#### Sample records for arc routing problem

1. Capacitated arc routing problem and its extensions in waste collection

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.

2. Capacitated arc routing problem and its extensions in waste collection

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

3. The time-dependent prize-collecting arc routing problem

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...

4. An evolutionary algorithm for the capacitated arc routing problem.

Dalessandro Soares Vianna

2006-08-01

Full Text Available The Capacitated Arc Routing Problem (CARP consists of visiting a subset of edges of the graph that describes the problem. CARP applications include urban waste collection and inspection of power lines. The CARP is NP-hard, even in the single-vehicle case (called Rural Postman Problem. In this case, the use of metaheuristics is an efficient solution strategy. This paper proposes a hybrid genetic algorithm for the CARP, which is tested on available instances of the literature. The results obtained until now show the effectiveness of the proposed algorithm when it is compared with lower bounds described in the literature.

5. Solving Arc Routing Problems Using the Lin-Kernighan-Helsgaun Algorithm

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...

6. A global repair operator for capacitated arc routing problem.

Mei, Yi; Tang, Ke; Yao, Xin

2009-06-01

Capacitated arc routing problem (CARP) has attracted much attention during the last few years due to its wide applications in real life. Since CARP is NP-hard and exact methods are only applicable for small instances, heuristics and metaheuristic methods are widely adopted when solving CARP. This paper demonstrates one major disadvantage encountered by traditional search algorithms and proposes a novel operator named global repair operator (GRO) to address it. We further embed GRO in a recently proposed tabu search algorithm (TSA) and apply the resultant repair-based tabu search (RTS) algorithm to five well-known benchmark test sets. Empirical results suggest that RTS not only outperforms TSA in terms of quality of solutions but also converges to the solutions faster. Moreover, RTS is also competitive with a number of state-of-the-art approaches for CARP. The efficacy of GRO is thereby justified. More importantly, since GRO is not specifically designed for the referred TSA, it might be a potential tool for improving any existing method that adopts the same solution representation. PMID:19211356

7. A Branch-and-Price Algorithm for the Capacitated Arc Routing Problem with Stochastic Demands

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 pro...... problem. Computational results are reported....

8. A mathematical modeling proposal for a Multiple Tasks Periodic Capacitated Arc Routing Problem

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.

9. THE PERIODIC CAPACITATED ARC ROUTING PROBLEM LINEAR PROGRAMMING MODEL,METAHEURISTIC AND LOWER BOUNDS

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.

10. Lower and Upper Bounds for the Node, Edge, and Arc Routing Problem

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...... 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 instances of all three benchmarks. For two of the instances, the gap is closed....

11. Implementation Weather-Type Models of Capacitated Arc Routing Problem via Heuristics

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.

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

Bach, Lukas; Hasle, Geir; Wøhlk, Sanne

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...... quality of the upper bound. This fact, and the high industrial relevance of the NEARP, should motivate more research on approximate and exact methods for this important problem....

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

Black, Daniel; Eglese, Richard; Wøhlk, Sanne

2015-01-01

-life traffic situations where the travel times change with the time of day are taken into account. Two metaheuristic algorithms, one based on Variable Neighborhood Search and one based on Tabu Search, are proposed and tested for a set of benchmark problems, generated from real road networks and travel time...... 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....

14. Routing and scheduling problems

Reinhardt, Line Blander

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...

15. Vehicle routing problems with alternative paths: an application to on-demand transportation

Garaix, Thierry; Artigues, Christian; Feillet, Dominique; Josselin, Didier

2010-01-01

The class of vehicle routing problems involves the optimization of freight or passenger transportation activities. These problems are generally treated via the representation of the road network as a weighted complete graph. Each arc of the graph represents the shortest route for a possible origin-destination connection. Several attributes can be deﬁned for one arc (travel time, travel cost . . . ), but the shortest route modelled by this arc is computed according to one single criterion, gen...

16. Major arcs for Goldbach's problem

Helfgott, H. A.

2013-01-01

The ternary Goldbach conjecture states that every odd number $n\\geq 7$ is the sum of three primes. The estimation of the Fourier series $\\sum_{p\\leq x} e(\\alpha p)$ and related sums has been central to the study of the problem since Hardy and Littlewood (1923). Here we show how to estimate such Fourier series for $\\alpha$ in the so-called major arcs, i.e., for $\\alpha$ close to a rational of small denominator. This is part of the author's proof of the ternary Goldbach conjecture. In contrast ...

17. Adaptive Memory Procedure to solve the Profitable Arc Tour Problem

Jalel Euchi

2010-05-01

Full Text Available In this paper we propose an Adaptive memory procedure to solve the Profitable Arc Tour Problem (PATP. The PATP is a variant of the well-known Vehicle Routing Problems in which a set of vehicle tours are constructed. The objective is to find a set of cycles in the vehicle tours that maximize the collection of profits minus travel costs, subject to constraints limiting the length of cycles that profit is available on arcs. Computational experiments show that our algorithms provide good results in terms of quality of solution and running times.

18. The Pyramidal Capacitated Vehicle Routing Problem

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...

19. The pyramidal capacitated vehicle routing problem

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...

20. Minor arcs for Goldbach's problem

Helfgott, H. A.

2012-01-01

The ternary Goldbach conjecture states that every odd number n>=7 is the sum of three primes. The estimation of sums of the form \\sum_{p\\leq x} e(\\alpha p), \\alpha = a/q + O(1/q^2), has been a central part of the main approach to the conjecture since (Vinogradov, 1937). Previous work required q or x to be too large to make a proof of the conjecture for all n feasible. The present paper gives new bounds on minor arcs and the tails of major arcs. This is part of the author's proof of the ternar...

1. Route Elimination Heuristic for Vehicle Routing Problem with Time Windows

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.

2. Minor arcs for Goldbach's problem

Helfgott, H A

2012-01-01

The ternary Goldbach conjecture states that every odd number $n\\geq 7$ is the sum of three primes. The estimation of sums of the form $\\sum_{p\\leq x} e(\\alpha p)$, $\\alpha = a/q + O(1/q^2)$, has been a central part of the main approach to the conjecture since (Vinogradov, 1937). Previous work required $q$ or $x$ to be too large to make a proof of the conjecture for all $n$ feasible. The present paper gives new bounds on minor arcs and the tails of major arcs. For $q\\geq 4\\cdot 10^6$, these bounds are of the strength needed to solve the ternary Goldbach conjecture. Only the range $q\\in \\lbrack 10^5, 4\\cdot 10^6\\rbrack$ remains to be checked, possibly by brute force, before the conjecture is proven for all $n$. The new bounds are due to several qualitative improvements. In particular, this paper presents a general method for reducing the cost of Vaughan's identity, as well as a way to exploit the tails of minor arcs in the context of the large sieve.

3. 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.

4. Rich Vehicle Routing Problems and Applications

Wen, Min

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......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...... problems in the sense that consolidation decisions have to be made at the depot and these decisions interact with the planning of pickup and delivery routes. We presented a mathematical model and proposed a Tabu Search based heuristic to solve it. It is shown that the approach can produce near-optimal...

5. Routing problems based on hils system platform

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

6. 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.

7. 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 ...

8. Applying min–max k postmen problems to the routing of security guards

E J Willemse; J W Joubert

2012-01-01

The most essential and alluring characteristic of a security estate is the estate's ability to provide 24-h security to its residents, of which the continual patrolling of roads and paths is vital. The objective of this paper is to address the lack of sufficient patrol route design procedures by presenting a tabu search algorithm capable of generating multiple patrol routes for an estate's security guards. The paper shows that the problem of designing these routes can be modelled as an Arc Ro...

9. 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.

10. Vehicle routing problem for save fuel consumption

LIU Hao; AI Wen-wen

2016-01-01

This study has extended a vehicle routing problem,by considering economy of fuel,and constructing a LF-VRP model,to obtain optimal fixed costs.Our objective was to minimize not only distance,but also the fuel consumption.A example were developed to solve the proposed models.It was found that our proposed models yielded better results than the traditional VRP models.

11. A new efficient transformation of the generalized vehicle routing problem into the classical vehicle routing problem

Pop Petrica

2011-01-01

Full Text Available Classical combinatorial optimization problems can be generalized in a natural way by considering a related problem relative to a given partition of the nodes of the graph into node sets. In the literature one can find generalized problems such as: generalized minimum spanning tree, generalized traveling salesman problem, generalized Steiner tree problem, generalized vehicle routing problem, etc. These generalized problems typically belong to the class of NP-complete problems; they are harder than the classical ones, and nowadays are intensively studied due to their interesting properties and applications in the real world. Because of the complexity of finding the optimal or near-optimal solution in case of the generalized combinatorial optimization problems, great effort has been made, by many researchers, to develop efficient ways of their transformation into classical corresponding variants. We present in this paper an efficient way of transforming the generalized vehicle routing problem into the vehicle routing problem, and a new integer programming formulation of the problem.

12. A new approach to turbulent arcs problem

A new hypothesis is advanced which assumes the mass being a charge that has not only the known static interaction but also the dynamic one. Moving mass charge produces a special field likewise the electric charge creates magnetic one. Dynamic Interaction of moving mass with the copartner field bends the particles trajectory and creates vortexes which are responsible for flow turbulization. The permeability constant and basic relations are derived for the ''vortex'' field. Some verifications of the hypothesis is done for ''cold'' flow and arc discharge. (author)

13. a Genetic Algorithm for Urban Transit Routing Problem

Chew, Joanne Suk Chun; Lee, Lai Soon

The Urban Transit Routing Problem (UTRP) involves solving a set of transit route networks, which proved to be a highly complex multi-constrained problem. In this study, a bus route network to find an efficient network to meet customer demands given information on link travel times is considered. An evolutionary optimization technique, called Genetic Algorithm is proposed to solve the UTRP. The main objective is to minimize the passenger costs where the quality of the route sets is evaluated by a set of parameters. Initial computational experiments show that the proposed algorithm performs better than the benchmark results for Mandl's problems.

14. Modeling the Multicommodity Multimodal Routing Problem with Schedule-Based Services and Carbon Dioxide Emission Costs

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.

15. Optimizing investment fund allocation using vehicle routing problem framework

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.

16. Tawanda’s non- iterative optimal tree algorithm for shortest route problems

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.

17. Robustness of a routing tree for the Push Tree Problem

Havet, Frédéric

2002-01-01

The Push Tree problem contains elements from both the Steiner Tree and Shortest Path problem. It deals with the trade-offs between the push and pull mechanism used in information distribution and retrieval. In , a two step approach for the Push Tree Problem was proposed. In the first step, a «good» spanning tree (called routing tree) is constructed and then the problem is solved in this particular tree. Finding a routing tree is NP-hard but the second step may be performed easily, thus the id...

18. The Service-Time Restricted Capacitated Arc Routing Problem

Lystlund, Lise; Wøhlk, Sanne

We consider an inventory system, operated by a base stock policy and serving two customer classes. One customer class, Class 1, does not provide any advance demand information at all, while the other, Class 2, does. In order to reward a customer of Class 2 for providing advance order information......, it may be sensible to make reservations for the order in the inventory system, thereby preventing later arriving orders from getting access to the inventory before this particular order. We propose various reservation policies and study their impact on the performance of the inventory system....

19. Optimization of Multiple Vehicle Routing Problems using Approximation Algorithms

Nallusamy, R; K. Duraiswamy,; Dhanalaksmi, R.; P. Parthiban

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 cl...

20. Ant Colony Algorithm for Solving QoS Routing Problem

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.

1. A Subpath Ejection Method for the Vehicle Routing Problem

César Rego

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...

2. The vehicle routing problem with time windows and temporal dependencies

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...... on the relaxed master problems. Finally, a computational study is performed to quantitatively reveal strengths and weaknesses of the proposed formulations. It is concluded that, depending on the problem at hand, the best performance is achieved either by relaxing the generalized precedence constraints...... in the master problem, or by using a time‐indexed model, where generalized precedence constraints are added as cuts when they become severely violated. © 2011 Wiley Periodicals, Inc. NETWORKS, Vol. 58(4), 273–289 2011...

3. A Study of Urgency Vehicle Routing Disruption Management Problem

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.

4. On the vehicle routing problem with time windows

Kallehauge, Brian

2006-01-01

eliminate time and capacity infeasible paths. We present a new class of strengthened path inequalities based on polyhedral results obtained in the context of the asymmetric traveling salesman problem with replenishment arcs. We study the VRPTW polytope and determine the polytope dimension. We show that the...... lifted path 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...

5. Classification of Ship Routing and Scheduling Problems in Liner Shipping

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 are...

6. Exact methods for time constrained routing and related scheduling problems

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 J?rnsten, Madsen and S?rensen (1986), which has been tested computationally by Halse (1992). Both methods decompose the problem into a series of time and capacity constrained shotest path problems. This yields a tight lower bound on the optimal objective, and the dual gap can often be closed...... of customers. In the VRPTW customers must be serviced within a given time period - a so called time window. The objective can be to minimize operating costs (e.g. distance travelled), fixed costs (e.g. the number of vehicles needed) or a combination of these component costs. During the last decade optimization...

7. Modeling a four-layer location-routing problem

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.

8. Vehicle routing problem with time-varying speed

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.

9. The Vehicle Routing Problem with Limited Vehicle Capacities

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.

10. FUNDAMENTAL PROBLEMS IN PULSED-BIAS ARC DEPOSITION

G.Q.Lin; Z.F.Ding; D.Qi; N.H.Wang; M.D.Huang; D.Z.Wang; Y.N.Wang; C.Dong; L.S.Wen

2002-01-01

Arc deposition, a widely used surface coating technique, has disadvantages such aslarge droplet size and high deposition temperature. Recent trend in its renovation isthe introduction of pulsed bias at the substrate. The present paper attempts to describethe deposition process of TiN films using this technique with emphasis laid on theunderstanding of the basic problems such as discharge plasma properties, temperaturecalculation, and droplet size reduction. We show that this technique improves thefilm microstructure and quality, lowers deposition temperature, and allows coatingson insulating substrates. After analyzing load current oscillation behaviors, we havedetermined that the plasma load is of capacitance nature due to plasma sheath and thatit is equivalent to a circuit element consisting of parallel capacitance and resistance.At last, we point out the remaining problems and future development of the pulsed-biasarc deposition technique.

11. Optimization of Multiple Vehicle Routing Problems Using Approximation Algorithms

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.

12. ACTIVITY-BASED COSTING FOR VEHICLE ROUTING PROBLEMS

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.

13. 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.

14. Performansi Algoritma CODEQ dalam Penyelesaian Vehicle Routing Problem

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.

15. STUDI TENTANG TRAVELLING SALESMAN DAN VEHICLE ROUTING PROBLEM DENGAN TIME WINDOWS

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.

16. 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.

17. Parallelization of the Vehicle Routing Problem with Time Windows

Larsen, Jesper

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. total distance traveled, number of vehicles needed or a combination of parameters). Since the late 80's...... also been 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...

18. Vehicle Coordinated Strategy for Vehicle Routing Problem with Fuzzy Demands

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.

19. The vehicle routing problem with edge set costs

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

2011-01-01

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. 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 e...

20. The selective vehicle routing problem in a collaborative environment

DEFRYN, Christof; Sörensen, Kenneth; CORNELISSENS, Trijntje

2015-01-01

We consider a selective vehicle routing problem, in which customers belonging to different partners in a logistic coalition are served in a single logistic operation with multiple vehicles. Each partner determines a cost of non-delivery (CND) for each of its customers, and a central algorithm creates an operational plan, including the decision on which customers to serve and in which trip. The total transportation cost of the coalition is then divided back to the partners through a cost alloc...

1. Choosing offshore pipeline routes: problems and solutions. Final report

Gowen, A.M.; Goetz, M.J.; Waitsman, I.M.

1980-05-01

The report discusses the environmental and fisheries problems associated with offshore pipelines. The report focuses on how these problems can be addressed during the pipeline planning and route selection process. Geologic hazards are highlighted as the major factors related to pipeline failure which can be addressed through the pipeline routing process. Habitats and ecosystems are particularly susceptible to installation-related disturbances. These areas as well as those where geologic hazards are most likely to be encountered are described. Fishing problems highlighted include loss of access to fishing areas due to pipelines both from platform to shore and between platforms. The effects of obstructions on bottom fishing gear are also considered. The concept of pipeline trenching for safety and stability is discussed. Finally, criteria to use in analyzing a proposed pipeline route are presented. Topics discussed include general industry siting criteria, geologic and environmental areas to avoid in pipeline siting and methods for minimizing unavoidable impacts. The report is designed to be used by scientists or engineers involved in offshore petroleum pipeline planning.

2. The Vehicle Routing Problem with Time Windows and Temporal Dependencies

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

to be scheduled with a certain slack between them. They refer to the vehicle problem as having interdependent time windows. Temporal dependencies have been modeled for a home care routing problem in a mixed integer programming model (MIP) which was solved with a standard MIP solver. An application with general...... temporal dependencies is also found in machine scheduling. Column generation is used to solve the problem. The pricing problem is primarily solved heuristically by local search and occasionally to optimality using a standard solver on an integer programming formulation of the pricing problem. Two compact...... is novel as well. Finally, we introduce a new set of context-free benchmark instances which enables a thorough quantitative analysis and which we hope will facilitate future research in this area. The analysis shows that, even though the time-indexed model has some nice properties, it also retains its...

3. 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.

4. On the vehicle routing problem with time windows

2006-01-01

Den danske titel på denne afhandling er ‘Ruteplanlægningsproblemet med tidsvinduer’. Dette problem omhandler den optimale styring af en flåde af lastbiler mellem et lager og et antal kunder, der skal besøges inden for et bestemt tidsinterval, et såkaldt tidsvindue. Formålet med denne afhandling er udvikling af nye og effektive metoder til løsning af ruteplanlægningsproblemet med tidsvinduer (vehicle routing problem with time windows - VRPTW). Afhandlingen består af et afsnit af introducerende...

5. The Cyclic-Routing UAV Problem is PSPACE-Complete

Ho, Hsi-Ming; Ouaknine, Joel

2014-01-01

Consider a finite set of targets, with each target assigned a relative deadline, and each pair of targets assigned a fixed transit flight time. Given a flock of identical UAVs, can one ensure that every target is repeatedly visited by some UAV at intervals of duration at most the target's relative deadline? The Cyclic-Routing UAV Problem (CR-UAV) is the question of whether this task has a solution. This problem can straightforwardly be solved in PSPACE by modelling it as a network of timed au...

6. Reachability cuts for the vehicle routing problem with time windows

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 for the...... VRPTW. In particular, any reachability cut dominates one or more k-path cuts. The paper presents separation procedures for reachability cuts and reports computational experiments on well-known VRPTW instances. The computational results suggest that reachability cuts can be highly useful as cutting...

7. The vehicle routing problem with edge set costs

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

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

8. 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.

9. SOLVING THE PROBLEM OF VEHICLE ROUTING BY EVOLUTIONARY ALGORITHM

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.

10. Separable cross decomposition to solve the assign–routing problem

M. Elizondo–Cortés

2008-01-01

Full Text Available The Inventory–Routing Problem emerges on a logistical context, that is presented into the companies and that it seeks to satisfy the demands of a group of clients distributed geographically, using a flotilla of vehicles of limited capacity, which are in a central ware house, at the small est possible cost. The IRP is a NP–hard problem that is usually great size in real applications. For its solution was designed an strategy that uses of combined form, the crossed de composition and the separable Lagrangean relaxation in order to solve the assign–distribution phase, with what it is obtained a ping–pong type scheme between two subproblems, which are from transport type, with which it is obtained a very efficient algorithm of order O(n3 and easy to implement for the complete problem.

11. Dynamic vehicle routing problems: Three decades and counting

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

2016-01-01

of DVRP papers according to 11 criteria. These are (1) type of problem, (2) logistical context, (3) transportation mode, (4) objective function, (5) fleet size, (6) time constraints, (7) vehicle capacity constraints, (8) the ability to reject customers, (9) the nature of the dynamic element, (10) the......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...... nature of the stochasticity (if any), and (11) the solution method. We comment on technological vis-à-vis methodological advances for this class of problems and suggest directions for further research. The latter include alternative objective functions, vehicle speed as decision variable, more explicit...

12. 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.

13. 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.

14. Linearization and Decomposition Methods for Large Scale Stochastic Inventory Routing Problem with 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, for a depot to determine delivery volumes to its customers in each period, and vehicle routes to distribute the delivery volumes. This

15. A Capacitated Location Routing Problem with Semi Soft Time Windows

Maryam Gharavani

2015-03-01

Full Text Available In this article we address The Location Routing Problem (LRP, where there is a set of customers with known demand and a set of potential depot site and there is a set of heterogeneous vehicle with a certain capacity. Due to the similarity of the problem with real world, the constraints of depot capacity and vehicle capacity as well as route length have been considered simultaneously. The model provided in this article is described concerning the semi soft time window in which that a delay in service delivery time results in delay costs. The total costs in the proposed model include, the total fixed costs of construction depot, fixed costs associated with the use of vehicles, the total distance traveled by the vehicles, the total time within the system for the vehicle and penalty cost associated with the violation of working hour of vehicles and penalty costs associated with delay time in the start of service to customers and the aim is to minimize the total cost. Due to its complexity, two Meta-Heuristic algorithms of Genetic and Tabu Search algorithm have been used. Since the performance of the Meta-Heuristic algorithms is significantly influenced by their parameters, Taguchi Method is used to set the parameters of developed algorithms. Finally, the result represents that the Genetic Algorithm and Tabu Search are significantly efficient in terms of better quality of solution and computational time respectively.

16. Efficient Intelligent Optimized Algorithm for Dynamic Vehicle Routing Problem

Jiangqing Wang

2011-11-01

Full Text Available In order to solve the dynamic vehicle routing problem (DVRP containing both dynamic network environment and real-time customer requests, an efficient intelligent optimized algorithm called IOA is proposed in this paper, which takes advantages of both global searching ability of evolutionary algorithms and local searching capability of ant colony algorithm. The proposed IOA incorporates ant colony algorithm for exploration and evolutionary algorithm for exploitation, and uses real-time information during the optimization process. In order to discuss the performance of the proposed algorithm, a mixed integral programming model for DVRP is formulated, and benchmark functions are constructed. Detailed simulation results and comparisons with the existed work show that the proposed IOA algorithm can achieve a higher performance gain, and is well suited to problems containing dynamic network environment and real-time customer requests.

17. An evolutionary algorithm for a real vehicle routing problem

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.

18. 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.

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

Yu Lin

2015-01-01

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

20. A sequential insertion heuristic for the vehicle routing problem with time windows with relatively few customers per route

DULLAERT, Wout

2000-01-01

In this paper we study the performance of Solomon’s (1987) sequential insertion heuristic |1, for Vehicle Routing Problems with Time Windows (VRPTWs) in which the number of customers per rout is small with respect to the customers’ time windows and the scheduling horizon. Solomon’s (1987) time insertion c12 (i, u, j) underestimates the additional time needed of inserting a new customer u between the depot, i= i0 and the first customer j in the partially constructed rout (i0= I, i1=j,i1,…,im)....

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

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...

2. Route Selection Problem Based on Hopfield Neural Network

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.

3. 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.

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

Yan Sun; Maoxiang Lang

2015-01-01

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. ...

5. The problem of pulmonary diseases in arc welders

25 cases of affections of the broncho-pulmonary tract in arc welders were evaluated on the basis of the case histories submitted to the professional association for acknowledgement as professional diseases. Unfortunately it was not possible to quantify the exposure. Welding in places too small to be adequately ventilated was normal with more than 80% of the persons concerned and is probably, in some cases, a negative influencing parameter in relation to the genesis of pulmonary damage. Approximately a quarter of the patients had a previous record of serious affections of the broncho-pulmonary system. The clinical diagnoses and findings were heterogeneous. A uniform ''welders' disease'' of the lungs cannot be derived from the case histories evaluated. In individual cases a characteristic aggravation of the affection respectively a substantial share in its causation by professional factors must be discussed. (orig./MG)

6. Problems in the Information Dissemination of the Internet Routing

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.

7. A branch-and-cut algorithm for the capacitated open vehicle routing problem

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...... assess the quality of existing heuristic methods, and to compare the relative difficulty of open and closed versions of the same problem....

8. A Branch-and-Cut Algorithm for the Capacitated Open Vehicle Routing Problem

Letchford, Adam N.; Lysgaard, Jens; Eglese, Richard W.

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...... assess the quality of existing heuristic methods, and to compare the relative difficulty of open and closed versions of the same problem....

9. An adaptive Cooperative Receding Horizon controller for the multivehicle routing problem

Giorgia Chini; Maria Guido Oddi; Antonio Pietrabissa

2012-01-01

The objective of the Vehicle Routing Problem (VRP), in the meaning of this paper, is to find the best path for a vehicle, or the best paths for a fleet of vehicles, with the aim of visiting a set of targets. Possible applications of the vehicle routing problem include surveillance, exploration, logistic,transportation, relief systems, etc. A lot of research has been carried out so far, but the VRP remains a complex and computationally expensive combinatorial problem, leading to the difficulty...

10. Improved Region-Growing and Combinatorial Algorithms for $k$-Route Cut Problems

Guruganesh, Guru; Sanita, Laura; Swamy, Chaitanya

2014-01-01

We study the {\\em $k$-route} generalizations of various cut problems, the most general of which is \\emph{$k$-route multicut} ($k$-MC) problem, wherein we have $r$ source-sink pairs and the goal is to delete a minimum-cost set of edges to reduce the edge-connectivity of every source-sink pair to below $k$. The $k$-route extensions of multiway cut ($k$-MWC), and the minimum $s$-$t$ cut problem ($k$-$(s,t)$-cut), are similarly defined. We present various approximation and hardness results for th...

11. Investigating the Value of Postponement in Inventory Routing Problems

Saka, Fernando

2009-01-01

Transportation and inventory management account for a large portion of the costs of distribution companies, so postponing delivery services could result in savings in these expenses. This particular study focuses on finding the optimal postponement horizon in which both routing and inventory holding costs are minimized. In addition, the research aims to explore the impact of a variety of parameters (service area, depot location, customers demand rate, customers density and vehicle capaci...

12. Hybrid discrete particle swarm optimization algorithm for capacitated vehicle routing problem

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.

13. Optimization of Capacitated Vehicle Routing Problem by Nested Particle Swarm Optimization

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.

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

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...

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

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 garba...

16. Coarse-Grained Parallel Genetic Algorithm to solve the Shortest Path Routing problem using Genetic operators

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.

17. The electric vehicle routing problem with partial charging and nonlinear charging function

Montoya, Alejandro; Guéret, Christelle; Mendoza, Jorge E.; Villegas, Juan

2015-01-01

Electric vehicle routing problems (eVRPs) extend classical routing problems to consider the limited driving range of electric vehicles. In general, this limitation is overcome by introducing planned detours to battery charging stations. Most existing eVRP models rely on one (or both) of the following assumptions: (i) the vehicles fully charge their batteries every time they reach a charging station, and (ii) the battery charge level is a linear function of the charging time. In practical situ...

18. A Particle Swarm Optimization with Adaptive Multi-Swarm Strategy for Capacitated Vehicle Routing Problem

Kui-Ting CHEN; Yijun Dai; Ke Fan; Takaaki Baba

2015-01-01

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 th...

19. Enhanced Genetic Algorithm approach for Solving Dynamic Shortest Path Routing Problems using Immigrants and Memory Schemes

Nair, T. R. Gopalakrishnan; Sooda, Kavitha; 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 ...

20. A Centroid-based Heuristic Algorithm for the Capacitated Vehicle Routing Problem

Kwangcheol Shin; Sangyong Han

2012-01-01

The vehicle routing problem (VRP) is famous as a nondeterministic polynomial-time hard problem. This study proposes a centroid-based heuristic algorithm to solve the capacitated VRP in polynomial time. The proposed algorithm consists of three phases: cluster construction, cluster adjustment, and route establishment. At the cluster construction phase, the farthest node (customer) among un-clustered nodes is selected as a seed to form a cluster. The notion of the geometrical centre of a cluster...

1. Research on multi-objective emergency logistics vehicle routing problem under constraint conditions

Miaomiao Du; Hua Yi

2013-01-01

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 ro...

2. Solving the Tractor and Semi-Trailer Routing Problem Based on a Heuristic Approach

Hongqi Li; Yue Lu; Jun Zhang; Tianyi Wang

2012-01-01

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 n...

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

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

4. Disruption management of the vehicle routing problem with vehicle breakdown

Mu, Q; Fu, Z; Lysgaard, Jens;

2011-01-01

solution needs to be quickly generated to minimise the costs. Two Tabu Search algorithms are developed to solve the problem and are assessed in relation to an exact algorithm. A set of test problems has been generated and computational results from experiments using the heuristic algorithms are presented....

5. REFINEMENTS OF THE COLUMN GENERATION PROCESS FOR THE VEHICLE ROUTING PROBLEM WITH TIME WINDOWS

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.

6. A Novel Linear Programming Formulation of Maximum Lifetime Routing Problem in Wireless Sensor Networks

2011-01-01

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...... 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......In wireless sensor networks, one of the key challenge is to achieve minimum energy consumption in order to maximize network lifetime. In fact, lifetime depends on many parameters: the topology of the sensor network, the data aggregation regime in the network, the channel access schemes, the routing...

7. 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.

8. Parallel algorithms for network routing problems and recurrences

Wisniewski, J.A. (Sandia Labs., Albuquerque, NM); Sameh, A.H.

1982-09-01

In this paper, we consider the parallel solution of recurrences, and linear systems in the regular algebra of Carre. These problems are equivalent to solving the shortest path problem in graph theory, and they also arise in the analysis of Fortran programs. Our methods for solving linear systems in the regular algebra are analogues of well-known methods for solving systems of linear algebraic equations. A parallel version of Dijkstra's method, which has no linear algebraic analogue, is presented. Considerations for choosing an algorithm when the problem is large and sparse are also discussed.

9. Parallel algorithms for network routing problems and recurrences

In this paper, we consider the parallel solution of recurrences, and linear systems in the regular algebra of Carre. These problems are equivalent to solving the shortest path problem in graph theory, and they also arise in the analysis of Fortran programs. Our methods for solving linear systems in the regular algebra are analogues of well-known methods for solving systems of linear algebraic equations. A parallel version of Dijkstra's method, which has no linear algebraic analogue, is presented. Considerations for choosing an algorithm when the problem is large and sparse are also discussed

10. Enhanced Mixed Integer Programming Techniques and Routing Problems

Tramontani, Andrea

2009-01-01

Mixed integer programming is up today one of the most widely used techniques for dealing with hard optimization problems. On the one side, many practical optimization problems arising from real-world applications (such as, e.g., scheduling, project planning, transportation, telecommunications, economics and finance, timetabling, etc) can be easily and effectively formulated as Mixed Integer linear Programs (MIPs). On the other hand, 50 and more years of intensive research has dramatically ...

11. 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.

12. Considering lost sale in inventory routing problems for perishable goods

Mirzaei, Samira; Seifi, Abbas

2015-01-01

solved to optimality for small instances and is used to obtain lower bounds for larger instances. We have also devised an efficient meta-heuristic algorithm to find good solutions for this class of problems based on Simulated Annealing (SA) and Tabu Search (TS). Computational results indicate that, for...

13. On the Integrated Job Scheduling and Constrained Network Routing Problem

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...

14. The dynamic multi-period vehicle routing problem

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

2010-01-01

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...

15. The Dynamic Multi-Period Vehicle Routing Problem

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

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...

16. On an iterative procedure for solving a routing problem with constraints

Chentsov, A. A.; A. G Chentsov

2013-01-01

The generalized precedence constrained traveling salesman problem is considered in the case when travel costs depend explicitly on the list of tasks that have not been performed (by the time of the travel). The original routing problem with dependent variables is represented in terms of an equivalent extremal problem with independent variables. An iterative method based on this representation is proposed for solving the original problem. The algorithm based on this method is implemented as a ...

17. RaceTrack: An Approximation Algorithm for the Mobile Sink Routing Problem

Yuan, Yuan; Peng, Yuxing

In large-scale monitoring applications, randomly deployed wireless sensor networks may not be fully connected. Using mobile sink for data collection is one of the feasible solutions. For energy saving, it is necessary to plan a shortest route for the mobile sink. Mobile sink routing problem can be regarded as a special case of TSP with neighborhoods (TSPN) problem. In this paper, we propose a novel approximation algorithm called RaceTrack. This algorithm forms a "racetrack" based on the TSP route, which is constructed from the locations of the deployed sensor nodes. By using inner lane heuristic and concave bend heuristic of auto racing, and a shortcut finding step, we optimize the obtained TSP route within O(n) computation time. Through formal proofs and large-scale simulations, we verified that our RaceTrack algorithm can achieve a good approximation ratio.

18. A Rounding by Sampling Approach to the Minimum Size k-Arc Connected Subgraph Problem

Laekhanukit, Bundit; Singh, Mohit

2012-01-01

In the k-arc connected subgraph problem, we are given a directed graph G and an integer k and the goal is the find a subgraph of minimum cost such that there are at least k-arc disjoint paths between any pair of vertices. We give a simple (1 + 1/k)-approximation to the unweighted variant of the problem, where all arcs of G have the same cost. This improves on the 1 + 2/k approximation of Gabow et al. [GGTW09]. Similar to the 2-approximation algorithm for this problem [FJ81], our algorithm simply takes the union of a k in-arborescence and a k out-arborescence. The main difference is in the selection of the two arborescences. Here, inspired by the recent applications of the rounding by sampling method (see e.g. [AGM+ 10, MOS11, OSS11, AKS12]), we select the arborescences randomly by sampling from a distribution on unions of k arborescences that is defined based on an extreme point solution of the linear programming relaxation of the problem. In the analysis, we crucially utilize the sparsity property of the ext...

19. Enhanced Genetic Algorithm approach for Solving Dynamic Shortest Path Routing Problems using Immigrants and Memory Schemes

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...

20. A STUDY AND IMPLEMENTATION OF THE TRANSIT ROUTE NETWORK DESIGN PROBLEM FOR A REALISTIC URBAN CASE

M. Kalochristianakis; Kosmopoulos, D.

2016-01-01

The design of public transportation networks presupposes solving optimization problems, involving various parameters such as the proper mathematical description of networks, the algorithmic approach to apply, and also the consideration of real-world, practical characteristics such as the types of vehicles in the network, the frequencies of routes, demand, possible limitations of route capacities, travel decisions made by passengers, the environmental footprint of the system, th...

1. A branch-and-price algorithm for the capacitated vehicle routing problem with stochastic demands

Christiansen, Christian Holk; Lysgaard, Jens

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....... Computational experiments show promising results....

2. Vehicle Routing Problem with Backhaul, Multiple Trips and Time Window

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.

3. Research on multi-objective emergency logistics vehicle routing problem under constraint conditions

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.

4. Multidimentional Self-organization for Online Time-Constrained Vehicle Routing Problems

ZEDDINI, B; ZARGAYOUNA, M

2010-01-01

Vehicle Routing problems are highly complex problems for which different Artificial Intelligence techniques have been used. In this paper, we propose two agent-oriented self-organization models for the dynamic version of the problem with time windows. The first model relies on a spatial representation, and the second is based on a space-time representation of the agents' action zones, which are able to maintain a good distribution of the vehicles on the environment. This distribution provides...

5. Solution to the problem of ant being stuck by ant colony routing algorithm

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.

6. An Investigation of Using Parallel Genetic Algorithm for Solving the Shortest Path Routing Problem

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

7. An Artificial Bee Colony Algorithm for the Capacitated Vehicle Routing Problem

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...... instances, and the computational results show that the heuristic produces good solutions....

8. Hybrid self organizing migrating algorithm - Scatter search for the task of capacitated vehicle routing problem

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.

9. Forming optimal routes in the problems of transport logistics by use of GIS technology

Nikolaenko, A. E.; Shugaley, O. A.

2014-12-01

Consideration of the key issues that arise in solving the problems of transport logistics, how to overcome them through the use of GIS technology. The analysis of the benefits of using GÐS before forming routes in manual mode and the evaluation of economic efficiency in the use of GIS technology in transport logistics.

10. A Hybrid Column Generation approach for an Industrial Waste Collection Routing Problem

Hauge, Kristian; Larsen, Jesper; Lusby, Richard Martin;

2014-01-01

This paper presents a practical roll-on/roll-o_ routing (ROROR) problem arising in the collection of industrial waste. Skip containers, which are used for the waste col-lection, need to be distributed between, and collected from, a set of customers. Full containers must be driven to dump sites...

11. 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.

12. Single-Commodity Vehicle Routing Problem with Pickup and Delivery Service

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.

13. 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.

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

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.

15. Research of Multi-Depot Vehicle Routing Problem by Cellular Ant Algorithm

Yuanzhi Wang

2013-07-01

Full Text Available The Multi-Depot Vehicle Routing Problem (MDVRP is a generalization of SDVRP, in which multiple vehicles start from multiple depots and return to their original depots at the end of their assigned tours. The MDVRP is NP-hard, therefore, the development of heuristic algorithms for this problem class is of primary interest. This paper solves Multi-Depot Vehicle Routing Problem with Cellular Ant Algorithm which is a new optimization method for solving real problems by using both the evolutionary rule of cellular, graph theory and the characteristics of ant colony optimization. The simulation experiment shows that the Cellular Ant Algorithm is feasible and effective for the MDVRP. The clarity and simplicity of the Cellular Ant Algorithm is greatly enhanced to ant colony optimization.

16. Solving the Tractor and Semi-Trailer Routing Problem Based on a Heuristic Approach

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.

17. 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.

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

Wen, Min; Krapper, Emil; Larsen, Jesper;

2011-01-01

The world's second largest producer of pork, Danish Crown, also provides a fresh meat supply logistics system within Denmark. This is used by the majority of supermarkets in Denmark. This article addresses an integrated vehicle routing and driver scheduling problem arising at Danish Crown...... week. Computational results show that the aggregation procedure and the decomposition strategy are very effective in solving this large scale problem, and our solutions are superior to the industrial solutions given the constraints considered in this work....

19. Solving global two dimensional routing problems using Snell's law and A* search

Richbourg, Robert F.; Rowe, Neil C.; Zyda, Michael J.; McGhee, Robert

1986-01-01

Long range route planning based on map data is an important component in the intelligent control system of an autonomous agent. Most attempts to solve this problem rely on applying simple search strategies to high resolution, node and link representations of the map. These techniques have several disadvantages including large time and space requirements. The authors present a solution technique which utilizes a more intelligent representation of the problem environment. Topographical features...

20. Acceleration of Lagrangian Method for the Vehicle Routing Problem with Time Windows

2012-01-01

The analytic center cutting plane method (ACCPM) is one of successful methods to solve nondifferentiable optimization problems. In this paper, ACCPM is used to accelerate Lagrangian relaxation procedure for solving a vehicle routing problem with time windows (VRPTW). First, a basic cutting plane algorithm and its relationship with a column generation technique is clarified. Then, the proposed method based on ACCPM is explained as a stabilization technique for Lagrangian relaxation. Both appro...

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

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.

2. Solving the Vehicle Routing Problem with Stochastic Demands via Hybrid Genetic Algorithm-Tabu Search

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.

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

Hiermann, Gerhard; Puchinger, Jakob; Røpke, Stefan;

2016-01-01

detours to recharging stations necessary, thus requiring efficient tour planning mechanisms in order to sustain the competitiveness of electric vehicles compared to conventional vehicles. We introduce the Electric Fleet Size and Mix Vehicle Routing Problem with Time Windows and Recharging Stations (E......-FSMFTW) to model decisions to be made with regards to fleet composition and the actual vehicle routes including the choice of recharging times and locations. The available vehicle types differ in their transport capacity, battery size and acquisition cost. Furthermore, we consider time windows at customer...

4. Robust Branch-and-Cut-and-Price for the Capacitated Vehicle Routing Problem

Fukasawa, R.; Longo, H.; Lysgaard, Jens; Poggi de Aragão, M.; Reis, M.; Uchoa, E.; Werneck, R.F.

2006-01-01

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......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...

5. A Discrete Firefly Algorithm to Solve a Rich Vehicle Routing Problem Modelling a Newspaper Distribution System with Recycling Policy

E. Osaba; Yang, Xin-She; Diaz, F.; Onieva, E.; Masegosa, A. D.; A. Perallos

2016-01-01

A real-world newspaper distribution problem with recycling policy is tackled in this work. In order to meet all the complex restrictions contained in such a problem, it has been modeled as a rich vehicle routing problem, which can be more specifically considered as an asymmetric and clustered vehicle routing problem with simultaneous pickup and deliveries, variable costs and forbidden paths (AC-VRP-SPDVCFP). This is the first study of such a problem in the literature. For this reason, a bench...

6. Optimized Crossover Genetic Algorithm for Vehicle Routing Problem with Time Windows

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.

7. A Mathematical Model for the Industrial Hazardous Waste Location-Routing Problem

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.

8. Vehicle Routing Problem for Fashion Supply Chains with Cross-Docking

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.

9. Relative Performance of Certain Meta Heuristics on Vehicle Routing Problem with Time Windows

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.

10. 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. PMID:24748696

11. Adaptive Agent Model with Hybrid Routing Selection Strategy for Improving the Road-Network Congestion Problem

Bin Jiang; Chao Yang; Takao Terano

2015-01-01

12. A HYBRID GENETIC ALGORITHM IMPLEMENTATION FOR VEHICLE ROUTING PROBLEM WITH TIME WINDOWS

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

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

MANAR Y. KASHMOLA

2012-06-01

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

14. 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.

15. An artificial bee colony algorithm for the capacitated vehicle routing problem

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

2011-01-01

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

16. An Angle-Based Crossover Tabu Search for Vehicle Routing Problem

Yang, Ning; Li, Ping; Li, Mingsen

An improved tabu search - crossover tabu search (CTS) is presented which adopt the crossover operator of the genetic algorithm as the diversification strategy, and selecting elite solutions as the intensification strategies. To improve the performances, the angle-based idea of the sweep heuristic is used to confirm the neighborhood, and an object function with punishment. The angle-based CTS is applied for the vehicle routing problem. The simulating results which compared the tradition sweep heuristic and the standard tabu search shows the results got by angle-based CTS are better than those got by other two heuristics. The experiment shows the angle-based CTS has good performance on the vehicle routing problem.

17. Branch and price for the time-dependent vehicle routing problem with time windows

Dabia, Said; Van Woensel, Tom; De Kok, Ton;

2013-01-01

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...... the variant of the TDVRPTW where the objective is to minimize total route duration and denote this variant the duration minimizing TDVRPTW (DM-TDVRPTW). Because of time dependency, vehicles' dispatch times at the depot are crucial as road congestion might be avoided. Because of its complexity, all...... 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...

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

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

2015-01-01

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. PMID:26343655

19. A Hybrid Genetic Algorithm for Vehicle Routing Problem with Complex Constraints

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.

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

Li Liao; Jianfeng Li; Yaohua Wu

2013-01-01

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

1. A mathematical model for the municipal solid waste location-routing problem with intermediate transfer stations

Hossein Asefi; Samsung Lim; Mojtaba Maghrebi

2015-01-01

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 orde...

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

Gonzalez-Feliu, Jesus

2012-01-01

Freight transportation constitutes one of the main activities that influences economy and society, as it assures a vital link between suppliers and customers and it 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 ...

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

Hiermann, Gerhard; Puchinger, Jakob; Ropke, Stefan; Hartl, Richard F.

2016-01-01

International audience 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 conventio...

4. Control strategies for the vehicle routing problem applied to medical emergencies

Chini, Giorgia

2014-01-01

This thesis deals with dynamic Multi-Vehicle Routing Problem (MVRP) in both deterministic and stochastic scenarios. The objective of the MVRP is to find the best paths for a fleet of vehicles, with the aim of visiting a set of targets. Based on the Cooperative Receding Horizon (CRH) approach proposed by Cassandras et al.(CRH) for the Euclidean case, this thesis: i) presents another algorithm that is more efficient with clustered targets (tCRH); ii) illustrates an algorithm that ex...

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

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.

6. A P-Based Hybrid Evolutionary Algorithm for Vehicle Routing Problem with Time Windows

Yunyun Niu

2014-01-01

Full Text Available The ability to solve optimization problems using membrane algorithms is an important application of membrane computing. This work combines membrane systems and genetic operators to build an approximated algorithm for the vehicle routing problem with time windows. The algorithm is based on a tissue-like membrane structure combined with cell separation rules and communication rules; during such processes membranes collect and disperse information. Genetic operators are used as the system's subalgorithms. We also design a special improvement strategy to speed up the search process in subsystems. The experimental results show that the solution quality from the proposed algorithm is competitive with other heuristic or metaheuristic algorithms in the literature.

7. Clique inequalities applied to the vehicle routing problem with time windows

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...

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

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 m...... model that is a relaxation and provides a valid lower bound. A specialized branching scheme is employed to obtain feasible solutions. Out of a test set of 93 instances the algorithm is able to solve 47 to optimality surpassing previous exact algorithms....

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

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.

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

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.

11. 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.

12. A STUDY AND IMPLEMENTATION OF THE TRANSIT ROUTE NETWORK DESIGN PROBLEM FOR A REALISTIC URBAN CASE

M. Kalochristianakis

2016-01-01

Full Text Available The design of public transportation networks presupposes solving optimization problems, involving various parameters such as the proper mathematical description of networks, the algorithmic approach to apply, and also the consideration of real-world, practical characteristics such as the types of vehicles in the network, the frequencies of routes, demand, possible limitations of route capacities, travel decisions made by passengers, the environmental footprint of the system, the available bus technologies, besides others. The current paper presents the progress of the work that aims to study the design of a municipal public transportation system that employs middleware technologies and geographic information services in order to produce practical, realistic results. The system employs novel optimization approaches such as the particle swarm algorithms and also considers various environmental parameters such as the use of electric vehicles and the emissions of conventional ones.

13. Intelligent Iterated Local Search Methods for Solving Vehicle Routing Problem with Different Fleets

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.

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

2014-08-01

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

15. A route-based decomposition for the Multi-Commodity k-splittable Maximum Flow Problem

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...

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

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.

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

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.

18. A mathematical model for the municipal solid waste location-routing problem with intermediate transfer stations

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.

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

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....... 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...

20. Flow Merging and Hub Route Optimization in Collaborative Transportation

2013-01-01

This paper studies the optimal hub routing problem of merged tasks in collaborative transportation. This problem allows all carriers’ transportation tasks to reach the destinations optionally passing through 0, 1, or 2 hubs within limited distance, while a cost discount on arcs in the hub route could be acquired after paying fixed charges. The problem arises in the application of logistics, postal services, airline transportation, and so forth. We formulate the problem as a mixed-integer prog...

1. Comparing The Performance of Simulated Annealing and Genetic Algorithm Metaheuristics in The Solving of Vehicle Routing Problem Variants

Epps, M

2014-01-01

Solving the variants of the Vehicle Routing Problem (VRP) is invaluable to a huge range of businesses today. It allows for the calculation of efficient logistics routing which can drastically improve a firm’s competitiveness. As NP-hard combinatorial optimisation problems, they cannot be solved by exact methods: the solution space is simply too large for it to be evaluated in entirety in a reasonable timespan. Instead, metaheuristic algorithms, which produce reasonably good solutions much mor...

2. Strength Pareto Evolutionary Algorithm based Multi-Objective Optimization for Shortest Path Routing Problem in Computer Networks

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.

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

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.

4. 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. PMID:27547672

5. A Simulation-Based Algorithm for the Capacitated Vehicle Routing Problem with Stochastic Travel Times

Zheng Wang

2013-01-01

Full Text Available This paper presents a flexible solution methodology for the capacitated vehicle routing problem with stochastic travel times (CVRPSTT. One of the basic ideas of the methodology is to consider a vehicle working time lower than the actual maximum vehicle working time when designing CVRPSTT solutions. In this way, the working time surplus can be used to cope with unexpected congestions when necessary. Another important idea is to transform the CVRPSTT instance to a limited set of capacitated vehicle routing problems (CVRP, each of which is defined by a given percentage of the maximum vehicle working time. Thus, our approach can take advantage of any efficient heuristic that already exists for the CVRP. Based on the two key ideas, this paper presents a simulation-based algorithm, in which Monte Carlo simulation is used to obtain estimates of the cost and the reliability of each solution, and the Clarke and Wright heuristic is improved to generate more reliable solutions. Finally, a number of numerical experiments are done in the paper with the purpose of analyzing the efficiency of the described methodology under different uncertainty scenarios.

6. Research on cultural algorithm for solving routing problem of mobile agent

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.

7. A Hybrid Bat Algorithm with Path Relinking for Capacitated Vehicle Routing Problem

Yongquan Zhou

2013-01-01

Full Text Available The capacitated vehicle routing problem (CVRP is an NP-hard problem with wide engineering and theoretical background. In this paper, a hybrid bat algorithm with path relinking (HBA-PR is proposed to solve CVRP. The HBA-PR is constructed based on the framework of continuous bat algorithm; the greedy randomized adaptive search procedure (GRASP and path relinking are effectively integrated into bat algorithm. Moreover, in order to further improve the performance, the random subsequences and single-point local search are operated with certain loudness (probability. In order to verify the validity of the method in this paper, and it's efficiency and with other existing methods, several classical CVRP instances from three classes of CVRP benchmarks are selected to tested. Experimental results and comparisons show that the HBA-PR is effective for CVRP.

8. Application of Modified Ant Colony Optimization (MACO for Multicast Routing Problem

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.

9. Arc-based constrained ant colony optimisation algorithms for the optimal solution of hydropower reservoir operation problems

Moeini, R.; Afshar, M.H.

2011-07-15

Hydropower is currently the number one source of electricity production in the world. For the design and construction of such systems, mathematical modelling is often use for reservoir operations. As conventional methods present some shortcomings in solving reservoir operation problems, a new method is presented here. It consists in an arc-based formulation of hydropower reservoir operation problems which can be applied to ant colony optimization algorithms. This paper first described this formulation and then applied it to solve two hydropower reservoir operation problems. The results showed that this formulation can optimally solve large-scale hydropower reservoir operation problems while offering a clear definition of heuristic information.

10. Multiobjective Dynamic Vehicle Routing Problem and Time Seed Based Solution Using Particle Swarm Optimization

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.

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

Yu Lin; Tianyi Xu; Zheyong Bian

2015-01-01

High frequency and small lot size are characteristics of milk runs and are often used to implement the just-in-time (JIT) strategy in logistical systems. The common frequency problem, which simultaneously involves planning of the route and frequency, has been extensively researched in milk run systems. In addition, vehicle type choice in the milk run system also has a significant influence on the operating cost. Therefore, in this paper, we simultaneously consider vehicle routing planning, fr...

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

Hao Yu; Wei Deng Solvang

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 tran...

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

Wan-Yu Liu; Chun-Cheng Lin; Ching-Ren Chiu; You-Song Tsao; Qunwei Wang

2014-01-01

Torespondto the reduction of greenhouse gas emissions and global warming, this paper investigates the minimal-carbon-footprint time-dependent heterogeneous-fleet vehicle routing problem with alternative paths (MTHVRPP). This finds a route with the smallestcarbon footprint, instead of the shortestroute distance, which is the conventional approach, to serve a number of customers with a heterogeneous fleet of vehicles in cases wherethere may not be only one path between each pair of customers, a...

14. A Multi-Start Evolutionary Local Search for the Two-Echelon Location Routing Problem

Nguyen, Viet-Phuong; Prins, Christian; Prodhon, Caroline

This paper presents a new hybrid metaheuristic between a greedy randomized adaptive search procedure (GRASP) and an evolutionary/iterated local search (ELS/ILS), using Tabu list to solve the two-echelon location routing problem (LRP-2E). The GRASP uses in turn three constructive heuristics followed by local search to generate the initial solutions. From a solution of GRASP, an intensification strategy is carried out by a dynamic alternation between ELS and ILS. In this phase, each child is obtained by mutation and evaluated through a splitting procedure of giant tour followed by a local search. The tabu list, defined by two characteristics of solution (total cost and number of trips), is used to avoid searching a space already explored. The results show that our metaheuristic clearly outperforms all previously published methods on LRP-2E benchmark instances. Furthermore, it is competitive with the best meta-heuristic published for the single-echelon LRP.

15. Improved Multi-Agent System for the Vehicle Routing Problem with Time Windows

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.

16. A hybrid genetic algorithm for route optimization in the bale collecting problem

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.

17. Route optimisation and solving Zermelo's navigation problem during long distance migration in cross flows.

Hays, Graeme C; Christensen, Asbjørn; Fossette, Sabrina; Schofield, Gail; Talbot, Julian; Mariani, Patrizio

2014-02-01

The optimum path to follow when subjected to cross flows was first considered over 80 years ago by the German mathematician Ernst Zermelo, in the context of a boat being displaced by ocean currents, and has become known as the 'Zermelo navigation problem'. However, the ability of migrating animals to solve this problem has received limited consideration, even though wind and ocean currents cause the lateral displacement of flyers and swimmers, respectively, particularly during long-distance journeys of 1000s of kilometres. Here, we examine this problem by combining long-distance, open-ocean marine turtle movements (obtained via long-term GPS tracking of sea turtles moving 1000s of km), with a high resolution basin-wide physical ocean model to estimate ocean currents. We provide a robust mathematical framework to demonstrate that, while turtles eventually arrive at their target site, they do not follow the optimum (Zermelo's) route. Even though adult marine turtles regularly complete incredible long-distance migrations, these vertebrates primarily rely on course corrections when entering neritic waters during the final stages of migration. Our work introduces a new perspective in the analysis of wildlife tracking datasets, with different animal groups potentially exhibiting different levels of complexity in goal attainment during migration. PMID:24304813

18. Some experiments with a savings heuristic and a tabu search approach for the vehicle routing problem with multiple deliverymen

Vanessa de Oliveira Ferreira

2012-08-01

Full Text Available In this work we consider a variant of the vehicle routing problem that allows the assignment of multiple deliverymen to one or more routes. A practical motivation for this variant arises, for example, in the distribution of beverages in highly dense urban areas, characterized by the difficulty in serving daily requests within regular working day hours with a single deliveryman per vehicle. We present a mathematical model and a savings algorithm in order to generate low cost routes that maximize the number of requests served in compliance with the maximum route time. The impact of the extra deliverymen on the solutions provided by the proposed heuristic is assessed by means of sets of generated examples based on classical instances of literature. It is also presented the results obtained by an adaptation of a tabu search approach from the literature.

19. Multiobjective Vehicle Routing Problems With Simultaneous Delivery and Pickup and Time Windows: Formulation, Instances, and Algorithms.

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. PMID:25794408

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

Wan-Yu Liu

2014-07-01

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

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

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.

2. Weldability Characteristics of Sintered Hot-Forged AISI 4135 Steel Produced through P/M Route by Using Pulsed Current Gas Tungsten Arc Welding

Joseph, Joby; Muthukumaran, S.; Pandey, K. S.

2016-01-01

Present investigation is an attempt to study the weldability characteristics of sintered hot-forged plates of AISI 4135 steel produced through powder metallurgy (P/M) route using matching filler materials of ER80S B2. Compacts of homogeneously blended elemental powders corresponding to the above steel were prepared on a universal testing machine (UTM) by taking pre-weighed powder blend with a suitable die, punch and bottom insert assembly. Indigenously developed ceramic coating was applied on the entire surface of the compacts in order to protect them from oxidation during sintering. Sintered preforms were hot forged to flat, approximately rectangular plates, welded by pulsed current gas tungsten arc welding (PCGTAW) processes with aforementioned filler materials. Microstructural, tensile and hardness evaluations revealed that PCGTAW process with low heat input could produce weldments of good quality with almost nil defects. It was established that PCGTAW joints possess improved tensile properties compared to the base metal and it was mainly attributed to lower heat input, resulting in finer fusion zone grains and higher fusion zone hardness. Thus, the present investigation opens a new and demanding field in research.

3. Branch-and-price-and-cut for the Split-collection Vehicle Routing Problem with Time Windows and Linear Weight-related Cost

Luo, Zhixin; Qin, Hu; Zhu, Wenbin; Lim, Andrew

2014-01-01

This paper addresses a new vehicle routing problem that simultaneously involves time windows, split collection and linear weight-related cost, which is a generalization of the split delivery vehicle routing problem with time windows (SDVRPTW). This problem consists of determining least-cost vehicle routes to serve a set of customers while respecting the restrictions of vehicle capacity and time windows. The travel cost per unit distance is a linear function of the vehicle weight and the custo...

4. An optimization algorithm for a capacitated vehicle routing problem with time windows

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.

5. Approximation Algorithms and Hardness of the k-Route Cut Problem

Chuzhoy, Julia; Zhou, Yuan; Vijayaraghavan, Aravindan

2011-01-01

We study the k-route cut problem: given an undirected edge-weighted graph G=(V,E), a collection {(s_1,t_1),(s_2,t_2),...,(s_r,t_r)} of source-sink pairs, and an integer connectivity requirement k, the goal is to find a minimum-weight subset E' of edges to remove, such that the connectivity of every pair (s_i, t_i) falls below k. Specifically, in the edge-connectivity version, EC-kRC, the requirement is that there are at most (k-1) edge-disjoint paths connecting s_i to t_i in G \\ E', while in the vertex-connectivity version, NC-kRC, the same requirement is for vertex-disjoint paths. Prior to our work, poly-logarithmic approximation algorithms have been known for the special case where k >= 3, but no non-trivial approximation algorithms were known for any value k>3, except in the single-source setting. We show an O(k log^{3/2}r)-approximation algorithm for EC-kRC with uniform edge weights, and several polylogarithmic bi-criteria approximation algorithms for EC-kRC and NC-kRC, where the connectivity requirement ...

6. Capacitated vehicle routing problem for PSS uses based on ubiquitous computing: An emerging markets approach

Alberto Ochoa-Ortíz

2015-01-01

7. MILP for the Inventory and Routing for Replenishment Problem in the Car Assembly Line.

Raul Pulido

2014-01-01

Full Text Available The inbound logistic for feeding the workstation inside the factory represents a critical issue in the car manufacturing industry. Nowadays, this issue is even more critical than in the past since more types of car are being produced in the assembly lines. Consequently, as workstations have to install many types of components, they also need to have an inventory of different types of the component in a compact space.The replenishment is a critical issue since a lack of inventory could cause line stoppage or reworking. On the other hand, an excess of inventory could increase the holding cost or even block the replenishment paths. The decision of the replenishment routes cannot be made without taking into consideration the inventory needed by each station during the production time which will depend on the production sequence. This problem deals with medium-sized instances and it is solved using online solvers. The contribution of this paper is a MILP for the replenishment and inventory of the components in a car assembly line.

8. Exact and heuristic solution approaches for the Integrated Job Scheduling and Constrained Network Routing Problem

Gamst, M.

2014-01-01

better than using a standard IP-solver; however, it is still unable to solve several instances. The proposed heuristics generally have good performance. Especially, the First Come First Serve scheduling heuristic combined with a routing strategy, which proposes several good routes for each demand, has...

9. MULTI-DEPOT VEHICLE ROUTING PROBLEM WITH TIME WINDOW MENGGUNAKAN ADAPTIVE GENETIC ALGORITHM DENGAN FUZZY LOGIC CONTROLLER

Tri Kusnandi Fazarudin

2015-12-01

Full Text Available Multi-Depot Vehicle Routing Problem with Time Window (MDVRPTW is a problem of finding an optimal route for a supplier. The supplier needs to deliver goods to a number of customers using the vehicles located in a number of depots. Each delivery must be done within the service time specified by each customer The vehicles used have a maximum limit on the amount of goods that can be loaded and the maximum time the vehicle may be used. MDVRPTW is one of the variations of Vehicle Routing Problem (VRP. There are various algorithms that have been used to solve VRP problems. Some of them are Genetic Algorithm (GA, Tabu Search, and Adaptive GA with Artificial Bee Colony. GA can solve the problem within a shorter time, but it is vulnerable to get trapped in a local optimum. A strategy to reduce the probability of it is to make the GA adaptive. In this research, MDVRPTW is solved with GA. To reduce the probability of getting trapped in a local optimum, the GA parameters are made adaptive using Fuzzy Logic Controller (FLC. Based on the results of this research, using FLC on GA causes the average of the solution to be better than the solution produced using GA without FLC.

10. A Mathematical Model for the Industrial Hazardous Waste Location-Routing Problem

Boyer, Omid; Sai Hong, Tang; Pedram, Ali; Mohd Yusuff, Rosnah Bt; Zulkifli, Norzima

2013-01-01

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 tra...

11. Enhancing Solution Similarity in Multi-Objective Vehicle Routing Problems with Different Demand Periods

2008-01-01

In this chapter, we proposed a local search that can be used in a two-fold EMO algorithm for multiple-objective VRPs with different demands. The simulation results show that the proposed method have the fine effectiveness to enhance the similarity of obtained routes for vehicles. Although the local search slightly deteriorates the maximum duration, it improves the similarity of the routes that may decrease the possibility of getting lost the way of drivers. If drivers get lost their ways duri...

12. A multi-level variable neighborhood search heuristic for a practical vehicle routing and driver scheduling problem

Wen, Min; Krapper, Emil; Larsen, Jesper;

things, predefined workdays, fixed starting time, maximum weekly working duration, break rule. The objective is to minimize the total delivery cost. The real-life case study is fi rst introduced and modelled as a mixed integer linear program. A multilevel variable neighborhood search heuristic is then......This paper addresses an integrated vehicle routing and driver scheduling problem arising at the largest fresh meat producer in Denmark. The problem consists of a one-week planning horizon, heterogeneous vehicles, and drivers with predefi ned work regulations. These regulations include, among other...... proposed for the problem. At the first level, the problem size is reduced through an aggregation procedure. At the second level, the aggregated weekly planning problem is decomposed into daily planning problems, each of which is solved by a variable neighborhood search. At the last level, the solution of...

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

Larsen, Jesper

2004-01-01

interval denoted the time window. The objective is to determine routes for the vehicles that minimizes the accumulated cost (or distance) with respect to the above mentioned constraints. Currently the best approaches for determining optimal solutions are based on column generation and Branch...

14. The Green Ship Routing and Scheduling Problem (GSRSP): A conceptual approach

Kontovas, Christos A.

2014-01-01

Recent reviews of the literature on ship routing and scheduling note the increased attention to environmental issues. This is an area of paramount importance for international shipping and will be even more so in the future. This short communication is motivated by the increasing attention to...

15. Paving a Way to Algebraic Word Problems Using a Nonalgebraic Route

Amit, Miriam; Klass-Tsirulnikov, Bella

2005-01-01

A three-stage model for algebraic word problem solving is developed in which students' understanding of the intrinsic logical structure of word problems is strengthened by connecting real-life problems and formal mathematics. (Contains 3 figure.)

16. Incorporating location, routing, and inventory decisions in a bi-objective supply chain design problem with risk-pooling

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.

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

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

2015-12-01

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

18. Modeling Arcs

Insepov, Zeke; Veitzer, Seth; Mahalingam, Sudhakar

2011-01-01

Although vacuum arcs were first identified over 110 years ago, they are not yet well understood. We have since developed a model of breakdown and gradient limits that tries to explain, in a self-consistent way: arc triggering, plasma initiation, plasma evolution, surface damage and gra- dient limits. We use simple PIC codes for modeling plasmas, molecular dynamics for modeling surface breakdown, and surface damage, and mesoscale surface thermodynamics and finite element electrostatic codes for to evaluate surface properties. Since any given experiment seems to have more variables than data points, we have tried to consider a wide variety of arcing (rf structures, e beam welding, laser ablation, etc.) to help constrain the problem, and concentrate on common mechanisms. While the mechanisms can be comparatively simple, modeling can be challenging.

19. Arc Statistics

Meneghetti, M; Dahle, H; Limousin, M

2013-01-01

The existence of an arc statistics problem was at the center of a strong debate in the last fifteen years. With the aim to clarify if the optical depth for giant gravitational arcs by galaxy clusters in the so called concordance model is compatible with observations, several studies were carried out which helped to significantly improve our knowledge of strong lensing clusters, unveiling their extremely complex internal structure. In particular, the abundance and the frequency of strong lensing events like gravitational arcs turned out to be a potentially very powerful tool to trace the structure formation. However, given the limited size of observational and theoretical data-sets, the power of arc statistics as a cosmological tool has been only minimally exploited so far. On the other hand, the last years were characterized by significant advancements in the field, and several cluster surveys that are ongoing or planned for the near future seem to have the potential to make arc statistics a competitive cosmo...

20. Flow Merging and Hub Route Optimization in Collaborative Transportation

Kerui Weng

2014-01-01

Full Text Available This paper studies the optimal hub routing problem of merged tasks in collaborative transportation. This problem allows all carriers’ transportation tasks to reach the destinations optionally passing through 0, 1, or 2 hubs within limited distance, while a cost discount on arcs in the hub route could be acquired after paying fixed charges. The problem arises in the application of logistics, postal services, airline transportation, and so forth. We formulate the problem as a mixed-integer programming model, and provide two heuristic approaches, respectively, based on Lagrangian relaxation and Benders decomposition. Computational experiments show that the algorithms work well.

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

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.

2. Solution Representations and Local Search for the bi-objective Inventory Routing Problem

Barthélemy, Thibaut; Sevaux, Marc

2012-01-01

The solution of the biobjective IRP is rather challenging, even for metaheuristics. We are still lacking a profound understanding of appropriate solution representations and effective neighborhood structures. Clearly, both the delivery volumes and the routing aspects of the alternatives need to be reflected in an encoding, and must be modified when searching by means of local search. Our work contributes to the better understanding of such solution representations. On the basis of an experimental investigation, the advantages and drawbacks of two encodings are studied and compared.

3. Exactly solving the Split Pickup and Split Delivery Vehicle Routing Problem on a bike-sharing system

Casazza, Marco

2016-01-01

We propose an exact methodology to solve the Split Pickup and Split Delivery Vehicle Routing Problem arising in bike-sharing systems: a bike-sharing system is a public service in which bicycles are stored in rack stations and made available for shared use to individuals on a short term basis. However, during peak hours, flows along particular direction are registered, leading to high risk of empty racks in departure stations, and full racks at destination. One of the solutions chosen by many ...

4. Enhanced Formulations for Minimax and Discrete Optimization Problems with Applications to Scheduling and Routing

Ghoniem, Ahmed

2007-01-01

This dissertation addresses the development of enhanced formulations for minimax and mixed-integer programming models for certain industrial and logistical systems, along with the design and implementation of efficient algorithmic strategies. We first examine the general class of minimax mixed-integer 0-1 problems of the type that frequently arise in decomposition approaches and in a variety of location and scheduling problems. We conduct an extensive polyhedral analysis of this problem in o...

5. Does Calculation or Word-Problem Instruction Provide a Stronger Route to Prealgebraic Knowledge?

Fuchs, Lynn S.; Powell, Sarah R.; Cirino, Paul T.; Schumacher, Robin F.; Marrin, Sarah; Hamlett, Carol L.; Fuchs, Douglas; Compton, Donald L.; Changas, Paul C.

2014-01-01

The focus of this study was connections among 3 aspects of mathematical cognition at 2nd grade: calculations, word problems, and prealgebraic knowledge. We extended the literature, which is dominated by correlational work, by examining whether intervention conducted on calculations or word problems contributes to improved performance in the other…

6. Modelling Problem-Solving Situations into Number Theory Tasks: The Route towards Generalisation

2010-01-01

This paper examines the way two 10th graders cope with a non-standard generalisation problem that involves elementary concepts of number theory (more specifically linear Diophantine equations) in the geometrical context of a rectangle's area. Emphasis is given on how the students' past experience of problem solving (expressed through interplay…

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

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.

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

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

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

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

10. 基于 ArcGIS 的传统村落最佳观景路线提取方法-以世界文化遗产：开平碉楼与村落为例%ArcGIS Based Scenic Route Design Of Traditional Vilages：Kaiping Watchtowers Case

阴劼; 杨雯; 孔中华

2015-01-01

传统村落具有规模较小、景观点数量众多且分散、景观层次丰富和生产与生活性路网发达的特点。采取微观视角下的观景路线选线方法，在已有路网基础上提取最佳观景路线对于传统村落景观的保护与利用具有重要意义。研究以世界文化遗产之开平碉楼与村落为例，探索基于 ArcGIS 的空间视域选线方法：首先，通过要素提取分析和对象特征分析，建立要素数据库、界定景观的观赏效果，以景观数量多且质量好的点为最佳观景点；其次，综合利用 ArcGIS 表面、三维、缓冲分析工具在生产与生活性道路上分析各观景点的景观数量和质量，判断最佳观景点；最后，利用网络分析工具选取最佳观景路线。最佳观景点及最佳观景路线的选择有利于优化村落游赏规划、调整遗产保护范围，为遗产区管理和遗产保护提供新的思路。%Traditional vil ages have rich landscape and road network. Scenic route design is significant to traditional vil age landscape preservation and utilization. The paper studies viewing route design with ArcGIS technology in world cultural heritage site-Kaiping watchtowers case. Firstly analysis of landscape qualities recommend the best viewing points, then ArcGIS technology is used to analyze the amount and quality of dif erent viewpoints, and final y the best scenic route is defined by network tools. The best scenic route design wil help improve vil age planning and heritage preservation.

11. Lagrangian duality applied to the vehicle routing problem with time windows

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

2006-01-01

shortest path subproblem. We present a stabilized cutting-plane algorithm within the framework of linear programming for solving the associated Lagrangian dual problem. This algorithm creates easier constrained shortest path subproblems because less negative cycles are introduced and it leads to faster...... respectively, which to date are the largest problems ever solved to optimality. We have implemented the LBCP algorithm using the ABACUS open-source framework for solving mixed-integer linear-programs by branch, cut, and price....

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

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.

13. Considering Competition to Solve a Flight Schedule and Aircraft Routing Problem for Small Airlines

J. Díaz-Ramírez

2012-08-01

Full Text Available For the case of low-cost airlines, which are characterized by having a single fleet with a small number of airplanes, ina previous work, a heuristic algorithm (AFS-MRA was developed to simultaneously find the flight schedule and theaircraft routes subject to maintenance constraints. This work advances this algorithm by incorporating competition inthe planning process (MAFS-MRA.Within a time frame with a given demand data, competition is seen as a game with two players (one airline and all itscompetitors, where the strategies are all the potential origin-destinations that could be included in the flight schedule,and the payment matrix contains the objective function coefficients that depend on the market share and the routespreviously selected.Numerical experimentation was undertaken using real data for the case of two airlines that operate at TolucaInternational Airport in Mexico. It was found that, by considering competition, the occupation improves to 3% and thatthe number of flights required to satisfy the demand was reduced to 21%. Besides, the updating process reduces theprofit computation error in almost 80%, as compared to the real market behavior for the period under study.

14. Combining Single (Mixed) Metric Approach and Genetic Algorithm for QoS Routing Problem

胡世余; 谢剑英

2004-01-01

A hybrid algorithm for the delay constrained least cost path problem is proposed through combination of single (mixed) metric approach and genetic algorithm. Compared with the known genetic algorithm for the same problem, the new algorithm adopts integral coding scheme and new genetic operator, which reduces the search space and improves the efficiency of genetic operation. Meanwhile, the single (mixed) approach accelerates the convergence speed. Simulation results indicate that the proposed algorithm can find near-optimal even optimal solutions within moderate numbers of generations.

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

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

2008-01-01

Solomon benchmarks where we were able to close several instances. The results show that applying subset-row inequalities in the master problem significantly improves the lower bound and, in many cases, makes it possible to prove optimality in the root node.   Subject classifications: transportation...

16. The Complex Route to Success: Complex Problem-Solving Skills in the Prediction of University Success

Stadler, Matthias J.; Becker, Nicolas; Greiff, Samuel; Spinath, Frank M.

2016-01-01

Successful completion of a university degree is a complex matter. Based on considerations regarding the demands of acquiring a university degree, the aim of this paper was to investigate the utility of complex problem-solving (CPS) skills in the prediction of objective and subjective university success (SUS). The key finding of this study was that…

17. Finding optimal solutions for vehicle routing problem with pickup and delivery services with time windows: A dynamic programming approach based on state-space-time network representations

2015-01-01

Optimization of on-demand transportation systems and ride-sharing services involves solving a class of complex vehicle routing problems with pickup and delivery with time windows (VRPPDTW). This paper first proposes a new time-discretized multi-commodity network flow model for the VRPPDTW based on the integration of vehicles carrying states within space-time transportation networks, so as to allow a joint optimization of passenger-to-vehicle assignment and turn-by-turn routing in congested tr...

18. Disjunctive cuts in a branch-and-price algorithm for the capacitated vehicle routing problem

Røpke, Stefan

This talk presents computational results that show the usefulness of the general-purpose valid inequalities disjunctive cuts when applied to the CVRP. Results indicate that the disjunctive cuts are able to reduce the gap between lower bound and upper bound more than state-of-the-art problem speci...... specific inequalities. Results also indicate that introducing the cuts leads to a smaller branch and bound tree and faster solution times overall.......This talk presents computational results that show the usefulness of the general-purpose valid inequalities disjunctive cuts when applied to the CVRP. Results indicate that the disjunctive cuts are able to reduce the gap between lower bound and upper bound more than state-of-the-art problem...

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

Christiansen, Christian Holk; Lysgaard, Jens

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...... approach we have embedded this column generation scheme in a branch-and-price algorithm. Computational experiments on a large set of test instances show promising results....

20. The home health care routing and scheduling problem with interdependent services.

Mankowska, Dorota Slawa; Meisel, Frank; Bierwirth, Christian

2014-03-01

This paper presents a model for the daily planning of health care services carried out at patients' homes by staff members of a home care company. The planning takes into account individual service requirements of the patients, individual qualifications of the staff and possible interdependencies between different service operations. Interdependencies of services can include, for example, a temporal separation of two services as is required if drugs have to be administered a certain time before providing a meal. Other services like handling a disabled patient may require two staff members working together at a patient's home. The time preferences of patients are included in terms of given time windows. In this paper, we propose a planning approach for the described problem, which can be used for optimizing economical and service oriented measures of performance. A mathematical model formulation is proposed together with a powerful heuristic based on a sophisticated solution representation. PMID:23780750

1. Peek Arc Consistency

Bodirsky, Manuel

2008-01-01

This paper studies peek arc consistency, a reasoning technique that extends the well-known arc consistency technique for constraint satisfaction. In contrast to other more costly extensions of arc consistency that have been studied in the literature, peek arc consistency requires only linear space and quadratic time and can be parallelized in a straightforward way such that it runs in linear time with a linear number of processors. We demonstrate that for various constraint languages, peek arc consistency gives a polynomial-time decision procedure for the constraint satisfaction problem. We also present an algebraic characterization of those constraint languages that can be solved by peek arc consistency, and study the robustness of the algorithm.

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

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.

3. A hybrid genetic-simulated annealing algorithm for the location-inventory-routing problem considering returns 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. PMID:24489489

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

Yanhui Li; Hao Guo; Lin Wang; Jing Fu

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-routin...

5. Solving a Closed-Loop Location-Inventory-Routing Problem with Mixed Quality Defects Returns in E-Commerce by Hybrid Ant Colony Optimization Algorithm

Shuai Deng; Yanhui Li; Hao Guo; Bailing Liu

2016-01-01

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 effici...

6. Modeling and Solving the Liner Shipping Service Selection Problem

We address a tactical planning problem, the Liner Shipping Service Selection Problem (LSSSP), facing container shipping companies. Given estimated demand between various ports, the LSSSP entails selecting the best subset of non-simple cyclic sailing routes from a given pool of candidate routes, and...... transporting as much demand as possible over the chosen routes. Since most containers are sent directly or transshipped at most twice in current liner shipping networks, we impose limits on the number of transshipments for each container. The objective is to maximize the net revenue, i.e., revenue from demand...... served less shipping costs. We propose a new hop-constrained multi-commodity arc flow model for the LSSSP that is based on an augmented network containing, for each candidate route, an arc (representing a sub-path) between every pair of ports that the route visits. This sub-path construct permits us to...

7. Road and Street Centerlines - MO 2011 October MoDOT Roads - Routes (GDB)

NSGIC GIS Inventory (aka Ramona) — Routes represent a single linear feature, such as a city street or highway. Routes are linear features composed of one or more arcs or parts of an arc; for example,...

8. Bi-Objective Modelling for Hazardous Materials Road–Rail Multimodal Routing Problem with Railway Schedule-Based Space–Time Constraints

Sun, Yan; Lang, Maoxiang; Wang, Danzhu

2016-01-01

The transportation of hazardous materials is always accompanied by considerable risk that will impact public and environment security. As an efficient and reliable transportation organization, a multimodal service should participate in the transportation of hazardous materials. In this study, we focus on transporting hazardous materials through the multimodal service network and explore the hazardous materials multimodal routing problem from the operational level of network planning. To formulate this problem more practicably, minimizing the total generalized costs of transporting the hazardous materials and the social risk along the planned routes are set as the optimization objectives. Meanwhile, the following formulation characteristics will be comprehensively modelled: (1) specific customer demands; (2) multiple hazardous material flows; (3) capacitated schedule-based rail service and uncapacitated time-flexible road service; and (4) environmental risk constraint. A bi-objective mixed integer nonlinear programming model is first built to formulate the routing problem that combines the formulation characteristics above. Then linear reformations are developed to linearize and improve the initial model so that it can be effectively solved by exact solution algorithms on standard mathematical programming software. By utilizing the normalized weighted sum method, we can generate the Pareto solutions to the bi-objective optimization problem for a specific case. Finally, a large-scale empirical case study from the Beijing–Tianjin–Hebei Region in China is presented to demonstrate the feasibility of the proposed methods in dealing with the practical problem. Various scenarios are also discussed in the case study. PMID:27483294

9. Bi-Objective Modelling for Hazardous Materials Road-Rail Multimodal Routing Problem with Railway Schedule-Based Space-Time Constraints.

Sun, Yan; Lang, Maoxiang; Wang, Danzhu

2016-01-01

The transportation of hazardous materials is always accompanied by considerable risk that will impact public and environment security. As an efficient and reliable transportation organization, a multimodal service should participate in the transportation of hazardous materials. In this study, we focus on transporting hazardous materials through the multimodal service network and explore the hazardous materials multimodal routing problem from the operational level of network planning. To formulate this problem more practicably, minimizing the total generalized costs of transporting the hazardous materials and the social risk along the planned routes are set as the optimization objectives. Meanwhile, the following formulation characteristics will be comprehensively modelled: (1) specific customer demands; (2) multiple hazardous material flows; (3) capacitated schedule-based rail service and uncapacitated time-flexible road service; and (4) environmental risk constraint. A bi-objective mixed integer nonlinear programming model is first built to formulate the routing problem that combines the formulation characteristics above. Then linear reformations are developed to linearize and improve the initial model so that it can be effectively solved by exact solution algorithms on standard mathematical programming software. By utilizing the normalized weighted sum method, we can generate the Pareto solutions to the bi-objective optimization problem for a specific case. Finally, a large-scale empirical case study from the Beijing-Tianjin-Hebei Region in China is presented to demonstrate the feasibility of the proposed methods in dealing with the practical problem. Various scenarios are also discussed in the case study. PMID:27483294

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

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.