified affected area has been considered. The results indicate that applying the dynamic risk is more appropriate than having a constant risk. The application of the proposed model indicates that, while chaotic variables depend on the initial conditions, the most frequent path will remain independent. The points that would help authorities to come to the better decision when they are dealing with Hazmat transportation route selection.
Adaptive search techniques for problems in vehicle routing, part II: A numerical comparison
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Kritzinger Stefanie
2015-01-01
Full Text Available Research in the field of vehicle routing often focused on finding new ideas and concepts in the development of fast and efficient algorithms for an improved solution process. Early studies introduce static tailor-made strategies, but trends show that algorithms with generic adaptive policies - which emerged in the past years - are more efficient to solve complex vehicle routing problems. In this first part of the survey, we present an overview of recent literature dealing with adaptive or guided search techniques for problems in vehicle routing.
Adaptive search techniques for problems in vehicle routing, part I: A survey
Directory of Open Access Journals (Sweden)
Kritzinger Stefanie
2015-01-01
Full Text Available Research in the field of vehicle routing often focused on finding new ideas and concepts in the development of fast and efficient algorithms for an improved solution process. Early studies introduce static tailor-made strategies, but trends show that algorithms with generic adaptive policies - which emerged in the past years - are more efficient to solve complex vehicle routing problems. In this first part of the survey, we present an overview of recent literature dealing with adaptive or guided search techniques for problems in vehicle routing.
A heterogeneous fleet vehicle routing model for solving the LPG distribution problem: A case study
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.
A Branch-and-Price Algorithm for the Capacitated Arc Routing Problem with Stochastic Demands
DEFF Research Database (Denmark)
Christiansen, Christian Holk; Lysgaard, Jens; Wøhlk, Sanne
2009-01-01
We address the Capacitated Arc Routing Problem with Stochastic Demands (CARPSD), which we formulate as a Set Partitioning Problem. The CARPSD is solved by a Branch-and-Price algorithm, which we apply without graph transformation. The demand's stochastic nature is incorporated into the pricing...... problem. Computational results are reported....
Refinements of the column generation process for the Vehicle Routing Problem with Time Windows
DEFF Research Database (Denmark)
Larsen, Jesper
2004-01-01
The Vehicle Routing Problem with Time Windows is a generalization of the well known capacity constrained Vehicle Routing Problem. A homogeneous fleet of vehicles has to service a set of the customers and fulfill their demands. The service of the customers can only start within a well-defined time...... 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...
Lower and Upper Bounds for the Node, Edge, and Arc Routing Problem
DEFF Research Database (Denmark)
Bach, Lukas; Wøhlk, Sanne; Hasle, Geir
The Node, Edge, and Arc Routing Problem (NEARP) was defined by Prins and Bouchenoua in 2004. They also proposed a memetic algorithm procedure and defined a set of test instances: the so-called CBMix benchmark. The NEARP generalizes the classical CVRP, the CARP, and the General Routing Problem....... It captures important aspects of real-life routing problems that were not adequately modeled in previous VRP variants. Hence, its definition and investigation contribute to the development of rich VRPs. In this paper we present the first lower bound 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 the CBMix benchmark. The first is based on well-known CARP instances; the second consists of real life cases of newspaper delivery routing. We provide numerical results in the form 1 of lower and best known upper bounds for all...
REFINEMENTS OF THE COLUMN GENERATION PROCESS FOR THE VEHICLE ROUTING PROBLEM WITH TIME WINDOWS
Institute of Scientific and Technical Information of China (English)
Jesper LARSEN
2004-01-01
The Vehicle Routing Problem with Time Windows is a generalization of the well known capacity constrained Vehicle Routing Problem. A homogeneous fleet of vehicles has to service a set of customers. The service of the customers can only start within a well-defined time interval denoted the time window. The objective is to determine routes for the vehicles that minimizes the accumulated cost (or distance). 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 run-time refinements when speeding up an exact approach without compromising optimality.
2016-01-01
The multi Vehicle Routing Problem with Pickup and Delivery with Time Windows is a challenging version of the Vehicle Routing Problem. In this paper, by embedding many complex assignment routing constraints through constructing a multi dimensional network, we intend to reach optimality for local clusters derived from a reasonably large set of passengers on real world transportation networks. More specifically, we introduce a multi vehicle state space time network representation in which only t...
APPLYING AN INTEGRATED ROUTE OPTIMIZATION METHOD AS A SOLUTION TO THE PROBLEM OF WASTE COLLECTION
Directory of Open Access Journals (Sweden)
A. H. Salleh
2016-09-01
Full Text Available Solid waste management (SWM is very subjective to budget control where the utmost expenses are devoted to the waste collection’s travel route. The common understanding of the travel route in SWM is that shorter route is cheaper. However, in reality it is not necessarily true as the SWM compactor truck is affected by various aspects which leads to higher fuel consumption. Thus, this ongoing research introduces a solution to the problem using multiple criteria route optimization process integrated with AHP/GIS as its main analysis tools. With the criteria obtained from the idea that leads to higher fuel consumption based on road factors, road networks and human factors. The weightage of criteria is obtained from the combination of AHP with the distance of multiple shortest routes obtained from GIS. A solution of most optimum routes is achievable and comparative analysis with the currently used route by the SWM compactor truck can be compared. It is expected that the decision model will be able to solve the global and local travel route problem in MSW.
Applying AN Integrated Route Optimization Method as a Solution to the Problem of Waste Collection
Salleh, A. H.; Ahamad, M. S. S.; Yusoff, M. S.
2016-09-01
Solid waste management (SWM) is very subjective to budget control where the utmost expenses are devoted to the waste collection's travel route. The common understanding of the travel route in SWM is that shorter route is cheaper. However, in reality it is not necessarily true as the SWM compactor truck is affected by various aspects which leads to higher fuel consumption. Thus, this ongoing research introduces a solution to the problem using multiple criteria route optimization process integrated with AHP/GIS as its main analysis tools. With the criteria obtained from the idea that leads to higher fuel consumption based on road factors, road networks and human factors. The weightage of criteria is obtained from the combination of AHP with the distance of multiple shortest routes obtained from GIS. A solution of most optimum routes is achievable and comparative analysis with the currently used route by the SWM compactor truck can be compared. It is expected that the decision model will be able to solve the global and local travel route problem in MSW.
On the vehicle routing problem with time windows
DEFF Research Database (Denmark)
Kallehauge, Brian
2006-01-01
generation. We have solved two test problems introduced in 2001 by Gehring and Homberger with 400 and 1000 customers 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...... inequalities are facet defining under certain assumptions. We also introduce precedence constraints in the context of the VRPTW. Computational experiments are performed with a branch-and-cut algorithm on the Solomon test problems with wide time windows. Based on results on 25-node problems the outcome...... is that the algorithmshows promising results compared to leading algorithms in the literature. In particularwe report a solution to a previously unsolved 50-node Solomon test problem R208. The conclusion is therefore that the path formulation of the VRPTW is no longer the unchallenged winning strategy for solving the VRPTW...
Genetic Algorithm and Tabu Search for Vehicle Routing Problems with Stochastic Demand
Ismail, Zuhaimy; Irhamah
2010-11-01
This paper presents a problem of designing solid waste collection routes, involving scheduling of vehicles where each vehicle begins at the depot, visits customers and ends at the depot. It is modeled as a Vehicle Routing Problem with Stochastic Demands (VRPSD). A data set from a real world problem (a case) is used in this research. We developed Genetic Algorithm (GA) and Tabu Search (TS) procedure and these has produced the best possible result. The problem data are inspired by real case of VRPSD in waste collection. Results from the experiment show the advantages of the proposed algorithm that are its robustness and better solution qualities.
Route of cocaine administration: patterns of use and problems among a Brazilian sample.
Ferri, C P; Gossop, M
1999-01-01
Route of administration has important implications for the understanding of drug addiction and related-problems. This cross-sectional study investigates patterns of consumption and cocaine-related problems among snorting and crack cocaine users in São Paulo and outlines changes in route of cocaine administration in Brazil between 1980-1997. Crack cocaine users had more social and health problems and higher involvement in crime than intranasal users. These problems, compounded by the larger doses being used and their greater involvement in prostitution, place crack cocaine users at higher risk from HIV infection and other sexually transmitted diseases as well as other physical risks.
The integrated model for solving the single-period deterministic inventory routing problem
Rahim, Mohd Kamarul Irwan Abdul; Abidin, Rahimi; Iteng, Rosman; Lamsali, Hendrik
2016-08-01
This paper discusses the problem of efficiently managing inventory and routing problems in a two-level supply chain system. Vendor Managed Inventory (VMI) policy is an integrating decisions between a supplier and his customers. We assumed that the demand at each customer is stationary and the warehouse is implementing a VMI. The objective of this paper is to minimize the inventory and the transportation costs of the customers for a two-level supply chain. The problem is to determine the delivery quantities, delivery times and routes to the customers for the single-period deterministic inventory routing problem (SP-DIRP) system. As a result, a linear mixed-integer program is developed for the solutions of the SP-DIRP problem.
A Hybrid Algorithm Based on ACO and PSO for Capacitated Vehicle Routing Problems
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Yucheng Kao
2012-01-01
Full Text Available The vehicle routing problem (VRP is a well-known combinatorial optimization problem. It has been studied for several decades because finding effective vehicle routes is an important issue of logistic management. This paper proposes a new hybrid algorithm based on two main swarm intelligence (SI approaches, ant colony optimization (ACO and particle swarm optimization (PSO, for solving capacitated vehicle routing problems (CVRPs. In the proposed algorithm, each artificial ant, like a particle in PSO, is allowed to memorize the best solution ever found. After solution construction, only elite ants can update pheromone according to their own best-so-far solutions. Moreover, a pheromone disturbance method is embedded into the ACO framework to overcome the problem of pheromone stagnation. Two sets of benchmark problems were selected to test the performance of the proposed algorithm. The computational results show that the proposed algorithm performs well in comparison with existing swarm intelligence approaches.
Diagnostic problems of abdominal desmoid tumors in various locations
Energy Technology Data Exchange (ETDEWEB)
Kreuzberg, B. [Department of Diagnostic Radiology, Faculty Hospital and Medical Faculty of Charles University, Alej Svobody 80, 30460 Pilsen (Czech Republic)]. E-mail: kreuzberg@fnplzen.cz; Koudelova, J. [Department of Diagnostic Radiology, Faculty Hospital and Medical Faculty of Charles University, Alej Svobody 80, 30460 Pilsen (Czech Republic); Ferda, J. [Department of Diagnostic Radiology, Faculty Hospital and Medical Faculty of Charles University, Alej Svobody 80, 30460 Pilsen (Czech Republic); Treska, V. [Department of Surgery, Faculty Hospital and Medical Faculty of Charles University, Alej Svobody 80, 30460 Pilsen (Czech Republic); Spidlen, V. [Department of Surgery, Faculty Hospital and Medical Faculty of Charles University, Alej Svobody 80, 30460 Pilsen (Czech Republic); Mukensnabl, P. [Sikl' s Department of Pathology, Faculty Hospital and Medical Faculty of Charles University, Alej Svobody 80, 30460 Pilsen (Czech Republic)
2007-05-15
Background: Abdominal desmoid tumor is one of the forms of deep (musculoaponeurotic) fibromatosis. It occurs more often as a desmoid tumor in the abdominal wall, less often in various intra-abdominal locations. In this work, we performed retrospective study concerning diagnostic problems of this disease with the use of imaging techniques. Method: Four patients (three females and one male) were examined by postcontrast CT (computed tomography) and one of them also by MR (magnetic resonance). All findings were correlated with the operational findings and histologic examination. Results: The findings were typical only in the case with the lesion located in the abdominal wall, three described cases of the intra-abdominal desmoid provided a broad range of differentially diagnostic possibilities (metastases, GIT tumors, lymphomas, etc.). In particular, the findings in infiltrative processes in intra-abdominal location and retroperitoneal involvement were less typical. Ultimately, the histological findings were decisive. Conclusion: The possibility of the occurrence of intra-abdominal desmoid tumor must be considered particularly in younger individuals with rapidly growing tumorous process, which does not immediately arise from the surrounding organs (digestive tract, internal genitalia, etc.), and is located in the abdominal wall or in the abdominal cavity.
Optimization of min-max vehicle routing problem based on genetic algorithm
Liu, Xia
2013-10-01
In some cases, there are some special requirements for the vehicle routing problem. Personnel or goods geographically scattered, should be delivered simultaneously to an assigned place by a fleet of vehicles as soon as possible. In this case the objective is to minimize the distance of the longest route among all sub-routes. An improved genetic algorithm was adopted to solve these problems. Each customer has a unique integer identifier and the chromosome is defined as a string of integers. Initial routes are constructed randomly, and then standard proportional selection incorporating elitist is chosen to guarantee the best member survives. New crossover and 2-exchange mutation is adopted to increase the diversity of group. The algorithm was implemented and tested on some instances. The results demonstrate the effectiveness of the method.
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
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.
Algebraic connectivity optimization in flight routes addition problem using tabu search method
Lumbanraja, E. M. U.; Sugeng, K. A.; Hariadi, N.
2017-07-01
In graph theory, the robustness of a network measures its resilience (in terms of connectivity) to either removal of network nodes or edges. Using algebraic connectivity is one of the best way to measure the robustness of a network. The higher algebraic connectivity means more robust network. The goal of this work is to improve the robustness of an existing air transportation network. It can be accomplished by adding edges (routes) to the network. However, due to limited budget and aircraft, the routes to be added have to be chosen carefully. The best routes to be added are the routes that will yield the highest algebraic connectivity when they were added to the network. This problem of choosing the best routes to be added is called flight routes addition. In this paper, the flight routes addition is solved using Tabu Search method with the algebraic connectivity component to choose two new lines to strengthening the robustness of the flight routes. We only consider the robustness and do not.
The vehicle routing problem with edge set costs
DEFF Research Database (Denmark)
Reinhardt, Line Blander; Jepsen, Mads Kehlet; Pisinger, David
. The certifications and contributions impose a cost for the company while they also give unlimited usage of a set of roads to all vehicles belonging to the company. Different versions for defining the edge sets are discussed and formulated. A MIP-formulation of the problem is presented, and a solution method based...
Solving stochastic multiobjective vehicle routing problem using probabilistic metaheuristic
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Gannouni Asmae
2017-01-01
closed form expression. This novel approach is based on combinatorial probability and can be incorporated in a multiobjective evolutionary algorithm. (iiProvide probabilistic approaches to elitism and diversification in multiobjective evolutionary algorithms. Finally, The behavior of the resulting Probabilistic Multi-objective Evolutionary Algorithms (PrMOEAs is empirically investigated on the multi-objective stochastic VRP problem.
AUTOMATED GUIDED VEHICLE (AGV SYSTEMS AND ROUTING PROBLEM IN DEPOT MAINTENANCE
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Fatih YİĞİT
2003-02-01
Full Text Available When full automation is realized in factory automation, material handing systems (MHS have a fairly important role. The most technological development among MHS's has been concentrated on Automated Guided Vehicle (AGV systems. An AGV is an unmanned vehicle capable of following an external guidance signal to deliver a unit load from destination to destination. Nowadays, there are a lot of applications lie along service sector to industrial sector because of flexibilities of AGVs. In this study, these subjects have been applied on the Army Aviation Depot Maintenance where aircraft's and aircraft parts can be maintained and overhauled is an application fields of AGV, requiring AGV numbers and AGV routing. The AGV routing problem and traveling sales person (TSP problems are identical problems; where the AGV routing problem is formulated as a zero one integer programming. Examples are presented to demonstrate the approach and LINGO has been used to solve the example.
Nair, T R Gopalakrishnan; Yashoda, M B
2011-01-01
In Internet Routing, the static shortest path (SP) problem has been addressed using well known intelligent optimization techniques like artificial neural networks, genetic algorithms (GAs) and particle swarm optimization. Advancement in wireless communication lead more and more mobile wireless networks, such as mobile networks [mobile ad hoc networks (MANETs)] and wireless sensor networks. Dynamic nature of the network is the main characteristic of MANET. Therefore, the SP routing problem in MANET turns into dynamic optimization problem (DOP). Here the nodes ae made aware of the environmental condition, thereby making it intelligent, which goes as the input for GA. The implementation then uses GAs with immigrants and memory schemes to solve the dynamic SP routing problem (DSPRP) in MANETS. In our paper, once the network topology changes, the optimal solutions in the new environment can be searched using the new immigrants or the useful information stored in the memory. Results shows GA with new immigrants sho...
Vehicle Routing Problem Using Savings-Insertion and Reactive Tabu with a Variable Threshold
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Moussa Bagayoko
2016-12-01
Full Text Available This paper focuses on how the competitiveness of companies is impacted by products distribution and transportation costs, especially in the context of exports. This paper uses our two steps approach, consisting in building a good initial solution and then improving it to solve vehicle routing problem. To that end, first, our mathematical model is adapted; secondly, our Savings-insertion builds a good initial solution, and thirdly, our Reactive tabu with a variable threshold improves the initial solution. The objective is the minimization of the total distance of transport by respecting the specified time window and the demand of all customers, which are important for some transportation companies’. Finally, the experimental results obtained with our methodology for Solomon 100 customers 56 vehicle routing problems are provided and discussed. Our methodology provides the best solutions for problems types R2 and RC2. Therefore, using our methodology reduces the total distance for long-haul vehicle routing problems.
Solving Practical Vehicle Routing Problem with Time Windows Using Metaheuristic Algorithms
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Filip Taner
2012-07-01
Full Text Available This paper addresses the Vehicle Routing Problem with Time Windows (VRPTW and shows that implementing algorithms for solving various instances of VRPs can significantly reduce transportation costs that occur during the delivery process. Two metaheuristic algorithms were developed for solving VRPTW: Simulated Annealing and Iterated Local Search. Both algorithms generate initial feasible solution using constructive heuristics and use operators and various strategies for an iterative improvement. The algorithms were tested on Solomon’s benchmark problems and real world vehicle routing problems with time windows. In total, 44 real world problems were optimized in the case study using described algorithms. Obtained results showed that the same distribution task can be accomplished with savings up to 40% in the total travelled distance and that manually constructed routes are very ineffective.
Approximate solution of the multiple watchman routes problem with restricted visibility range.
Faigl, Jan
2010-10-01
In this paper, a new self-organizing map (SOM) based adaptation procedure is proposed to address the multiple watchman route problem with the restricted visibility range in the polygonal domain W. A watchman route is represented by a ring of connected neuron weights that evolves in W, while obstacles are considered by approximation of the shortest path. The adaptation procedure considers a coverage of W by the ring in order to attract nodes toward uncovered parts of W. The proposed procedure is experimentally verified in a set of environments and several visibility ranges. Performance of the procedure is compared with the decoupled approach based on solutions of the art gallery problem and the consecutive traveling salesman problem. The experimental results show the suitability of the proposed procedure based on relatively simple supporting geometrical structures, enabling application of the SOM principles to watchman route problems in W.
A route-based decomposition for the Multi-Commodity k-splittable Maximum Flow Problem
DEFF Research Database (Denmark)
Gamst, Mette
2012-01-01
The Multi-Commodity k-splittable Maximum Flow Problem routes flow through a capacitated graph such that each commodity uses at most k paths and such that the total amount of routedflow is maximized. This paper proposes a branch-and-price algorithm based on a route-based Dantzig-Wolfe decomposition......, where a route consists of up to k paths. Computational results show that the new algorithm has best performance on seven benchmark instances and is capable of solving two previously unsolved instances....
A heuristic approach based on Clarke-Wright algorithm for open vehicle routing problem.
Pichpibul, Tantikorn; Kawtummachai, Ruengsak
2013-01-01
We propose a heuristic approach based on the Clarke-Wright algorithm (CW) to solve the open version of the well-known capacitated vehicle routing problem in which vehicles are not required to return to the depot after completing service. The proposed CW has been presented in four procedures composed of Clarke-Wright formula modification, open-route construction, two-phase selection, and route postimprovement. Computational results show that the proposed CW is competitive and outperforms classical CW in all directions. Moreover, the best known solution is also obtained in 97% of tested instances (60 out of 62).
A weighted min-max model for balanced freight train routing problem with fuzzy information
Yang, Lixing; Gao, Ziyou; Li, Xiang; Li, Keping
2011-12-01
A multi-objective freight train routing problem with fuzzy information is investigated in this article. To handle the fuzziness in the railway transportation system, the measure ℳλ (i.e. the convex combination of a possibility measure and a necessity measure) is first introduced. Then, a min-max chance-constrained programming model is constructed to obtain optimal train routing plans. In order to solve the model, a potential route algorithm, fuzzy simulation and tabu search algorithm are integrated as a hybrid algorithm. Finally, some numerical experiments are performed to show the applications of the model and the algorithm.
Directory of Open Access Journals (Sweden)
Julia Rieck
2013-05-01
Full Text Available In reverse logistics networks, products (e.g., bottles or containers have to be transported from a depot to customer locations and, after use, from customer locations back to the depot. In order to operate economically beneficial, companies prefer a simultaneous delivery and pick-up service. The resulting Vehicle Routing Problem with Simultaneous Delivery and Pick-up (VRPSDP is an operational problem, which has to be solved daily by many companies. We present two mixed-integer linear model formulations for the VRPSDP, namely a vehicle-flow and a commodity-flow model. In order to strengthen the models, domain-reducing preprocessing techniques, and effective cutting planes are outlined. Symmetric benchmark instances known from the literature as well as new asymmetric instances derived from real-world problems are solved to optimality using CPLEX 12.1.
A Variable Neighborhood Search-Based Heuristic for the Multi-Depot Vehicle Routing Problem
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Arif Imran
2013-01-01
Full Text Available The multi-depot vehicle routing problem (MDVRP is addressed using an adaptation of the variable neighborhood search (VNS. The proposed VNS algorithm besides using several neighborhoods and a number of local searches has a number of additional features. These include a scheme for identifying borderline customers, a diversivication procedure and a mechanism that aggregates and disaggregates routes between depots. The proposed algorithm is tested on the data instances from the literature and produces competitive results.
A savings based method for real-life vehicle routing problems
1999-01-01
textabstractThis paper describes a Savings Based algorithm for the Extended Vehicle Routing Problem. This algorithm is compared with a Sequential Insertion algorithm on real-life data. Besides the traditional quality measures such as total distance traveled and total workload, we compare the routing plans of both algorithms according to non-standard quality measures that help to evaluate the "visual attractiveness" of the plan. Computational results show that, in general, the Savings Based al...
DEFF Research Database (Denmark)
Cetin, Bilge Kartal; Prasad, Neeli R.; Prasad, Ramjee
2011-01-01
of the maximum lifetime routing problem that considers the operation modes of the node. Solution of the linear programming gives the upper analytical bound for the network lifetime. In order to illustrate teh application of the optimization model, we solved teh problem for different parameter settings...
A branch-and-price algorithm for the capacitated vehicle routing problem with stochastic demands
DEFF Research Database (Denmark)
Christiansen, Christian Holk; Lysgaard, Jens
2007-01-01
This article introduces a new exact algorithm for the Capacitated Vehicle Routing Problem with Stochastic Demands (CVRPSD). The CVRPSD can be formulated as a Set Partitioning Problem and it is shown that the associated column generation subproblem can be solved using a dynamic programming scheme...
An Adaptable Variable Neighborhood Search for the Vehicle Routing Problem with Order Outsourcing
Huijink, S.; Kant, G.; Peeters, M.J.P.
2014-01-01
In practice, many package transportation companies lower their costs by hiring outside carriers to serve orders that cannot be served efficiently by their own trucks. The problem which takes the order outsource option into account is the Vehicle Routing Problem with Private Fleet and Common Carrier.
An Adaptable Variable Neighborhood Search for the Vehicle Routing Problem with Order Outsourcing
Huijink, S.; Kant, G.; Peeters, M.J.P.
2014-01-01
In practice, many package transportation companies lower their costs by hiring outside carriers to serve orders that cannot be served efficiently by their own trucks. The problem which takes the order outsource option into account is the Vehicle Routing Problem with Private Fleet and Common Carrier.
Determining which Orders to Outsource in the Vehicle Routing Problem with Order Outsourcing
Huijink, Sybren; Kant, Goos; Peeters, Rene
2015-01-01
In practice, many package transportation companies lower their costs by hiring outside carriers to serve orders that cannot be served efficiently by their own trucks. The problem which takes the order outsource option into account is the Vehicle Routing Problem with Private Fleet and Common Carrier.
Determining which Orders to Outsource in the Vehicle Routing Problem with Order Outsourcing
Huijink, Sybren; Kant, Goos; Peeters, Rene
2015-01-01
In practice, many package transportation companies lower their costs by hiring outside carriers to serve orders that cannot be served efficiently by their own trucks. The problem which takes the order outsource option into account is the Vehicle Routing Problem with Private Fleet and Common Carrier.
Directory of Open Access Journals (Sweden)
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.
Using Grey Wolf Algorithm to Solve the Capacitated Vehicle Routing Problem
Korayem, L.; Khorsid, M.; Kassem, S. S.
2015-05-01
The capacitated vehicle routing problem (CVRP) is a class of the vehicle routing problems (VRPs). In CVRP a set of identical vehicles having fixed capacities are required to fulfill customers' demands for a single commodity. The main objective is to minimize the total cost or distance traveled by the vehicles while satisfying a number of constraints, such as: the capacity constraint of each vehicle, logical flow constraints, etc. One of the methods employed in solving the CVRP is the cluster-first route-second method. It is a technique based on grouping of customers into a number of clusters, where each cluster is served by one vehicle. Once clusters are formed, a route determining the best sequence to visit customers is established within each cluster. The recently bio-inspired grey wolf optimizer (GWO), introduced in 2014, has proven to be efficient in solving unconstrained, as well as, constrained optimization problems. In the current research, our main contributions are: combining GWO with the traditional K-means clustering algorithm to generate the ‘K-GWO’ algorithm, deriving a capacitated version of the K-GWO algorithm by incorporating a capacity constraint into the aforementioned algorithm, and finally, developing 2 new clustering heuristics. The resulting algorithm is used in the clustering phase of the cluster-first route-second method to solve the CVR problem. The algorithm is tested on a number of benchmark problems with encouraging results.
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Yan Sun
2015-01-01
Full Text Available We explore a freight routing problem wherein the aim is to assign optimal routes to move commodities through a multimodal transportation network. This problem belongs to the operational level of service network planning. The following formulation characteristics will be comprehensively considered: (1 multicommodity flow routing; (2 a capacitated multimodal transportation network with schedule-based rail services and time-flexible road services; (3 carbon dioxide emissions consideration; and (4 a generalized costs optimum oriented to customer demands. The specific planning of freight routing is thus defined as a capacitated time-sensitive multicommodity multimodal generalized shortest path problem. To solve this problem systematically, we first establish a node-arc-based mixed integer nonlinear programming model that combines the above formulation characteristics in a comprehensive manner. Then, we develop a linearization method to transform the proposed model into a linear one. Finally, a computational experiment from the Chinese inland container export business is presented to demonstrate the feasibility of the model and linearization method. The computational results indicate that implementing the proposed model and linearization method in the mathematical programming software Lingo can effectively solve the large-scale practical multicommodity multimodal transportation routing problem.
On the Integrated Job Scheduling and Constrained Network Routing Problem
DEFF Research Database (Denmark)
Gamst, Mette
This paper examines the NP-hard problem of scheduling a number of jobs on a finite set of machines such that the overall profit of executed jobs is maximized. Each job demands a number of resources, which must be sent to the executing machine via constrained paths. Furthermore, two resource demand...... transmissions cannot use the same edge in the same time period. An exact solution approach based on Dantzig-Wolfe decomposition is proposed along with several heuristics. The methods are computationally evaluated on test instances arising from telecommunications with up to 500 jobs and 500 machines. Results...
Research on multi-objective emergency logistics vehicle routing problem under constraint conditions
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Miaomiao Du
2013-03-01
Full Text Available Purpose: Aim at choosing a relative good vehicle routing in emergency conditions under constraint conditions when disaster happens. Rapid response and rescue can save a lot of people. Design/methodology/approach: Modeling analysis: establishing a mathematical model of multi-objective emergency logistics vehicle routing problem. And in end of the paper, we intend to use genetic algorithms to solve the problem. Findings: Considering time requirement and cost limit both while choosing vehicle routing when the disasters happens is meaningful. We can get a relative good result and give a guidance to rescue teams. Originality/value: Consider cost and time objectives and kinds of realistic conditions (such as the road congestion in the model when solving the problem, having expanded the theory scope.
Optimal tests for the two-sample spherical location problem
Ley, Christophe; Verdebout, Thomas
2012-01-01
We tackle the classical two-sample spherical location problem for directional data by having recourse to the Le Cam methodology, habitually used in classical "linear" multivariate analysis. More precisely we construct locally and asymptotically optimal (in the maximin sense) parametric tests, which we then turn into semi-parametric ones in two distinct ways. First, by using a studentization argument; this leads to so-called pseudo-FvML tests. Second, by resorting to the invariance principle; this leads to efficient rank-based tests. Within each construction, the semi-parametric tests inherit optimality under a given distribution (the FvML in the first case, any rotationally symmetric one in the second) from their parametric counterparts and also improve on the latter by being valid under the whole class of rotationally symmetric distributions. Asymptotic relative efficiencies are calculated and the finite-sample behavior of the proposed tests is investigated by means of a Monte Carlo simulation.
Vehicle Routing Problem with Backhaul, Multiple Trips and Time Window
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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.
Developing a Direct Search Algorithm for Solving the Capacitated Open Vehicle Routing Problem
Simbolon, Hotman
2011-06-01
In open vehicle routing problems, the vehicles are not required to return to the depot after completing service. In this paper, we present the first exact optimization algorithm for the open version of the well-known capacitated vehicle routing problem (CVRP). The strategy of releasing nonbasic variables from their bounds, combined with the "active constraint" method and the notion of superbasics, has been developed for efficiently requirements; this strategy is used to force the appropriate non-integer basic variables to move to their neighborhood integer points. A study of criteria for choosing a nonbasic variable to work with in the integerizing strategy has also been made.
A note on "A LP-based heuristic for a time-constrained routing problem"
Muter, İbrahim; Muter, Ibrahim; Birbil, Ş. İlker; Birbil, S. Ilker; Bülbül, Kerem; Bulbul, Kerem; Şahin, Güvenç; Sahin, Guvenc
2012-01-01
Avella et al. (2006) [Avella, P., D'Auria, B., Salerno, S. (2006). A LP-based heuristic for a time-constrained routing problem. European Journal of Operational Research 173:120-124] investigate a time-constrained routing (TCR) problem. The core of the proposed solution approach is a large-scale linear program (LP) that grows both row- and column-wise when new variables are introduced. Thus, a column-and-row generation algorithm is proposed to solve this LP optimally, and an optimality conditi...
Solution to the problem of ant being stuck by ant colony routing algorithm
Institute of Scientific and Technical Information of China (English)
ZHAO Jing; TONG Wei-ming
2009-01-01
Many ant colony routing (ACR) algorithms have been presented in recent years, but few have studied the problem that ants will get stuck with probability in any terminal host when they are searching paths to route packets around a network. The problem has to be faced when designing and implementing the ACR algorithm. This article analyzes in detail the differences between the ACR and the ant colony optimization (ACO). Besides, particular restrictions on the ACR are pointed out and the three causes of ant being-stuck problem are obtained. Furthermore, this article proposes a new ant searching mechanism through dual path-checking and online routing loop removing by every intermediate node an ant visited and the destination host respectively, to solve the problem of ant being stuck and routing loop simultaneously. The result of numerical simulation is abstracted from one real network. Compared with existing two typical ACR algorithms, it shows that the proposed algorithm can settle the problem of ant being stuck and achieve more effective searching outcome for optimization path.
An Investigation of Using Parallel Genetic Algorithm for Solving the Shortest Path Routing Problem
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Salman Yussof
2011-01-01
Full Text Available Problem statement: Shortest path routing is the type of routing widely used in computer network nowadays. Even though shortest path routing algorithms are well established, other alternative methods may have their own advantages. One such alternative is to use a GA-based routing algorithm. According to previous researches, GA-based routing algorithm has been found to be more scalable and insensitive to variations in network topologies. However, it is also known that GA-based routing algorithm is not fast enough for real-time computation. Approach: To improve the computation time of GA-based routing algorithm, this study proposes a coarse-grained parallel GA routing algorithm for solving the shortest path routing problem. The proposed algorithm is evaluated using simulation where the proposed algorithm is executed on networks with various topologies and sizes. The parallel computation is performed using an MPI cluster. Three different experiments were conducted to identify the best value for the migration rate, the accuracy and execution time with respect to the number of computing nodes and speedup achieved as compared to the serial version of the same algorithm. Results: The result of the simulation shows that the best result is achieved for a migration rate around 0.1 and 0.2. The experiments also show that with larger number of computing nodes, accuracy decreases linearly, but computation time decreases exponentially, which justifies the use parallel implementation of GA to improve the speed of GA-based routing algorithm. Finally, the experiments also show that the proposed algorithm is able to achieve a speedup of up to 818.11% on the MPI cluster used to run the simulation. Conclusion/Recommendations: We have successfully shown that the performance of GA-based shortest path routing algorithm can be improved by using a coarse-grained parallel GA implementation. Even though in this study the proposed algorithm is executed
Shanmugasundaram, Jothiganesh; Soulalay, Vongdeuane; Chettiyappan, Visvanathan
2012-06-01
In Lao People's Democratic Republic (Lao PDR), a growth of healthcare centres, and the environmental hazards and public health risks typically accompanying them, increased the need for healthcare waste (HCW) management planning. An effective planning of an HCW management system including components such as the treatment plant siting and an optimized routeing system for collection and transportation of waste is deemed important. National government offices at developing countries often lack the proper tools and methodologies because of the high costs usually associated with them. However, this study attempts to demonstrate the use of an inexpensive GIS modelling tool for healthcare waste management in the country. Two areas were designed for this study on HCW management, including: (a) locating centralized treatment plants and designing optimum travel routes for waste collection from nearby healthcare facilities; and (b) utilizing existing hospital incinerators and designing optimum routes for collecting waste from nearby healthcare facilities. Spatial analysis paved the way to understand the spatial distribution of healthcare wastes and to identify hotspots of higher waste generating locations. Optimal route models were designed for collecting and transporting HCW to treatment plants, which also highlights constraints in collecting and transporting waste for treatment and disposal. The proposed model can be used as a decision support tool for the efficient management of hospital wastes by government healthcare waste management authorities and hospitals.
2013-01-01
Transportation costs constitute a significant fraction of total logistics cost in Supply Chain Management (SCM). To reduce transportation costs, improve customer service and to achieve maximum customer satisfaction, the optimal selection of the vehicle route is a frequent decision problem and this is commonly known as vehicle routing problem. Vehicle routing problem with one-sided time constraint, where the delivery of products from depots to distribution centers has to take place within the ...
Kok, A.L.; Meyer, C.M.; Kopfer, H.; Schutten, J.M.J.
2010-01-01
In practice, apart from the problem of vehicle routing, schedulers also face the problem of finding feasible driver schedules complying with complex restrictions on drivers' driving and working hours. To address this complex interdependent problem of vehicle routing and break scheduling, we propose
An optimization algorithm for a capacitated vehicle routing problem with time windows
Indian Academy of Sciences (India)
PINAR KIRCI
2016-05-01
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 hours. Recently, cost and on-time delivery are the most important actors in logistics. Thus, the logistic applications attract attention of companies. In logistic management, determining the locations of delivery points and deciding the path are the vital components that should be considered. Deciding the paths of vehicles provides companies to use their vehicles efficiently. And with utilizing optimized paths, big amounts of cost and time savings will be gained. The main aim of the work is providing the best path according to the needs of the customers, minimizing the costs with utilizing the VRP and presenting an application for companies that need logistic management. To compare the results, simulated annealing is used on special scenarios. And t-test is performed in the study for the visited path in km with p-value of 0.05.
A Food Chain Algorithm for Capacitated Vehicle Routing Problem with Recycling in Reverse Logistics
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.
The Time-Dependent Multiple-Vehicle Prize-Collecting Arc Routing Problem
DEFF Research Database (Denmark)
Black, Daniel; Eglese, Richard; Wøhlk, Sanne
2015-01-01
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...
Davendra, Donald; Zelinka, Ivan; Senkerik, Roman; Jasek, Roman; Bialic-Davendra, Magdalena
2012-11-01
One of the new emerging application strategies for optimization is the hybridization of existing metaheuristics. The research combines the unique paradigms of solution space sampling of SOMA and memory retention capabilities of Scatter Search for the task of capacitated vehicle routing problem. The new hybrid heuristic is tested on the Taillard sets and obtains good results.
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
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...
Constraint Programming based Local Search for the Vehicle Routing Problem with Time Windows
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".
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...
THREE-DIMENSIONAL LOADING VEHICLE ROUTING PROBLEM SOLUTION WITH SET-PARTITIONING-BASED METHOD
2013-01-01
The article considers the optimization problem of vehicle routing with three-dimensional loading constraints. Several practical loading constraints encountered in freight transportation are formalized. The efficiency of using the set-partitioning approach to improve heuristic solution is shown by means of computational experiment.
Procedures for Vehicle Routing Problems with An Application to Milk Assembly in New York
1982-01-01
This paper discusses improved procedures for applying heuristic methods to well-known transportation and routing algorithms for solving a milk assembly problem. Miles traveled to assemble milk are reduced by up to 20 percent in a detailed case study in New York.
Stochastic time-dependent vehicle routing problem: Mathematical models and ant colony algorithm
Directory of Open Access Journals (Sweden)
Zhengyu Duan
2015-11-01
Full Text Available This article addresses the stochastic time-dependent vehicle routing problem. Two mathematical models named robust optimal schedule time model and minimum expected schedule time model are proposed for stochastic time-dependent vehicle routing problem, which can guarantee delivery within the time windows of customers. The robust optimal schedule time model only requires the variation range of link travel time, which can be conveniently derived from historical traffic data. In addition, the robust optimal schedule time model based on robust optimization method can be converted into a time-dependent vehicle routing problem. Moreover, an ant colony optimization algorithm is designed to solve stochastic time-dependent vehicle routing problem. As the improvements in initial solution and transition probability, ant colony optimization algorithm has a good performance in convergence. Through computational instances and Monte Carlo simulation tests, robust optimal schedule time model is proved to be better than minimum expected schedule time model in computational efficiency and coping with the travel time fluctuations. Therefore, robust optimal schedule time model is applicable in real road network.
2015-01-01
subsection 4 provides an overview of the benchmark data sets for the SDVRP. 3 2.1 SDVRP Formulation According to Aleman et al. (2010), the...variants of the vehicle routing problem. 24 References Aleman , R.E., Zhang, X., Hill, R. R., 2010. An adaptive memory algorithm for the split
Lower and Upper Bounds for the Node, Edge, and Arc Routing Problem
DEFF Research Database (Denmark)
Bach, Lukas; Wøhlk, Sanne; Hasle, Geir
. It captures important aspects of real-life routing problems that were not adequately modeled in previous VRP variants. Hence, its definition and investigation contribute to the development of rich VRPs. In this paper we present the first lower bound for the NEARP. It is a further development of lower bounds...
An Artificial Bee Colony Algorithm for the Capacitated Vehicle Routing Problem
DEFF Research Database (Denmark)
Szeto, W.Y.; Wu, Yongzhong; Ho, Sin C.
This paper introduces an artificial bee colony heuristic for 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. The performance of the heuristic is evaluated on two sets of benchmark ins...
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...
Indoor Pedestrian Navigation Based on Hybrid Route Planning and Location Modeling
DEFF Research Database (Denmark)
Schougaard, Kari Rye; Grønbæk, Kaj; Scharling, Tejs
2012-01-01
This paper introduces methods and services called PerPosNav for development of custom indoor pedestrian navigation applications to be deployed on a variety of platforms. PerPosNav combines symbolic and geometry based modeling of buildings, and in turn combines graph-based and geometric route...
A framework for the interactive resolution of multi-objective vehicle routing problems
Geiger, Martin Josef
2008-01-01
The article presents a framework for the resolution of rich vehicle routing problems which are difficult to address with standard optimization techniques. We use local search on the basis on variable neighborhood search for the construction of the solutions, but embed the techniques in a flexible framework that allows the consideration of complex side constraints of the problem such as time windows, multiple depots, heterogeneous fleets, and, in particular, multiple optimization criteria. In order to identify a compromise alternative that meets the requirements of the decision maker, an interactive procedure is integrated in the resolution of the problem, allowing the modification of the preference information articulated by the decision maker. The framework is prototypically implemented in a computer system. First results of test runs on multiple depot vehicle routing problems with time windows are reported.
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.
Single-Commodity Vehicle Routing Problem with Pickup and Delivery Service
Directory of Open Access Journals (Sweden)
Goran Martinovic
2008-01-01
Full Text Available We present a novel variation of the vehicle routing problem (VRP. Single commodity cargo with pickup and delivery service is considered. Customers are labeled as either cargo sink or cargo source, depending on their pickup or delivery demand. This problem is called a single commodity vehicle routing problem with pickup and delivery service (1-VRPPD. 1-VRPPD deals with multiple vehicles and is the same as the single-commodity traveling salesman problem (1-PDTSP when the number of vehicles is equal to 1. Since 1-VRPPD specializes VRP, it is hard in the strong sense. Iterative modified simulated annealing (IMSA is presented along with greedy random-based initial solution algorithm. IMSA provides a good approximation to the global optimum in a large search space. Experiment is done for the instances with different number of customers and their demands. With respect to average values of IMSA execution times, proposed method is appropriate for practical applications.
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.
Solving the Tractor and Semi-Trailer Routing Problem Based on a Heuristic Approach
Directory of Open Access Journals (Sweden)
Hongqi Li
2012-01-01
Full Text Available We study the tractor and semi-trailer routing problem (TSRP, a variant of the vehicle routing problem (VRP. In the TSRP model for this paper, vehicles are dispatched on a trailer-flow network where there is only one main depot, and all tractors originate and terminate in the main depot. Two types of decisions are involved: the number of tractors and the route of each tractor. Heuristic algorithms have seen widespread application to various extensions of the VRP. However, this approach has not been applied to the TSRP. We propose a heuristic algorithm to solve the TSRP. The proposed heuristic algorithm first constructs the initial route set by the limitation of a driver’s on-duty time. The candidate routes in the initial set are then filtered by a two-phase approach. The computational study shows that our algorithm is feasible for the TSRP. Moreover, the algorithm takes relatively little time to obtain satisfactory solutions. The results suggest that our heuristic algorithm is competitive in solving the TSRP.
A hybrid differential evolution algorithm to vehicle routing problem with fuzzy demands
Erbao, Cao; Mingyong, Lai
2009-09-01
In this paper, the vehicle routing problem with fuzzy demands (VRPFD) is considered, and a fuzzy chance constrained program model is designed, based on fuzzy credibility theory. Then stochastic simulation and differential evolution algorithm are integrated to design a hybrid intelligent algorithm to solve the fuzzy chance constrained program model. Moreover, the influence of the dispatcher preference index on the final objective of the problem is discussed using stochastic simulation, and the best value of the dispatcher preference index is obtained.
Hybrid tabu search for the multi-depot vehicle routing problem
Hu, Shan-Liang
2010-07-01
A hybrid tabu search for the multi-depot vehicle routing problem is considered in this paper. The purpose of the proposed approach is to decrease the number of used vehicles and the total travel cost. An extensive numerical experiment was performed on benchmark problem instances available in literature, the computational results are presented to show the high effectiveness and performance of the proposed approaches.
Inventory-routing problem with pickups and deliveries of RTI in closed-loop supply chain
Limbourg, Sabine
2014-01-01
Reducing environmental impact, related regulations and potential for operational benefits are the main reasons why companies share their Returnable Transport Items (RTIs) among different partners of a closed-loop supply chain. This research deals with an inventory-routing problem with pickups and deliveries of RTIs. A mixed-integer linear program is developed and tested on small instances. To handle realistic large size problems, a clustering algorithm is coupled with a simulation model. This...
The vehicle routing problem: State of the art classification and review
Braekers, Kris; Ramaekers, Katrien; Van Nieuwenhuyse, Inneke
2016-01-01
Over the past decades, the Vehicle Routing Problem (VRP) and its variants have grown ever more popular in the academic literature. Yet, the problem characteristics and assumptions vary widely and few literature reviews have made an effort to classify the existing articles accordingly. In this article, we present a taxonomic review of the VRP literature published between 2009 and June 2015. Based on an adapted version of an existing comprehensive taxonomy, we classify 277 articles and analyze ...
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.
Location Problem of Air Materials Supply Center for Air Force
Institute of Scientific and Technical Information of China (English)
王涛; 何亚群; 陶学禹
2002-01-01
Based on the analysis of three influencing factors on the air material supply center location, the location model of air material supply center was established. By solving the model, the rational supply center of air materials was also determined.
An exact algorithm for the vehicle routing problem with stochastic demands
Energy Technology Data Exchange (ETDEWEB)
Louveaux, F.
1994-12-31
The classical deterministic Vehicle Routing Problem (VRP) can be defined as follows. Let G = (V, E) be an undirected graph where V = {l_brace}v{sub 1}, {center_dot}{center_dot}, v{sub n}{r_brace} is a set of vertices representing cities or customers, and E = {l_brace}(v{sub i}, V{sub j}) : i < j; v{sub i}, v{sub j} {element_of} V{r_brace} is an edge set. With each vertex v{sub i}(i {>=} 2) (v{sub i}, v{sub j}) is associated a non-negative cost (distance, travel time) c{sub ij}. Vertex v{sub 1} represents a depot at which are based m identical vehicle of capacity Q > 0. Depending on the version of the problem considered, the value of m is either fixed, or bounded above by a constant {<=} m. The VRP consists of determining vehicle routes in such a way that (i) all routes start and end at the depot; (ii) each vertex other than the depot is visited exactly once; (iii) the total demand of any given route does not exceed Q; (iv) the total distance traveled by all vehicles is minimized. In the Stochastic Vehicle Routing Problem (SVRP), the demand associated with vertex v{sub i} is a random variable {xi}{sub i}. As a result, it is no longer possible to assume that vehicle routes may be followed as planned. The SRVP is modeled in two stages. In the first stage, a priori vehicle routes satisyfing conditions (i) and (ii) are constructed, without full information on the demands. In the second stage, when this information becomes available, routes are followed as planned, until the accumulated demand attains or exceeds the vehicle capacity. In this case, failure is said to occur and a recourse action is taken: the vehicle returns to the depot to unload, and resumes its visits at the point of failure. The SVRP consists of determining an a priori set of routes so as to minimize the expected cost of the second stage solution. The corresponding model can be solved using the relaxation approach in Laporte and Louveaux.
Heuristic algorithms for solving of the tool routing problem for CNC cutting machines
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.
Solving the Vehicle Routing Problem with Stochastic Demands via Hybrid Genetic Algorithm-Tabu Search
Directory of Open Access Journals (Sweden)
Z. Ismail
2008-01-01
Full Text Available This study considers a version of the stochastic vehicle routing problem where customer demands are random variables with known probability distribution. A new scheme based on a hybrid GA and Tabu Search heuristic is proposed for this problem under a priori approach with preventive restocking. The relative performance of the proposed HGATS is compared to each GA and TS alone, on a set of randomly generated problems following some discrete probability distributions. The problem data are inspired by real case of VRPSD in waste collection. Results from the experiment show the advantages of the proposed algorithm that are its robustness and better solution qualities resulted.
Simulated annealing (SA to vehicle routing problems with soft time windows
Directory of Open Access Journals (Sweden)
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.
GREEDY NON-DOMINATED SORTING IN GENETIC ALGORITHM-II FOR VEHICLE ROUTING PROBLEM IN DISTRIBUTION
Institute of Scientific and Technical Information of China (English)
无
2008-01-01
Vehicle routing problem in distribution (VRPD) is a widely used type of vehicle routing problem (VRP), which has been proved as NP-Hard, and it is usually modeled as single objective optimization problem when modeling. For multi-objective optimization model, most researches consider two objectives. A multi-objective mathematical model for VRP is proposed, which considers the number of vehicles used, the length of route and the time arrived at each client. Genetic algorithm is one of the most widely used algorithms to solve VRP. As a type of genetic algorithm (GA), non-dominated sorting in genetic algorithm-Ⅱ(NSGA-Ⅱ) also suffers from premature convergence and enclosure competition. In order to avoid these kinds of shortage, a greedy NSGA-Ⅱ (GNSGA-Ⅱ) is proposed for VRP problem. Greedy algorithm is implemented in generating the initial population, cross-over and mutation. All these procedures ensure that NSGA-Ⅱ is prevented from premature convergence and refine the performance of NSGA-Ⅱ at each step. In the distribution problem of a distribution center in Michigan, US, the GNSGA-Ⅱ is compared with NSGA-Ⅱ. As a result, the GNSGA-II is the most efficient one and can get the most optimized solution to VRP problem. Also, in GNSGA-II, premature convergence is better avoided and search efficiency has been improved sharply.
The electric vehicle routing problem with non-linear charging functions
2015-01-01
International audience; The use of electric vehicles (EVs) in freight and passenger transportation gives birth to a new family of vehicle routing problems (VRPs), the so-called electric VRPs (e-VRPs). As their name suggests, e-VRPs extend classical VRPs to account (mainly) for two constraining EV features: the short driving range and the long battery charging time. As a matter of fact, routes performed by EVs usually need to include time-consuming detours to charging stations. Most of the exi...
Directory of Open Access Journals (Sweden)
Martin Macík
2015-09-01
Full Text Available High level of competition on postal market increases demands on reliability of postal services and lowering of transport costs. This can be achieved by optimizing the routing of postal vehicles. The article discusses the possibilities of such optimization by using graph theory. It describes basic methods of finding optimal routes using a graph. The approach, used in this article, assesses the possibility of applying meta-heuristic solution to the traveling salesman problem in the postal sector. Simulation of methods described has been applied on a regional postal network. Results showed that the software used proves to be sufficiently functional for the field of postal transport networks.
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...... new integer linear programming formulations for the GVRP, two based on multicommodity flow and the other two based on exponential sets of inequalities. Branch-and-cut algorithms are proposed for the latter two. Computational results on a large set of instances are presented....
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.
Optimized Crossover Genetic Algorithm for Vehicle Routing Problem with Time Windows
Directory of Open Access Journals (Sweden)
H. Nazif
2010-01-01
Full Text Available Problem statement: In this study, we considered the application of a genetic algorithm to vehicle routing problem with time windows where a set of vehicles with limits on capacity and travel time are available to service a set of customers with demands and earliest and latest time for serving. The objective is to find routes for the vehicles to service all the customers at a minimal cost without violating the capacity and travel time constraints of the vehicles and the time window constraints set by the customers. Approach: We proposed a genetic algorithm using an optimized crossover operator designed by a complete undirected bipartite graph that finds an optimal set of delivery routes satisfying the requirements and giving minimal total cost. Various techniques have also been introduced into the proposed algorithm to further enhance the solutions quality. Results: We tested our algorithm with benchmark instances and compared it with some other heuristics in the literature. The results showed that the proposed algorithm is competitive in terms of the quality of the solutions found. Conclusion/Recommendations: This study presented a genetic algorithm for solving vehicle routing problem with time windows using an optimized crossover operator. From the results, it can be concluded that the proposed algorithm is competitive when compared with other heuristics in the literature.
Relative Performance of Certain Meta Heuristics on Vehicle Routing Problem with Time Windows
Directory of Open Access Journals (Sweden)
Sandhya
2015-11-01
Full Text Available —Solving Vehicle Routing Problem (VRP and its variants arise in many real life distribution systems. Classical VRP can be described as the problem of finding minimum cost routes with identical vehicles having fixed capacity which starts from a depot and reaches a number of customers with known demands with the proviso that each route starts and ends at the depot and the demand of each customer does not exceed the vehicle capacity is met. One of the generalizations of standard VRP is Vehicle Routing Problem with Time Windows (VRPTW with added complexity of serving every customer within a specified time window. Since VRPTW is a NP hard meta heuristics have often been designed for solving it. In this paper we compare the performance of Simulated Annealing (SA, genetic Algorithm (GA and Ant Colony Optimization (ACO for solving VRPTW based on their performance using different parameters taking total travel distance as the objective to be minimized. The results indicate that ACO is in general slightly more efficient then SA and GA.
Vehicle Routing Problem for Fashion Supply Chains with Cross-Docking
Directory of Open Access Journals (Sweden)
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.
Indoor Pedestrian Navigation Based on Hybrid Route Planning and Location Modeling
DEFF Research Database (Denmark)
Schougaard, Kari Rye; Grønbæk, Kaj; Scharling, Tejs
2012-01-01
This paper introduces methods and services called PerPosNav for development of custom indoor pedestrian navigation applications to be deployed on a variety of platforms. PerPosNav combines symbolic and geometry based modeling of buildings, and in turn combines graph-based and geometric route...... computation. The paper argues why these hybrid approaches are necessary to handle the challenges of in-door pedestrian navigation...
Shi, Juanfei; Calveras, Anna; Cheng, Ye; Liu, Kai
2013-05-15
The extensive usage of wireless sensor networks (WSNs) has led to the development of many power- and energy-efficient routing protocols. Cooperative routing in WSNs can improve performance in these types of networks. In this paper we discuss the existing proposals and we propose a routing algorithm for wireless sensor networks called Power Efficient Location-based Cooperative Routing with Transmission Power-upper-limit (PELCR-TP). The algorithm is based on the principle of minimum link power and aims to take advantage of nodes cooperation to make the link work well in WSNs with a low transmission power. In the proposed scheme, with a determined transmission power upper limit, nodes find the most appropriate next nodes and single-relay nodes with the proposed algorithm. Moreover, this proposal subtly avoids non-working nodes, because we add a Bad nodes Avoidance Strategy (BAS). Simulation results show that the proposed algorithm with BAS can significantly improve the performance in reducing the overall link power, enhancing the transmission success rate and decreasing the retransmission rate.
Location and Mobility Optimized On-demand Geographical Multipath Routing Protocol for MANET
Directory of Open Access Journals (Sweden)
M. Kokilamani
2016-01-01
Full Text Available The advancement of science and technology had made mobile ad hoc network an important tool to access network of next generation. Recently, numerous multipath routing protocols for mobile ad hoc network are reported in literature. Each routing methods works based on their salient feature, but failed to control congestion, energy efficiency, overhead packets, signal stability during data transmission which leads to edge effect, signal decay and bottleneck situation of the bandwidth consumption. In this paper a novel approach havely Geographical Distance based Ad Hoc On-demand Distance Vector Routing (GD-AOMDV, which selects the path based on transmission distance value to limit and control the congestion and control overheads has been proposed. The salient feature of the proposed model is that it establishes a relationship between path distance and MANET design parameters including transmission range, consumption of energy and bandwidth. The accuracy of the proposed scheme is analyzed and validated with the experimental results in respect to various flow using NS2 simulations.
A new memetic algorithm for solving split delivery vehicle routing problem
Directory of Open Access Journals (Sweden)
Ali Bozorgi-Amiri
2015-11-01
Full Text Available Split delivery vehicle routing problem is one of the traditional types of routing problems in which the demand of different points can be divided among vehicles and the objective is to minimize the path length, which vehicles travel. In this paper, fuel cost of vehicles which is assumed to be dependent on their traveled path and load is considered as the objective functions. Namely, the cost of the consumed fuel is proportionate to the unit of load carried per unit of distance. In order to solve the proposed model a new memetic algorithm is developed which has two rows. The performance of the proposed algorithm for 21 standard problems is compared with the optimum solutions obtained from mathematical programming standard solver and the solutions of the same algorithm with single row solution representation. The results express the efficiency of developed algorithm.
A generalized multi-depot vehicle routing problem with replenishment based on LocalSolver
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Ying Zhang
2015-01-01
Full Text Available In this paper, we consider the multi depot heterogeneous vehicle routing problem with time windows in which vehicles may be replenished along their trips. Using the modeling technique in a new-generation solver, we construct a novel formulation considering a rich series of constraint conditions and objective functions. Computation results are tested on an example comes from the real-world application and some cases obtained from the benchmark problems. The results show the good performance of local search method in the efficiency of replenishment system and generalization ability. The variants can be used to almost all kinds of vehicle routing problems, without much modification, demonstrating its possibility of practical use.
Directory of Open Access Journals (Sweden)
Kui-Ting CHEN
2015-12-01
Full Text Available Capacitated vehicle routing problem with pickups and deliveries (CVRPPD is one of the most challenging combinatorial optimization problems which include goods delivery/pickup optimization, vehicle number optimization, routing path optimization and transportation cost minimization. The conventional particle swarm optimization (PSO is difficult to find an optimal solution of the CVRPPD due to its simple search strategy. A PSO with adaptive multi-swarm strategy (AMSPSO is proposed to solve the CVRPPD in this paper. The proposed AMSPSO employs multiple PSO algorithms and an adaptive algorithm with punishment mechanism to search the optimal solution, which can deal with large-scale optimization problems. The simulation results prove that the proposed AMSPSO can solve the CVRPPD with the least number of vehicles and less transportation cost, simultaneously.
Solving the vehicle routing problem by a hybrid meta-heuristic algorithm
Yousefikhoshbakht, Majid; Khorram, Esmaile
2012-08-01
The vehicle routing problem (VRP) is one of the most important combinational optimization problems that has nowadays received much attention because of its real application in industrial and service problems. The VRP involves routing a fleet of vehicles, each of them visiting a set of nodes such that every node is visited by exactly one vehicle only once. So, the objective is to minimize the total distance traveled by all the vehicles. This paper presents a hybrid two-phase algorithm called sweep algorithm (SW) + ant colony system (ACS) for the classical VRP. At the first stage, the VRP is solved by the SW, and at the second stage, the ACS and 3-opt local search are used for improving the solutions. Extensive computational tests on standard instances from the literature confirm the effectiveness of the presented approach.
About a Routing Problem of the Tool Motion on Sheet Cutting
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A. A. Petunin
2015-01-01
Full Text Available For the routing problem of tool permutations under the thermal cutting of parts from sheet material realized on CNC machines, questions connected with constructing precise (optimal and heuristic algorithms used on the stage of mathematical simulation of route elements under sequential megalopolises circuit are investigated. Cutting points and points of tool cut-off are items (cities of the above-mentioned megalopolises. In each megalopolis, interior works are provided. These works are connected with motion to the equidistant curve of the cut contour of a part from the cutting point and (with cutting completed with motion from the equidistant curve to the tool cut-off (we keep in mind a working run. The problem about the time-optimal process of cutting which is a special variant of the generalized courier problem is investigated (the problem of the routing on the megalopolises with precedence conditions. An optimal procedure based on the dynamic programming and an effective heuristic algorithm realized on a multicore computer are proposed. A dynamic programming based procedure uses a special extension of the main problem. This extension provides the replacement of admissibility by precedence with the admissibility by deletion (from the list of tasks. Precedence conditions are used for decreasing computational complexity: it excludes the building of the whole array of the Bellman function values (this function is replaced by the layers system.
A mathematical modeling proposal for a Multiple Tasks Periodic Capacitated Arc Routing Problem
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Cleverson Gonçalves dos Santos
2015-12-01
Full Text Available The countless accidents and incidents occurred at dams at the last years, propelled the development of politics related with dams safety. One of the strategies is related to the plan for instrumentation and monitoring of dams. The monitoring demands from the technical team the reading of the auscultation data, in order to periodically monitor the dam. The monitoring plan of the dam can be modeled as a problem of mathematical program of the periodical capacitated arcs routing program (PCARP. The PCARP is considered as a generalization of the classic problem of routing in capacitated arcs (CARP due to two characteristics: 1 Planning period larger than a time unity, as that vehicle make several travels and; 2 frequency of associated visits to the arcs to be serviced over the planning horizon. For the dam's monitoring problem studied in this work, the frequent visits, along the time horizon, it is not associated to the arc, but to the instrument with which is intended to collect the data. Shows a new problem of Multiple tasks Periodic Capacitated Arc Routing Problem and its elaboration as an exact mathematical model. The new main characteristics presented are: multiple tasks to be performed on each edge or edges; different frequencies to accomplish each of the tasks; heterogeneous fleet; and flexibility for more than one vehicle passing through the same edge at the same day. The mathematical model was implemented and examples were generated randomly for the proposed model's validation.
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Cihan Ercan
2013-02-01
Full Text Available Outwith the technological developments made with Unmanned Aerial Vehicles (UAV; other important issues for the users like effective planning and re-planning; providing the clear, concise and timely information to the decision makers is part of the Network Enabled Capability. Significant improvements to the Communication and Information systems have made it possible to find dynamic solutions for Vehicle Routing Problems. In this context, "Vehicle Routing" applications for UAVs in reconnaissance missions are increasing exponentially. This study investigates the literature in "dynamic route planning", defining the scope and identifying shortcomings for future studies in Unmanned Aerial Systems. Using this approach not only reduces stagnant travel time to target time but increases the usable times spent on targets.
Electric Vehicle Routing Problem with Charging Time and Variable Travel Time
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Sai Shao
2017-01-01
Full Text Available An electric vehicle routing problem with charging time and variable travel time is developed to address some operational issues such as range limitation and charging demand. The model is solved by using genetic algorithm to obtain the routes, the vehicle departure time at the depot, and the charging plan. Meanwhile, a dynamic Dijkstra algorithm is applied to find the shortest path between any two adjacent nodes along the routes. To prevent the depletion of all battery power and ensure safe operation in transit, electric vehicles with insufficient battery power can be repeatedly recharged at charging stations. The fluctuations in travel time are implemented to reflect a dynamic traffic environment. In conclusion, a large and realistic case study with a road network in the Beijing urban area is conducted to evaluate the model performance and the solution technology and analyze the results.
Branch and price for the time-dependent vehicle routing problem with time windows
DEFF Research Database (Denmark)
Dabia, Said; Van Woensel, Tom; De Kok, Ton
2013-01-01
solution methods to the DM-TDVRPTW are based on (meta-)heuristics. The decomposition of an arc-based formulation leads to a setpartitioning problem as the master problem, and a time-dependent shortest path problem with resource constraints as the pricing problem. The master problem is solved by means...... of column generation, and a tailored labeling algorithm is used to solve the pricing problem. We introduce new dominance criteria that allow more label dominance. For our numerical results, we modified Solomon's data sets by adding time dependency. Our algorithm is able to solve about 63% of the instances......This paper presents a branch-and-price algorithm for the time-dependent vehicle routing problem with time windows (TDVRPTW). We capture road congestion by considering time-dependent travel times, i.e., depending on the departure time to a customer, a different travel time is incurred. We consider...
A set-covering based heuristic algorithm for the periodic vehicle routing problem.
Cacchiani, V; Hemmelmayr, V C; Tricoire, F
2014-01-30
We present a hybrid optimization algorithm for mixed-integer linear programming, embedding both heuristic and exact components. In order to validate it we use the periodic vehicle routing problem (PVRP) as a case study. This problem consists of determining a set of minimum cost routes for each day of a given planning horizon, with the constraints that each customer must be visited a required number of times (chosen among a set of valid day combinations), must receive every time the required quantity of product, and that the number of routes per day (each respecting the capacity of the vehicle) does not exceed the total number of available vehicles. This is a generalization of the well-known vehicle routing problem (VRP). Our algorithm is based on the linear programming (LP) relaxation of a set-covering-like integer linear programming formulation of the problem, with additional constraints. The LP-relaxation is solved by column generation, where columns are generated heuristically by an iterated local search algorithm. The whole solution method takes advantage of the LP-solution and applies techniques of fixing and releasing of the columns as a local search, making use of a tabu list to avoid cycling. We show the results of the proposed algorithm on benchmark instances from the literature and compare them to the state-of-the-art algorithms, showing the effectiveness of our approach in producing good quality solutions. In addition, we report the results on realistic instances of the PVRP introduced in Pacheco et al. (2011) [24] and on benchmark instances of the periodic traveling salesman problem (PTSP), showing the efficacy of the proposed algorithm on these as well. Finally, we report the new best known solutions found for all the tested problems.
A HYBRID GENETIC ALGORITHM IMPLEMENTATION FOR VEHICLE ROUTING PROBLEM WITH TIME WINDOWS
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Muhammad Faisal Ibrahim
2016-01-01
Full Text Available This article is related to approach development in order to determine the most appropriate route for bottled water delivery from warehouse to retail from particular boundaries such as a limit on number of vehicle, vehicle capacity, and time windows to each retail. A mathematical model of VRPTW is adopted to solve the problem. Malang is one of the drinking water production centers in Indonesia, definitely it will be difficult for the company to determine the optimal delivery route with the existing restrictions. In this research hybrid genetic algorithm is use to determine the route shipping companies with the Java programming language. After analyzing the results obtained show that the results of the implementation of hybrid genetic algorithm is better than the company actual route. Moreover, authors also analyze the effect the number of iterations for the computation time, and the influence the number of iterations for the fitness value or violation. This algorithm can be applied for the routing and the result obtained is an optimal solution
2015-03-26
Robbins, PhD Chair LTC Brian J. Lunday, PhD Member AFIT-ENS-MS-15-M-140 Abstract The United States Army uses Vendor Managed Inventory ( VMI ) replenishment...making decisions about vehicle routing and inventory resupply, typically under ven– dor-managed inventory ( VMI ) practices [7]. Traditionally, a...customer alerts a central vendor when resupply at its location is necessary. However, under VMI practices, a central vendor monitors the supply levels of
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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.
THE PERIODIC CAPACITATED ARC ROUTING PROBLEM LINEAR PROGRAMMING MODEL,METAHEURISTIC AND LOWER BOUNDS
Institute of Scientific and Technical Information of China (English)
Feng CHU; Nacima LABADI; Christian PRINS
2004-01-01
The Periodic Capacitated Arc Routing Problem (PCARP) generalizes the well known NP-hard Capacitated Arc Routing Problem (CARP) by extending the single period to multi-period horizon.The Capacitated Arc Routing Problem (CARP) is defined on an undirected network in which a fleet of identical vehicles is based at a depot node. A subset of edges, called tasks, must be serviced by a vehicle. The CARP consists of determining a set of feasible vehicle trips that minimizes the total cost of traversed edges. The PCARP involves the assignment of tasks to periods and the determination of vehicles trips in each period, to minimize the total cost on the whole horizon. This new problem arises in various real life applications such as waste collection, mail delivery, etc. In this paper, a new linear programming model and preliminary lower bounds based on graph transformation are proposed. A meta-heuristic approach - Scatter Search (SS) is developed for the PCARP and evaluated on a large variety of instances.
Determination of optimal self-drive tourism route using the orienteering problem method
Hashim, Zakiah; Ismail, Wan Rosmanira; Ahmad, Norfaieqah
2013-04-01
This paper was conducted to determine the optimal travel routes for self-drive tourism based on the allocation of time and expense by maximizing the amount of attraction scores assigned to each city involved. Self-drive tourism represents a type of tourism where tourists hire or travel by their own vehicle. It only involves a tourist destination which can be linked with a network of roads. Normally, the traveling salesman problem (TSP) and multiple traveling salesman problems (MTSP) method were used in the minimization problem such as determination the shortest time or distance traveled. This paper involved an alternative approach for maximization method which is maximize the attraction scores and tested on tourism data for ten cities in Kedah. A set of priority scores are used to set the attraction score at each city. The classical approach of the orienteering problem was used to determine the optimal travel route. This approach is extended to the team orienteering problem and the two methods were compared. These two models have been solved by using LINGO12.0 software. The results indicate that the model involving the team orienteering problem provides a more appropriate solution compared to the orienteering problem model.
A Hybrid Genetic Algorithm for Vehicle Routing Problem with Complex Constraints
Institute of Scientific and Technical Information of China (English)
CHEN Yan; LU Jun; LI Zeng-zhi
2006-01-01
Most research on the Vehicle Routing Problem (VRP) is focused on standard conditions, which is not suitable for specific cases. A Hybrid Genetic Algorithm is proposed to solve a Vehicle Routing Problem (VRP) with complex side constraints. A novel coding method is designed especially for side constraints. A greedy algorithm combined with a random algorithm is introduced to enable the diversity of the initial population, as well as a local optimization algorithm employed to improve the searching efficiency. In order to evaluate the performance, this mechanism has been implemented in an oil distribution center, the experimental and executing results show that the near global optimal solution can be easily and quickly obtained by this method, and the solution is definitely satisfactory in the VRP application.
Solving the Capacitated Vehicle Routing Problem Based on Improved Ant-clustering Algorithm
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Zhang Jiashan
2015-01-01
Full Text Available The capacitated vehicle routing problems (CVRP are NP-hard. Most approaches can solve small-scale case studies to optimality. Furthermore, they are time-consuming. To overcome the limitation, this paper presents a novel three-phase heuristic approach for the capacitated vehicle routing problem. The first phase aims to identify sets of cost-effective feasible clusters through an improved ant-clustering algorithm, in which the adaptive strategy is adopted. The second phase assigns clusters to vehicles and sequences them on each tour. The third phase orders nodes within clusters for every tour and genetic algorithm is used to order nodes within clusters. The simulation indicates the algorithm attains high quality results in a short time.
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.
The Problems in QoS Routing%QoS中的路由问题
Institute of Scientific and Technical Information of China (English)
彭孜; 曾家智; 周明天
2000-01-01
The next-greneration high-speed networks are expected to suppot a wide range of delay-sensitive multimedia applications. They need a different routing algorithm from the conventional one. The goal of the new algorithm is twofold: (1)satisfying the QoS requirements for every admitted connections,and(2)achieving global efficiency in resource utilization. Thus,most of problems in QoS routing area have multiple constraints which make them NP-Hard. Until now,the generally effcient algorithm has not been found. In this paper,we pose two algorithms for PCPO problems common in QoS communication,and analyze respective characteristics and uses.
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Ika Ayu Fajarwati
2012-09-01
Full Text Available Vehicle Routing Problem (VRP merupakan permasalahan optimasi kombinatorial kompleks yang memiliki peranan penting dalam manajemen sistem distribusi dengan tujuan meminimalkan biaya yang diperlukan, dimana penentuan biaya berkaitan dengan jarak dari rute yang ditempuh oleh armada distribusi. Ciri dari VRP yaitu penggunaan armada dengan kapasitas tertentu dan kegiatannya berpusat pada satu titik depot untuk melayani pelanggan pada titik-titik tertentu dengan jumlah permintaan yang diketahui. Kasus distribusi yang menggabungkan aktifitas pengiriman dan pengambilan produk termasuk dalam salah satu jenis VRP yaitu Vehicle Routing Problem Delivery and Pick-Up (VRP-DP. Banyak metode yang dapat digunakan untuk menyelesaikan permasalahan VRP-DP, salah satunya adalah metode optimasi metaheuristik yaitu Algoritma Differential Evolution yang akan diperkenalkan dalam penelitian ini. Hasil yang diharapkan nantinya adalah rute distribusi optimal untuk armada perusahaan sehingga menghasilkan jarak tempuh dan tentunya total biaya yang minimal dalam memenuhi semua permintaan pelanggan
The life and times of the Savings Method for Vehicle Routing Problems
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GK Rand
2009-12-01
Full Text Available Forty five 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 significant part of the research agenda nearly half a century later. Adaptations of their method are significant components in the analysis of the many different extensions to the problem that have been investigated. This paper provides the historical background to the development of the savings method and subsequent proposed variations to the basic savings formula and other improvements, and then charts the role the savings method has played in the investigation of VRPs with additional constraints. Some interesting examples of practical applications of the savings method are reported. Finally, comments are made on the use of the savings method in commercial routing packages.
Bounds in the generalized Weber problem under locational uncertainty
DEFF Research Database (Denmark)
Juel, Henrik
1981-01-01
An existing analysis of the bounds on the Weber problem solution under uncertainty is incorrect. For the generalized problem with arbitrary measures of distance, we give easily computable ranges on the bounds and state the conditions under which the exact values of the bounds can be found...
AN ALGORITHM FOR CONTINUOUS TYPE OPTIMAL SPHERICALFACILITY LOCATION PROBLEM
Institute of Scientific and Technical Information of China (English)
ZHANG Liping; WANG Changyu
1999-01-01
In this paper, we study the continuously spherical facilitylocation problem.(P)(minx∈S∫∫(x)=Ωφ(υ)cos-1(υTx)dΩ) We prove a hull property and optimality condition of the problem (P), andpropose an algorithm to solve (P). Global convergence is proved.
A Comparison of Homogeneous and Heterogeneous Vehicle Fleet Size in Green Vehicle Routing Problem
Moutaoukil, Abdelhamid; Neubert, Gilles; Derrouiche, Ridha
2014-01-01
Part 1: Knowledge-Based Sustainability; International audience; To balance a fragmented logistics organization, Small and Medium Enterprises have to find collective solutions to decrease their environmental impact. Especially when the demand at each producer takes the form of small packages and low quantities this paper examines the effect of the introduction of a consolidation center on the environmental issue. Therefore, the Fleet Size and Mix Vehicle Routing Problem (FSMVRP) was adapted in...
A Novel Heuristic Algorithm Based on Clark and Wright Algorithm for Green Vehicle Routing Problem
Mehdi Alinaghian; Zahra Kaviani; Siyavash Khaledan
2015-01-01
A significant portion of Gross Domestic Production (GDP) in any country belongs to the transportation system. Transportation equipment, in the other hand, is supposed to be great consumer of oil products. Many attempts have been assigned to the vehicles to cut down Greenhouse Gas (GHG). In this paper a novel heuristic algorithm based on Clark and Wright Algorithm called Green Clark and Wright (GCW) for Vehicle Routing Problem regarding to fuel consumption is presented. The objective function ...
MODELING AND SOLVING A RICH VEHICLE ROUTING PROBLEM FOR THE DELIVERY OF GOODS IN URBAN AREAS
José Ferreira de Souza Neto; Vitória Pureza
2016-01-01
ABSTRACT This work addresses a vehicle routing problem that aims at representing delivery operations of large volumes of products in dense urban areas. Inspired by a case study in a drinks producer and distributor, we propose a mathematical programming model and solution approaches that take into account costs with own and chartered vehicles, multiple deliverymen, time windows in customers, compatibility of vehicles and customers, time limitations for the circulation of large vehicles in city...
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Qi Hu
2013-04-01
Full Text Available State-of-the-art heuristic algorithms to solve the vehicle routing problem with time windows (VRPTW usually present slow speeds during the early iterations and easily fall into local optimal solutions. Focusing on solving the above problems, this paper analyzes the particle encoding and decoding strategy of the particle swarm optimization algorithm, the construction of the vehicle route and the judgment of the local optimal solution. Based on these, a hybrid chaos-particle swarm optimization algorithm (HPSO is proposed to solve VRPTW. The chaos algorithm is employed to re-initialize the particle swarm. An efficient insertion heuristic algorithm is also proposed to build the valid vehicle route in the particle decoding process. A particle swarm premature convergence judgment mechanism is formulated and combined with the chaos algorithm and Gaussian mutation into HPSO when the particle swarm falls into the local convergence. Extensive experiments are carried out to test the parameter settings in the insertion heuristic algorithm and to evaluate that they are corresponding to the data’s real-distribution in the concrete problem. It is also revealed that the HPSO achieves a better performance than the other state-of-the-art algorithms on solving VRPTW.
A Novel Joint Problem of Routing, Scheduling, and Variable-Width Channel Allocation in WMNs
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Chun-Cheng Lin
2014-01-01
Full Text Available This paper investigates a novel joint problem of routing, scheduling, and channel allocation for single-radio multichannel wireless mesh networks in which multiple channel widths can be adjusted dynamically through a new software technology so that more concurrent transmissions and suppressed overlapping channel interference can be achieved. Although the previous works have studied this joint problem, their linear programming models for the problem were not incorporated with some delicate constraints. As a result, this paper first constructs a linear programming model with more practical concerns and then proposes a simulated annealing approach with a novel encoding mechanism, in which the configurations of multiple time slots are devised to characterize the dynamic transmission process. Experimental results show that our approach can find the same or similar solutions as the optimal solutions for smaller-scale problems and can efficiently find good-quality solutions for a variety of larger-scale problems.
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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.
A Column Generation Approach to the Capacitated Vehicle Routing Problem with Stochastic Demands
DEFF Research Database (Denmark)
Christiansen, Christian Holk; Lysgaard, Jens
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....... 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...
Clique inequalities applied to the vehicle routing problem with time windows
DEFF Research Database (Denmark)
Spoorendonk, Simon; Desaulniers, Guy
2010-01-01
This work presents an exact branch-cut-and-price algorithm for the vehicle routing problem with time windows (VRPTW) where the well-known clique inequalities are used as cutting planes defined on the set partitioning master problem variables. It shows how these cutting planes affect the dominance......, to our knowledge, this is a first attempt at incorporating for the VRPTW a set of valid inequalities specialized for the set partitioning polytope. Computational results show that the use of clique inequalities improves the lower bound at the root node of the search tree and reduces the number of nodes...
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...
Tawanda’s non- iterative optimal tree algorithm for shortest route problems
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Trust Tawanda
2013-03-01
Full Text Available So many algorithms have been proposed to solve the shortest path in road networks, in this paper, an algorithm is developed to solve shortest route problems. The algorithm is being demonstrated through solving of various network problems. The principle of the algorithm consist in transforming the graph into a tree by means of arc and node replication, thereby expanding outwards from the source node considering all possible paths up to the destination node. The objective is to develop a method that can be applied in directed and non-directed graphs.
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Yan Sun
2015-09-01
Full Text Available Purpose: The purpose of study is to solve the multi-modal transportation routing planning problem that aims to select an optimal route to move a consignment of goods from its origin to its destination through the multi-modal transportation network. And the optimization is from two viewpoints including cost and time. Design/methodology/approach: In this study, a bi-objective mixed integer linear programming model is proposed to optimize the multi-modal transportation routing planning problem. Minimizing the total transportation cost and the total transportation time are set as the optimization objectives of the model. In order to balance the benefit between the two objectives, Pareto optimality is utilized to solve the model by gaining its Pareto frontier. The Pareto frontier of the model can provide the multi-modal transportation operator (MTO and customers with better decision support and it is gained by the normalized normal constraint method. Then, an experimental case study is designed to verify the feasibility of the model and Pareto optimality by using the mathematical programming software Lingo. Finally, the sensitivity analysis of the demand and supply in the multi-modal transportation organization is performed based on the designed case. Findings: The calculation results indicate that the proposed model and Pareto optimality have good performance in dealing with the bi-objective optimization. The sensitivity analysis also shows the influence of the variation of the demand and supply on the multi-modal transportation organization clearly. Therefore, this method can be further promoted to the practice. Originality/value: A bi-objective mixed integer linear programming model is proposed to optimize the multi-modal transportation routing planning problem. The Pareto frontier based sensitivity analysis of the demand and supply in the multi-modal transportation organization is performed based on the designed case.
A note on fixed point optimality criteria for the location problem with arbitrary norms: Reply
DEFF Research Database (Denmark)
Juel, Henrik; Love, Robert F.
1983-01-01
The single-facility location problem in continuous space is considered, with distances given by arbitrary norms. When distances are Euclidean, for many practical problems the optimal location of the new facility coincides with one of the existing facilities. This property carries over to problems...... with generalized distances. In this paper a necessary and sufficient condition for the location of an existing facility to be the optimal location of the new facility is developed. Some computational examples using the condition are given....
A modified ant colony optimization to solve multi products inventory routing problem
Wong, Lily; Moin, Noor Hasnah
2014-07-01
This study considers a one-to-many inventory routing problem (IRP) network consisting of a manufacturer that produces multi products to be transported to many geographically dispersed customers. We consider a finite horizon where a fleet of capacitated homogeneous vehicles, housed at a depot/warehouse, transport products from the warehouse to meet the demand specified by the customers in each period. The demand for each product is deterministic and time varying and each customer requests a distinct product. The inventory holding cost is product specific and is incurred at the customer sites. The objective is to determine the amount on inventory and to construct a delivery schedule that minimizes both the total transportation and inventory holding costs while ensuring each customer's demand is met over the planning horizon. The problem is formulated as a mixed integer programming problem and is solved using CPLEX 12.4 to get the lower and upper bound (best integer solution) for each problem considered. We propose a modified ant colony optimization (ACO) to solve the problem and the built route is improved by using local search. ACO performs better on large instances compared to the upper bound.
Sebastian Henn; André Scholz; Meike Stuhlmann; Gerhard Wäscher
2015-01-01
The Single-Picker Routing Problem deals with the determination of sequences according to which items have to be picked in a distribution warehouse and the identification of the corresponding paths which have to be travelled by human operators (order pickers). The Single-Picker Routing Problem represents a special case of the classic Traveling Salesman Problem (TSP) and, therefore, can also be modeled as a TSP. However, the picking area of a warehouse typically possesses a block layout, i.e. t...
The p-median Facility Location Problem and Solution Approaches
BASTI, MEHMET
2012-01-01
In today’s globalized and increasingly competitive environment, organizations’ need to implement successful strategies for supply chain management has become indispensable. Transportation costs within the supply chain comprise an important part of the organizations’ expenses. For this reason, the strategic selection of location is an issue that directly affects supply chain performance and costs. At this stage, it becomes very important to apply the latest and the best methods to the facility...
A robust approach to the missile defence location problem
Bloemen, A.A.F.; Evers, L.; Barros, A.I.; Monsuur, H.; Wagelmans, A.P.M.
2011-01-01
This paper proposes a model for determining a robust defence strategy against ballistic missile threat. Our approach takes into account a variety of possible future scenarios and different forms of robustness criteria, including the well-known absolute robustness criterion. We consider two problem
Approximability of the d-dimensional Euclidean capacitated vehicle routing problem
Khachay, Michael; Dubinin, Roman
2016-10-01
Capacitated Vehicle Routing Problem (CVRP) is the well known intractable combinatorial optimization problem, which remains NP-hard even in the Euclidean plane. Since the introduction of this problem in the middle of the 20th century, many researchers were involved into the study of its approximability. Most of the results obtained in this field are based on the well known Iterated Tour Partition heuristic proposed by M. Haimovich and A. Rinnoy Kan in their celebrated paper, where they construct the first Polynomial Time Approximation Scheme (PTAS) for the single depot CVRP in ℝ2. For decades, this result was extended by many authors to numerous useful modifications of the problem taking into account multiple depots, pick up and delivery options, time window restrictions, etc. But, to the best of our knowledge, almost none of these results go beyond the Euclidean plane. In this paper, we try to bridge this gap and propose a EPTAS for the Euclidean CVRP for any fixed dimension.
Robust Branch-and-Cut-and-Price for the Capacitated Vehicle Routing Problem
DEFF Research Database (Denmark)
Fukasawa, R.; Longo, H.; Lysgaard, Jens
2006-01-01
The best exact algorithms for the Capacitated Vehicle Routing Problem (CVRP) have been based on either branch-and-cut or Lagrangean relaxation/column generation. This paper presents an algorithm that combines both approaches: it works over the intersection of two polytopes, one associated...... with a traditional Lagrangean relaxation over q-routes, the other defined by bound, degree and capacity constraints. This is equivalent to a linear program with exponentially many variables and constraints that can lead to lower bounds that are superior to those given by previous methods. The resulting branch......-and-cut-and-price algorithm can solve to optimality all instances from the literature with up to 135 vertices. This more than doubles the size of the instances that can be consistently solved....
Intelligent Iterated Local Search Methods for Solving Vehicle Routing Problem with Different Fleets
Institute of Scientific and Technical Information of China (English)
无
2007-01-01
To solve vehicle routing problem with different fleets, two methodologies are developed. The first methodology adopts twophase strategy. In the first phase, the improved savings method is used to assign customers to appropriate vehicles. In the second phase, the iterated dynasearch algorithm is adopted to route each selected vehicle with the assigned customers. The iterated dynasearch algorithm combines dynasearch algorithm with iterated local search algorithm based on random kicks. The second methodplogy adopts the idea of cyclic transfer which is performed by using dynamic programming algorithm, and the iterated dynasearch algorithm is also embedded in it. The test results show that both methodologies generate better solutions than the traditional method, and the second methodology is superior to the first one.
Locating CVBEM collocation points for steady state heat transfer problems
Hromadka, T.V.
1985-01-01
The Complex Variable Boundary Element Method or CVBEM provides a highly accurate means of developing numerical solutions to steady state two-dimensional heat transfer problems. The numerical approach exactly solves the Laplace equation and satisfies the boundary conditions at specified points on the boundary by means of collocation. The accuracy of the approximation depends upon the nodal point distribution specified by the numerical analyst. In order to develop subsequent, refined approximation functions, four techniques for selecting additional collocation points are presented. The techniques are compared as to the governing theory, representation of the error of approximation on the problem boundary, the computational costs, and the ease of use by the numerical analyst. ?? 1985.
DEFF Research Database (Denmark)
Christensen, Jonas Mark; Røpke, Stefan
The Vehicle Routing Problem with Time Windows (VRPTW) consist of determining a set of feasible vehicle routes to deliver goods to a set of customers using a hierarchical objective; first minimising the number of vehicles used and, second, the total driving distance. A three-stage method is proposed...
A two-stage heuristic method for vehicle routing problem with split deliveries and pickups
Institute of Scientific and Technical Information of China (English)
Yong WANG; Xiao-lei MA; Yun-teng LAO; Hai-yan YU; Yong LIU
2014-01-01
The vehicle routing problem (VRP) is a well-known combinatorial optimization issue in transportation and logistics network systems. There exist several limitations associated with the traditional VRP. Releasing the restricted conditions of traditional VRP has become a research focus in the past few decades. The vehicle routing problem with split deliveries and pickups (VRPSPDP) is particularly proposed to release the constraints on the visiting times per customer and vehicle capacity, that is, to allow the deliveries and pickups for each customer to be simultaneously split more than once. Few studies have focused on the VRPSPDP problem. In this paper we propose a two-stage heuristic method integrating the initial heuristic algorithm and hybrid heuristic algorithm to study the VRPSPDP problem. To validate the proposed algorithm, Solomon benchmark datasets and extended Solomon benchmark datasets were modified to compare with three other popular algorithms. A total of 18 datasets were used to evaluate the effectiveness of the proposed method. The computational results indicated that the proposed algorithm is superior to these three algorithms for VRPSPDP in terms of total travel cost and average loading rate.
An Inverse Robust Optimisation Approach for a Class of Vehicle Routing Problems under Uncertainty
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Liang Sun
2016-01-01
Full Text Available There is a trade-off between the total penalty paid to customers (TPC and the total transportation cost (TTC in depot for vehicle routing problems under uncertainty (VRPU. The trade-off refers to the fact that the TTC in depot inevitably increases when the TPC decreases and vice versa. With respect to this issue, the vehicle routing problem (VRP with uncertain customer demand and travel time was studied to optimise the TPC and the TTC in depot. In addition, an inverse robust optimisation approach was proposed to solve this kind of VRPU by combining the ideas of inverse optimisation and robust optimisation so as to improve both the TPC and the TTC in depot. The method aimed to improve the corresponding TTC of the robust optimisation solution under the minimum TPC through minimising the adjustment of benchmark road transportation cost. According to the characteristics of the inverse robust optimisation model, a genetic algorithm (GA and column generation algorithm are combined to solve the problem. Moreover, 39 test problems are solved by using an inverse robust optimisation approach: the results show that both the TPC and TTC obtained by using the inverse robust optimisation approach are less than those calculated using a robust optimisation approach.
Institute of Scientific and Technical Information of China (English)
石兆; 符卓
2013-01-01
In order to solve the problem of food cold chain logistics distribution system optimization problem, for perishable goods characteristics, combined with the distribution network time-varying characteristics to analyse travel time, this paper designed satisfaction degree function according to service time windows and established the simulation model under time-dependent. It designed the two-phase solution of preoptimization phase and real-time optimization phase, by using the decomposition method, it decomposed the problem, designed the minimum envelope clustering analysis method and tabu search algorithm to solve the problem. Simulation results show the effectiveness of the model and algorithm of practical value.%为解决食品冷链配送系统优化问题,针对易腐品特性,结合配送网络时变特征进行行程时间分析,根据服务时间窗设计满意度函数,建立时变条件下的仿真模型；采用“预优化阶段+实时优化阶段”两阶段求解策略,利用分解法进行问题分解,设计最小包络聚类分析方法与混合遗传算法求解.仿真计算验证了模型和算法的有效性与研究的实用价值.
A note on fixed point optimality criteria for the location problem with arbitrary norms: Reply
DEFF Research Database (Denmark)
Juel, Henrik; Love, Robert F.
1983-01-01
The single-facility location problem in continuous space is considered, with distances given by arbitrary norms. When distances are Euclidean, for many practical problems the optimal location of the new facility coincides with one of the existing facilities. This property carries over to problems...
A Novel Heuristic Algorithm Based on Clark and Wright Algorithm for Green Vehicle Routing Problem
Directory of Open Access Journals (Sweden)
Mehdi Alinaghian
2015-08-01
Full Text Available A significant portion of Gross Domestic Production (GDP in any country belongs to the transportation system. Transportation equipment, in the other hand, is supposed to be great consumer of oil products. Many attempts have been assigned to the vehicles to cut down Greenhouse Gas (GHG. In this paper a novel heuristic algorithm based on Clark and Wright Algorithm called Green Clark and Wright (GCW for Vehicle Routing Problem regarding to fuel consumption is presented. The objective function is fuel consumption, drivers, and the usage of vehicles. Being compared to exact methods solutions for small-sized problems and to Differential Evolution (DE algorithm solutions for large-scaled problems, the results show efficient performance of the proposed GCW algorithm.
Metaheuristics for multi products inventory routing problem with time varying demand
Moin, Noor Hasnah; Ab Halim, Huda Zuhrah; Yuliana, Titi
2014-07-01
This paper addresses the inventory routing problem (IRP) with a many-to-one distribution network, consisting of a single depot, an assembly plant, and geographically dispersed suppliers where a capacitated homogeneous vehicle delivers a distinct product from the suppliers to fulfill the demand specified by the assembly plant over the planning horizon. The inventory holding cost is assumed to be product specific and only incurred at the assembly plant. Two metaheuristics comprise of artificial bee colony (ABC) and scatter search (SS) algorithms are proposed to solve the problem. Computational testing on instances which represents small, medium, and large data sets show that the ABC algorithm performs slightly better when compared the SS overall except for fifty suppliers problems.
Bhanja, Urmila; Roy, Rajarshi; 10.5121/ijcnc.2010.2209
2010-01-01
We present an evolutionary programming algorithm for solving the dynamic routing and wavelength assignment (DRWA) problem in optical wavelength-division multiplexing (WDM) networks under wavelength continuity constraint. We assume an ideal physical channel and therefore neglect the blocking of connection requests due to the physical impairments. The problem formulation includes suitable constraints that enable the algorithm to balance the load among the individuals and thus results in a lower blocking probability and lower mean execution time than the existing bio-inspired algorithms available in the literature for the DRWA problems. Three types of wavelength assignment techniques, such as First fit, Random, and Round Robin wavelength assignment techniques have been investigated here. The ability to guarantee both low blocking probability without any wavelength converters and small delay makes the improved algorithm very attractive for current optical switching networks.
A sequential insertion heuristic for the initial solution to a constrained vehicle routing problem
Directory of Open Access Journals (Sweden)
JW Joubert
2006-06-01
Full Text Available The Vehicle Routing Problem (VRP is a well-researched problem in the Operations Research literature. It is the view of the authors of this paper that the various VRP variants have been researched in isolation. This paper embodies an attempt to integrate three specific variants of the VRP, namely the VRP with multiple time windows, the VRP with a heterogeneous fleet, and the VRP with double scheduling, into an initial solution algorithm. The proposed initial solution algorithm proves feasible for the integration, while the newly introduced concept of time window compatibility decreases the computational burden when using benchmark data sets from literature as a basis for efficiency testing. The algorithm also improves the quality of the initial solution for a number of problem classes.
A hybrid ACO/PSO based algorithm for QoS multicast routing problem
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Manoj Kumar Patel
2014-03-01
Full Text Available Many Internet multicast applications such as videoconferencing, distance education, and online simulation require to send information from a source to some selected destinations. These applications have stringent Quality-of-Service (QoS requirements that include delay, loss rate, bandwidth, and delay jitter. This leads to the problem of routing multicast traffic satisfying QoS requirements. The above mentioned problem is known as the QoS constrained multicast routing problem and is NP Complete. In this paper, we present a swarming agent based intelligent algorithm using a hybrid Ant Colony Optimization (ACO/Particle Swarm Optimization (PSO technique to optimize the multicast tree. The algorithm starts with generating a large amount of mobile agents in the search space. The ACO algorithm guides the agents’ movement by pheromones in the shared environment locally, and the global maximum of the attribute values are obtained through the random interaction between the agents using PSO algorithm. The performance of the proposed algorithm is evaluated through simulation. The simulation results reveal that our algorithm performs better than the existing algorithms.
On the Miller-Tucker-Zemlin Based Formulations for the Distance Constrained Vehicle Routing Problems
Kara, Imdat
2010-11-01
Vehicle Routing Problem (VRP), is an extension of the well known Traveling Salesman Problem (TSP) and has many practical applications in the fields of distribution and logistics. When the VRP consists of distance based constraints it is called Distance Constrained Vehicle Routing Problem (DVRP). However, the literature addressing on the DVRP is scarce. In this paper, existing two-indexed integer programming formulations, having Miller-Tucker-Zemlin based subtour elimination constraints, are reviewed. Existing formulations are simplified and obtained formulation is presented as formulation F1. It is shown that, the distance bounding constraints of the formulation F1, may not generate the distance traveled up to the related node. To do this, we redefine the auxiliary variables of the formulation and propose second formulation F2 with new and easy to use distance bounding constraints. Adaptation of the second formulation to the cases where new restrictions such as minimal distance traveled by each vehicle or other objectives such as minimizing the longest distance traveled is discussed.
A memory structure adapted simulated annealing algorithm for a green vehicle routing problem.
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.
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%.
A Framing Link Based Tabu Search Algorithm for Large-Scale Multidepot Vehicle Routing Problems
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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.
Aggregation and non aggregation techniques for large facility location problems: A survey
Directory of Open Access Journals (Sweden)
Irawan Chandra Ade
2015-01-01
Full Text Available A facility location problem is concerned with determining the location of some useful facilities in such a way so to fulfil one or a few objective functions and constraints. We survey those problems where, in the presence of a large number of customers, some form of aggregation may be required. In addition, a review on conditional location problems where some (say q facilities already exist in the study area is presented.
Solving Minimal Covering Location Problems with Single and Multiple Node Coverage
Directory of Open Access Journals (Sweden)
Darko DRAKULIĆ
2016-12-01
Full Text Available Location science represents a very attractiveresearch field in combinatorial optimization and it is in expansion in last five decades. The main objective of location problems is determining the best position for facilities in a given set of nodes.Location science includes techniques for modelling problemsand methods for solving them. This paper presents results of solving two types of minimal covering location problems, with single and multiple node coverage, by using CPLEX optimizer and Particle Swarm Optimization method.
Improved Fractal Space Filling Curves Hybrid Optimization Algorithm for Vehicle Routing Problem.
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.
A multiple ship routing and speed optimization problem under time, cost and environmental objectives
DEFF Research Database (Denmark)
Wen, M.; Pacino, Dario; Kontovas, C.A.
2017-01-01
The purpose of this paper is to investigate a multiple ship routing and speed optimization problem under time, cost and environmental objectives. A branch and price algorithm as well as a constraint programming model are developed that consider (a) fuel consumption as a function of payload, (b......) fuel price as an explicit input, (c) freight rate as an input, and (d) in-transit cargo inventory costs. The alternative objective functions are minimum total trip duration, minimum total cost and minimum emissions. Computational experience with the algorithm is reported on a variety of scenarios....
The problem of the availability of nautical charts and publications on the Northern Sea Route
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Pastusiak Tadeusz
2015-03-01
Full Text Available Statistical studies of marine accidents and unfortunate events in ice-covered areas in 1995–2004 and 2004–2011 showed a general lack of information from the area under the jurisdiction of the Russian Federation. The author’s research for the period 2004–2011 showed a large number of unfortunate events caused by lack of adequate provision of nautical charts, shortage of accurate position systems on board vessels as well as weak technical condition of these vessels. The author examined the problem of navigation safety on the Northern Sea Route in terms of availability of the official nautical charts and publications.
Topology aggregation with multiple QoS parameters for scalable routing problem
Institute of Scientific and Technical Information of China (English)
LUO Yong-jun; SHI Ming-hong; BAI Ying-cai
2005-01-01
In this paper, we investigate the problem of topology aggregation in QoS-based routing. We propose a new algorithm to perform full-mesh and modified-star aggregation, which is simple and effective in a network with additive and concave parameters constrained. The time complexity is O( b2 ) , where b is the number of border nodes. We extend the algorithm to topology aggregation with multi-parameters constrained. The simulation results show that our algorithm has very good performance in terms of success ratio.
Vehicle Routing Problem Solving Method for a Cooperative Logistics Network by Using Multi-Stage GA
Onoyama, Takashi; Maekawa, Takuya; Kubota, Sen; Tsuruta, Setsuo; Komoda, Norihisa
A GA applied VRP (Vehicle Routing Problem) solving-method which realizes optimization of a cooperative logistics network is proposed. For this optimization a VRP solving-method that can obtain human expert-level solution, which realizes steady logistics operation, in interactive response time is required. The multi-stage GA enables to obtain the accurate solution under both hard and weak time constraints in interactive response time. Moreover, to realize the stable logistics operation, the daily fluctuation of shipping volume is taken into the fitness value of each individual in GA. The experimental result reveals the proposed method obtains the accurate solution that realizes the stable operation in interactive response time.
MODELING AND SOLVING A RICH VEHICLE ROUTING PROBLEM FOR THE DELIVERY OF GOODS IN URBAN AREAS
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José Ferreira de Souza Neto
Full Text Available ABSTRACT This work addresses a vehicle routing problem that aims at representing delivery operations of large volumes of products in dense urban areas. Inspired by a case study in a drinks producer and distributor, we propose a mathematical programming model and solution approaches that take into account costs with own and chartered vehicles, multiple deliverymen, time windows in customers, compatibility of vehicles and customers, time limitations for the circulation of large vehicles in city centers and multiple daily trips. Results with instances based on real data provided by the company highlight the potential of applicability of some of the proposed methods.
Improved Fractal Space Filling Curves Hybrid Optimization Algorithm for Vehicle Routing Problem
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Yi-xiang Yue
2015-01-01
Full Text Available 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.
Improved Fractal Space Filling Curves Hybrid Optimization Algorithm for Vehicle Routing Problem
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. PMID:26167171
Energy Technology Data Exchange (ETDEWEB)
Gendreau, M.; Seguin, R.; Laporte, G.
1995-10-01
This paper considers a version of the stochastic vehicle routing problem where customers are present with some probability and have random demands. A tabu search heuristic is developed for this problem. Comparisons with known optimal solutions indicate that the heuristic solves the problem to optimality in the vast majority of cases and deviations from optimality are almost always small.
Directory of Open Access Journals (Sweden)
Subbaraj Potti
2011-01-01
Full Text Available Problem statement: A new multi-objective approach, Strength Pareto Evolutionary Algorithm (SPEA, is presented in this paper to solve the shortest path routing problem. The routing problem is formulated as a multi-objective mathematical programming problem which attempts to minimize both cost and delay objectives simultaneously. Approach: SPEA handles the shortest path routing problem as a true multi-objective optimization problem with competing and noncommensurable objectives. Results: SPEA combines several features of previous multi-objective evolutionary algorithms in a unique manner. SPEA stores nondominated solutions externally in another continuously-updated population and uses a hierarchical clustering algorithm to provide the decision maker with a manageable pareto-optimal set. SPEA is applied to a 20 node network as well as to large size networks ranging from 50-200 nodes. Conclusion: The results demonstrate the capabilities of the proposed approach to generate true and well distributed pareto-optimal nondominated solutions.
A new algorithm for solving the inventory routing problem with direct shipment
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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.
Chen, Xianshun; Feng, Liang; Ong, Yew Soon
2012-07-01
In this article, we proposed a self-adaptive memeplex robust search (SAMRS) for finding robust and reliable solutions that are less sensitive to stochastic behaviours of customer demands and have low probability of route failures, respectively, in vehicle routing problem with stochastic demands (VRPSD). In particular, the contribution of this article is three-fold. First, the proposed SAMRS employs the robust solution search scheme (RS 3) as an approximation of the computationally intensive Monte Carlo simulation, thus reducing the computation cost of fitness evaluation in VRPSD, while directing the search towards robust and reliable solutions. Furthermore, a self-adaptive individual learning based on the conceptual modelling of memeplex is introduced in the SAMRS. Finally, SAMRS incorporates a gene-meme co-evolution model with genetic and memetic representation to effectively manage the search for solutions in VRPSD. Extensive experimental results are then presented for benchmark problems to demonstrate that the proposed SAMRS serves as an efficable means of generating high-quality robust and reliable solutions in VRPSD.
Jawarneh, Sana; Abdullah, Salwani
2015-01-01
This paper presents a bee colony optimisation (BCO) algorithm to tackle the vehicle routing problem with time window (VRPTW). The VRPTW involves recovering an ideal set of routes for a fleet of vehicles serving a defined number of customers. The BCO algorithm is a population-based algorithm that mimics the social communication patterns of honeybees in solving problems. The performance of the BCO algorithm is dependent on its parameters, so the online (self-adaptive) parameter tuning strategy is used to improve its effectiveness and robustness. Compared with the basic BCO, the adaptive BCO performs better. Diversification is crucial to the performance of the population-based algorithm, but the initial population in the BCO algorithm is generated using a greedy heuristic, which has insufficient diversification. Therefore the ways in which the sequential insertion heuristic (SIH) for the initial population drives the population toward improved solutions are examined. Experimental comparisons indicate that the proposed adaptive BCO-SIH algorithm works well across all instances and is able to obtain 11 best results in comparison with the best-known results in the literature when tested on Solomon's 56 VRPTW 100 customer instances. Also, a statistical test shows that there is a significant difference between the results.
Modified artificial bee colony for the vehicle routing problems with time windows.
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.
Implementation Weather-Type Models of Capacitated Arc Routing Problem via Heuristics
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Zuhaimy Ismail
2011-01-01
Full Text Available Problem statement: In this study, we introduced a new and real-life condition of Capacitated Arc Routing Problem (CARP, a model that represents vehicles operation in waste collection. In general, we studied the element of rain drops that affected the collected waste weight in total by imposed a new variable namely rainy weight age. In rainy days, the household refusals did not increase in volumes, but in weights due to rain drops. Consequently, this matter thus burdened vehicles capacity and prolonged its operation time. This dynamic variable thus changes the initial CARP model where the existing model did not consider other external elements that have effected onto the model. Approach: Then we developed and enhanced CARP by integrating stochastic demand and time windows to suit the models with our specific case. Results: Objectively, CARP with stochastic demand (CARPSD and CARP with time windows (CARPTW were designed to minimize the total routing cost and number of trips for a vehicle. Our approach is to design CARP models in almost likely to road layout in residential area and graphically this model is called mesh network. We also developed a constructive heuristic that is called nearest procedure based on highest demand/cost (NPHDC and work in conjunction with switching rules to search the feasible solution. Conclusion: Our preliminary results show a higher cost and more trips are needed when the vehicle operates in rainy day compared to normal day operation.
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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.
Formulations and exact algorithms for the vehicle routing problem with time windows
DEFF Research Database (Denmark)
Kallehauge, Brian
2008-01-01
In this paper we review the exact algorithms proposed in the last three decades for the solution of the vehicle routing problem with time windows (VRPTW). The exact algorithms for the VRPTW are in many aspects inherited from work on the traveling salesman problem (TSP). In recognition of this fact...... this paper is structured relative to four seminal papers concerning the formulation and exact solution of the TSP, i.e. the arc formulation, the arc-node formulation, the spanning tree formulation, and the path formulation. We give a detailed analysis of the formulations of the VRPTW and a review...... with the analysis of the polyhedral structure of the VRPTW. We conclude by examining possible future lines of research in the area of the VRPTW....
Research on cultural algorithm for solving routing problem of mobile agent
Institute of Scientific and Technical Information of China (English)
无
2008-01-01
The key idea behind cultural algorithm is to explicitly acquire problem-solving knowledge from the evolving population and in return apply that knowledge to guide the search. In this article, cultural algorithm-simulated annealing is proposed to solve the routing problem of mobile agent. The optimal individual is accepted to improve the belief space's evolution of cultural algorithms by simulated annealing. The step size in search is used as situational knowledge to guide the search of optimal solution in the population space. Because of this feature, the search time is reduced. Experimental results show that the algorithm proposed in this article can ensure the quality of optimal solutions, and also has better convergence speed. The operation efficiency of the system is considerably improved.
Application of Modified Ant Colony Optimization (MACO for Multicast Routing Problem
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Sudip Kumar Sahana
2016-04-01
Full Text Available It is well known that multicast routing is combinatorial problem finds the optimal path between source destination pairs. Traditional approaches solve this problem by establishment of the spanning tree for the network which is mapped as an undirected weighted graph. This paper proposes a Modified Ant Colony Optimization (MACO algorithm which is based on Ant Colony System (ACS with some modification in the configuration of starting movement and in local updation technique to overcome the basic limitations of ACS such as poor initialization and slow convergence rate. It is shown that the proposed Modified Ant Colony Optimization (MACO shows better convergence speed and consumes less time than the conventional ACS to achieve the desired solution.
Wang, Jiahai; Zhou, Ying; Wang, Yong; Zhang, Jun; Chen, C L Philip; Zheng, Zibin
2016-03-01
This paper investigates a practical variant of the vehicle routing problem (VRP), called VRP with simultaneous delivery and pickup and time windows (VRPSDPTW), in the logistics industry. VRPSDPTW is an important logistics problem in closed-loop supply chain network optimization. VRPSDPTW exhibits multiobjective properties in real-world applications. In this paper, a general multiobjective VRPSDPTW (MO-VRPSDPTW) with five objectives is first defined, and then a set of MO-VRPSDPTW instances based on data from the real-world are introduced. These instances represent more realistic multiobjective nature and more challenging MO-VRPSDPTW cases. Finally, two algorithms, multiobjective local search (MOLS) and multiobjective memetic algorithm (MOMA), are designed, implemented and compared for solving MO-VRPSDPTW. The simulation results on the proposed real-world instances and traditional instances show that MOLS outperforms MOMA in most of instances. However, the superiority of MOLS over MOMA in real-world instances is not so obvious as in traditional instances.
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
for defining the edge sets are discussed and formulated. Both the multigraph case and the direct path case are described, and mixed-integer-programming formulations of the problem are presented for both cases. A solution method based on branch-price-and-cut is applied to the direct path case. The computational......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 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...
The Time-Dependent Multiple-Vehicle Prize-Collecting Arc Routing Problem
DEFF Research Database (Denmark)
Black, Daniel; Eglese, Richard; Wøhlk, Sanne
2015-01-01
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......-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...... information. Both algorithms are capable of finding good solutions, though the Tabu Search approach generally shows better performance for large instances whereas the VNS is superior for small instances. We discuss the structural differences of the implementation of the algorithms which explain these results....
Geiger, Martin Josef
2008-01-01
The article describes an investigation of the effectiveness of genetic algorithms for multi-objective combinatorial optimization (MOCO) by presenting an application for the vehicle routing problem with soft time windows. The work is motivated by the question, if and how the problem structure influences the effectiveness of different configurations of the genetic algorithm. Computational results are presented for different classes of vehicle routing problems, varying in their coverage with time windows, time window size, distribution and number of customers. The results are compared with a simple, but effective local search approach for multi-objective combinatorial optimization problems.
Kumar, Rakesh; Chandrawat, Rajesh Kumar; Garg, B. P.; Joshi, Varun
2017-07-01
Opening the new firm or branch with desired execution is very relevant to facility location problem. Along the lines to locate the new ambulances and firehouses, the government desires to minimize average response time for emergencies from all residents of cities. So finding the best location is biggest challenge in day to day life. These type of problems were named as facility location problems. A lot of algorithms have been developed to handle these problems. In this paper, we review five algorithms that were applied to facility location problems. The significance of clustering in facility location problems is also presented. First we compare Fuzzy c-means clustering (FCM) algorithm with alternating heuristic (AH) algorithm, then with Particle Swarm Optimization (PSO) algorithms using different type of distance function. The data was clustered with the help of FCM and then we apply median model and min-max problem model on that data. After finding optimized locations using these algorithms we find the distance from optimized location point to the demanded point with different distance techniques and compare the results. At last, we design a general example to validate the feasibility of the five algorithms for facilities location optimization, and authenticate the advantages and drawbacks of them.
An approximation algorithm for a facility location problem with stochastic demands
Bumb, A.F.; van Ommeren, Jan C.W.
2004-01-01
In this article we propose, for any $\\epsilon>0$, a $2(1+\\epsilon)$-approximation algorithm for a facility location problem with stochastic demands. This problem can be described as follows. There are a number of locations, where facilities may be opened and a number of demand points, where requests
An improved Lagrangian relaxation and dual ascent approach to facility location problems
DEFF Research Database (Denmark)
Jörnsten, Kurt; Klose, Andreas
2016-01-01
method for optimizing both the semi-Lagrangian dual function as well as its simplified form for the case of a generic discrete facility location problem and apply the method to the uncapacitated facility location problem. Our computational results show that the method generally only requires a very few...
An approximation algorithm for a facility location problem with stochastic demands
Bumb, A.F.; Ommeren, van J.C.W.
2004-01-01
In this article we propose, for any $\\epsilon>0$, a $2(1+\\epsilon)$-approximation algorithm for a facility location problem with stochastic demands. This problem can be described as follows. There are a number of locations, where facilities may be opened and a number of demand points, where requests
An impact of some parameters on correctness of the location problem solution
Directory of Open Access Journals (Sweden)
Marta JANÁČKOVÁ
2008-01-01
Full Text Available This paper deals with the modifications of customer demands and with the impact of modifications of customer demands on the location of supply centers. The solution of the location problem with exactly p location is sought. During the computation the penalty constant is used very often. Accumulation of the penalty values in the same variable causes the memory overflow. To eliminate this defect, we use the coefficient of the proportionality in some parameters of the location problem. We find how the coefficient of the proportionality influences the accuracy of the final result. The obtained results can help to solve the problem of the distribution systems design.
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.
Polynomial Size Formulations for the Distance and Capacity Constrained Vehicle Routing Problem
Kara, Imdat; Derya, Tusan
2011-09-01
The Distance and Capacity Constrained Vehicle Routing Problem (DCVRP) is an extension of the well known Traveling Salesman Problem (TSP). DCVRP arises in distribution and logistics problems. It would be beneficial to construct new formulations, which is the main motivation and contribution of this paper. We focused on two indexed integer programming formulations for DCVRP. One node based and one arc (flow) based formulation for DCVRP are presented. Both formulations have O(n2) binary variables and O(n2) constraints, i.e., the number of the decision variables and constraints grows with a polynomial function of the nodes of the underlying graph. It is shown that proposed arc based formulation produces better lower bound than the existing one (this refers to the Water's formulation in the paper). Finally, various problems from literature are solved with the node based and arc based formulations by using CPLEX 8.0. Preliminary computational analysis shows that, arc based formulation outperforms the node based formulation in terms of linear programming relaxation.
Directory of Open Access Journals (Sweden)
Omprakash Kaiwartya
2015-01-01
Full Text Available A multiobjective dynamic vehicle routing problem (M-DVRP has been identified and a time seed based solution using particle swarm optimization (TS-PSO for M-DVRP has been proposed. M-DVRP considers five objectives, namely, geographical ranking of the request, customer ranking, service time, expected reachability time, and satisfaction level of the customers. The multiobjective function of M-DVRP has four components, namely, number of vehicles, expected reachability time, and profit and satisfaction level. Three constraints of the objective function are vehicle, capacity, and reachability. In TS-PSO, first of all, the problem is partitioned into smaller size DVRPs. Secondly, the time horizon of each smaller size DVRP is divided into time seeds and the problem is solved in each time seed using particle swarm optimization. The proposed solution has been simulated in ns-2 considering real road network of New Delhi, India, and results are compared with those obtained from genetic algorithm (GA simulations. The comparison confirms that TS-PSO optimizes the multiobjective function of the identified problem better than what is offered by GA solution.
Directory of Open Access Journals (Sweden)
Satria Nur Alam
2012-09-01
Full Text Available Seiring dengan bertambahnya jumlah kendaraan setiap tahun, akan mempengaruhi konsumsi bahan bakar yang dibutuhkan. Tingginya kebutuhan bahan bakar di Indonesia didominasi oleh jenis bahan bakar premium. Persentase konsumsi bahan bakar premium di daerah Jawa-Bali mencapai 59% dari kuota premium nasional. Besarnya persentase kebutuhan akan bahan bakar premium, menyebabkan manajemen distribusi menjadi hal krusial yang perlu ditingkatkan secara berkala. Depo yang berperan sebagai supplier terhadap retailer -yang dalam studi kasus ini adalah SPBU- diusulkan menerapkan model Vendor Managed Inventory (VMI, yaitu proses pengadaan barang dimana supplier mengelola inventori dari retailernya. VMI memiliki salah satu perencanaan yaitu Inventory Routing Problem (IRP, IRP merupakan suatu bentuk perencanaan berbasis vendor hasil perpaduan antara Inventory Management dengan Inventory Routing yang mengatur kuantitas pengiriman dan retailer mana yang harus dikunjungi dalam suatu waktu perencanaan dalam jangka waktu tertentu yang bersifat terbatas (finite planning horizon. Dengan hasil akhir berupa penjadwalan, perencanaan model IRP mempertimbangkan jarak supplier-retailer dan biaya stockout yang mungkin terjadi pada retailer, sehingga diharapkan pengiriman optimal dan tidak terjadi stockout pada pos-pos penjualan bahan bakar.
Directory of Open Access Journals (Sweden)
P. L. N. U. Cooray
2017-01-01
Full Text Available During the last decade, tremendous focus has been given to sustainable logistics practices to overcome environmental concerns of business practices. Since transportation is a prominent area of logistics, a new area of literature known as Green Transportation and Green Vehicle Routing has emerged. Vehicle Routing Problem (VRP has been a very active area of the literature with contribution from many researchers over the last three decades. With the computational constraints of solving VRP which is NP-hard, metaheuristics have been applied successfully to solve VRPs in the recent past. This is a threefold study. First, it critically reviews the current literature on EMVRP and the use of metaheuristics as a solution approach. Second, the study implements a genetic algorithm (GA to solve the EMVRP formulation using the benchmark instances listed on the repository of CVRPLib. Finally, the GA developed in Phase 2 was enhanced through machine learning techniques to tune its parameters. The study reveals that, by identifying the underlying characteristics of data, a particular GA can be tuned significantly to outperform any generic GA with competitive computational times. The scrutiny identifies several knowledge gaps where new methodologies can be developed to solve the EMVRPs and develops propositions for future research.
A Privacy-Preserving Prediction Method for Human Travel Routes
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Wen-Chen Hu
2014-12-01
Full Text Available This paper proposes a kind of location-based research, human travel route prediction, which is to predict the track of a subject's future movements. The proposed method works as follows. The mobile user sends his/her current route along with several dummy routes to the server by using a 3D route matrix, which encodes a set of routes. The server restores the routes from the 3D matrix and matches the restored routes to the saved routes. The predicted route is found as the trunk of the tree, which is built by superimposing the matching results. The server then sends the predicted routes back to the user, who will apply the predicted route to a real-world problem such as traffic control and planning. Preliminary experimental results show the proposed method successfully predicts human travel routes based on current and previous routes. User privacy is also rigorously protected by using a simple method of dummy routes.
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.
Improved Multi-Agent System for the Vehicle Routing Problem with Time Windows
Institute of Scientific and Technical Information of China (English)
DAN Zhenggang; CAI Linning; ZHENG Li
2009-01-01
The vehicle routing problem with time windows (VRPTW) involves assigning a fleet of limited ca-pacity vehicles to serve a set of customers without violating the capacity and time constraints. This paper presents a multi-agent model system for the VRPTW based on the internal behavior of agents and coordina-tion among the agents. The system presents a formal view of coordination using the traditional contract-net protocol (CNP) that relies on the basic loop of agent behavior for order receiving, order announcement, bid calculation, and order scheduling followed by order execution. An improved CNP method based on a vehicle selection strategy is used to reduce the number of negotiations and the negotiation time. The model is vali-dated using Solomon's benchmarks, with the results showing that the improved CNP uses only 30% as many negotiations and only 70% of the negotiation time of the traditional CNP.
A hybrid genetic algorithm for route optimization in the bale collecting problem
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C. Gracia
2013-06-01
Full Text Available The bale collecting problem (BCP appears after harvest operations in grain and other crops. Its solution defines the sequence of collecting bales which lie scattered over the field. Current technology on navigation-aid systems or auto-steering for agricultural vehicles and machines, is able to provide accurate data to make a reliable bale collecting planning. This paper presents a hybrid genetic algorithm (HGA approach to address the BCP pursuing resource optimization such as minimizing non-productive time, fuel consumption, or distance travelled. The algorithmic route generation provides the basis for a navigation tool dedicated to loaders and bale wagons. The approach is experimentally tested on a set of instances similar to those found in real situations. In particular, comparative results show an average improving of a 16% from those obtained by previous heuristics.