Showing papers on "Vehicle routing problem published in 1996"
TL;DR: The main problems of stochastic vehicle routing are described within a broad classification scheme and the most important contributions are summarized in table form.
652 citations
TL;DR: This paper develops simulated annealing metaheuristics for the vehicle routing and scheduling problem with time window constraints using the λ-interchange mechanism of Osman and thek-node interchange process of Christofides and Beasley.
Abstract: This paper develops simulated annealing metaheuristics for the vehicle routing and scheduling problem with time window constraints. Two different neighborhood structures, the λ-interchange mechanism of Osman and thek-node interchange process of Christofides and Beasley, are implemented. The enhancement of the annealing process with a short-term memory function via a tabu list is examined as a basis for improving the metaheuristic approach. Computational results on test problems from the literature as well as large-scale real-world problem are reported. The metaheuristics achieve solutions that compare favorably with previously reported results.
344 citations
TL;DR: A tabu search algorithm for the multi-depot vehicle routing problem with capacity and route length restrictions is described and is shown to outperform existing heuristics.
342 citations
TL;DR: A tabu search heuristic is developed for a version of the stochastic vehicle routing problem where customers are present at locations with some probabilities and have random demands and produces an optimal solution in 89.45% of cases.
Abstract: This paper considers a version of the stochastic vehicle routing problem where customers are present at locations with some probabilities and have random demands. A tabu search heuristic is developed for this problem. Comparisons with known optimal solutions on problems whose sizes vary from 6 to 46 customers indicate that the heuristic produces an optimal solution in 89.45% of cases, with an average deviation of 0.38% from optimality.
305 citations
TL;DR: In this paper, a fast and extremely effective heuristic is presented and tested on 67 problems taken from the literature and 40 new test problems and the computational results are presented in detail.
302 citations
TL;DR: These new developments are based on theoretical analysis, combine probabilistic and combinatorial modeling, and lead to new algorithms that produce near-optimal solutions, and a deeper understanding of uncertainty issues in vehicle routing.
Abstract: In recent years new insights and algorithms have been obtained for the classical, deterministic vehicle routing problem as well as for natural stochastic and dynamic variations of it These new developments are based on theoretical analysis, combine probabilistic and combinatorial modeling, and lead to new algorithms that produce near-optimal solutions, and a deeper understanding of uncertainty issues in vehicle routing In this paper, we survey these new developments with an emphasis on the insights gained and on the algorithms proposed
275 citations
TL;DR: A tabu search heuristic is developed for the vehicle routeing problem with multiple use of vehicles and is shown to produce high quality solutions on a series of test problems.
Abstract: The vehicle routeing problem with multiple use of vehicles is a variant of the standard vehicle routeing problem in which the same vehicle may be assigned to several routes during a given planning period. A tabu search heuristic is developed for this problem. It is shown to produce high quality solutions on a series of test problems.
247 citations
TL;DR: An exact column generation algorithm for integer programs with a large (implicit) number of columns is presented in this article, where the family of problems that can be treated includes standard partitioning problems such as bin packing and certain vehicle routing problems in which the columns generated have 0-1 compenents and a right-hand side vector of 1's.
243 citations
TL;DR: A tabu search heuristic for the vehicle routing problem with time windows is described, based on specialized local search heuristics that maintain the feasibility of the solution at all time.
Abstract: This paper describes a tabu search heuristic for the vehicle routing problem with time windows. The tabu search is based on specialized local search heuristics that maintain the feasibility of the solution at all time. Computational results on a standard set of test problems are reported, as well as comparisons with other heuristics.
227 citations
TL;DR: In this article, a wide variety of combinatorial optimization problems can be modelled as GTSPs, including location-routeing problems, material flow system design, post box collection, stochastic vehicle routeing and arc routeing.
Abstract: In the Generalized Travelling Salesman Problem (GTSP), the aim is to determine a least cost Hamiltonian circuit or cycle through several clusters of vertices. It is shown that a wide variety of combinatorial optimization problems can be modelled as GTSPs. These problems include location-routeing problems, material flow system design, post-box collection, stochastic vehicle routeing and arc routeing.
185 citations
TL;DR: A new local search approach based on a network flow model that is used to simultaneously evaluate several customer ejection and insertion moves is developed and incorporated into the procedure to overcome local optimality.
Abstract: We develop a new local search approach based on a network flow model that is used to simultaneously evaluate several customer ejection and insertion moves. We use this approach and a direct customer swap procedure to solve the well-known Vehicle Routing Problem. The capacity constraints are relaxed using penalty terms whose parameter values are adjusted according to time and search feedback. Tabu Search is incorporated into the procedure to overcome local optimality. More advanced issues such as intensification and diversification strategies are developed to provide effective enhancements to the basic tabu search algorithm. Computational experience on standard test problems is discussed and comparisons with best-known solutions are provided.
Book•
01 Oct 1996
TL;DR: Genetic Algorithms and Engineering Design is the only book to cover the most recent technologies and their application to manufacturing, presenting a comprehensive and fully up-to-date treatment of genetic algorithms in industrial engineering and operations research.
Abstract: From the Publisher:
The last few years have seen important advances in the use of genetic algorithms to address challenging optimization problems in industrial engineering. Genetic Algorithms and Engineering Design is the only book to cover the most recent technologies and their application to manufacturing, presenting a comprehensive and fully up-to-date treatment of genetic algorithms in industrial engineering and operations research. Beginning with a tutorial on genetic algorithm fundamentals and their use in solving constrained and combinatorial optimization problems, the book applies these techniques to problems in specific areas - sequencing, scheduling and vehicle routing, facility layout, location-allocation, and more. Each topic features a clearly written problem description, mathematical model, and summary of conventional heuristic algorithms. All algorithms are explained in intuitive, rather than highly-technical, language and are reinforced with illustrative figures and numerical examples. Ideal for both self-study and classroom use, this self-contained reference provides indispensable state-of-the-art guidance to profeccionals and students working in industrial engineering, management science, operations research, computer science, and artificial intelgence.
TL;DR: A route construction heuristic for the VRPBTW, as well as different local search heuristics to improve the initial solutions are described, which are within 2.5% of the known optimal solutions on average.
TL;DR: The algorithm proposed in this paper yields solutions almost as good as those produced by tabu search adaptations, but at only a small fraction of their computing time.
Abstract: Solutions produced by the first generation of heuristics for the vehicle routeing problem are often far from optimal. Recent adaptations of local search improvement heuristics, like tabu search, produce much better solutions but require increased computing time. However there are situations where good solutions must be obtained quickly. The algorithm proposed in this paper yields solutions almost as good as those produced by tabu search adaptations, but at only a small fraction of their computing time. This heuristic can be seen as an improved version of the original petal heuristic. On 14 benchmark test problems, the proposed heuristic yields solutions whose values lie on average within 2.38% of that of the best known solutions.
01 Jan 1996
TL;DR: A Parallel Tabu Search algorithm for the vehicle routing problem under capacity and distance restrictions and in the neighborhood search, the algorithm uses compound moves generated by an ejection chain process.
Abstract: In this paper we describe a Parallel Tabu Search algorithm for the vehicle routing problem under capacity and distance restrictions. In the neighborhood search, the algorithm uses compound moves generated by an ejection chain process. Parallel processing is used to explore the solution space more extensively and different parallel techniques are used to accelerate the search process. Tests were carried out on a network of SUNSparc workstations and computational results for a set of benchmark problems prove the efficiency of the algorithm proposed.
TL;DR: A heuristic algorithm is devised with a computer program which allows user-interaction, and provides a practical tool for planning gritter routes and test results from the interactive algorithm are found to outperform another existing approach which solves the same problem.
Abstract: In winter, when roads may become dangerously slippery due to frost, ice or snow, a de-icing agent (usually salt) is spread on them by a local authority for safety reasons. A gritter only needs to travel once down all those roads requiring treatment, as it can spread the salt onto both sides of the carriageway. The problem studied is how to design routes for gritters which will minimise costs. This problem is a type of Capacitated Arc Routeing Problem including consideration of multiple depot locations, limited vehicle capacities, time constraints on when roads must be gritted, roads with different priorities for gritting, the existence of one-way roads and salt-refilling locations. The objective function to be optimised depends on both the total distance travelled and the number and capacity of the gritters. A heuristic algorithm is devised with a computer program which allows user-interaction, and provides a practical tool for planning gritter routes. The model is linked to a GIS containing information on the road network for the County of Lancashire. Test results from the interactive algorithm are found to outperform another existing approach which solves the same problem.
TL;DR: A greedy route construction heuristic for a vehicle routing problem with backhauling using a fixed a priori ordering of customers to identify an ordering that produces good routes is described.
Abstract: In this paper, a greedy route construction heuristic for a vehicle routing problem with backhauling is described. This heuristic inserts customers one by one into the routes using a fixed a priori ordering of customers. Then, a genetic algorithm is used to identify an ordering that produces good routes. Numerical comparisons are provided with an exact algorithm and with other heuristic approaches.
TL;DR: A model to design vehicle routing when demand at the nodes is uncertain is developed, based on the heuristic “sweeping” algorithm, the rules of fuzzy arithmetic and fuzzy logic.
TL;DR: In this article, the authors present a characterization of the asymptotic optimal solution value for general distributions of service times, time windows, customer loads and locations, which leads to the development of a new algorithm based on formulating the problem as a stylized location problem.
Abstract: In the Vehicle Routing Problem with Time Windows, a set of customers are served by a fleet of vehicles of limited capacity, initially located at a central depot. Each customer provides a period of time in which they require service, which may consist of repair work or loading/unloading the vehicle. The objective is to find tours for the vehicles, such that each customer is served in its time window, the total load on any vehicle is no more than the vehicle capacity, and the total distance traveled is as small as possible. In this paper, we present a characterization of the asymptotic optimal solution value for general distributions of service times, time windows, customer loads and locations. This characterization leads to the development of a new algorithm based on formulating the problem as a stylized location problem. Computational results show that the algorithm is very effective on a set of standard test problems.
TL;DR: In this article, the optimal deployment of a vehicle fleet of truck-trailer combinations is investigated, where the opportunity is introduced to leave the trailer at a parking-place and visit some difficult customers with the easy manoeuvrable truck only.
TL;DR: In this article, an extension to ACVRP of the two well-known Clarke-Wright and Fisher-Jaikumar heuristic algorithms is proposed, which, starting with an initial infeasible solution, determines the final set of vehicle routes through an insertion procedure as well as intea-route and inter-route arc exchanges.
TL;DR: The nucleolus is formed, which minimizes maximum discontent among the players in a co-operative game in characteristic function form and gives conditions for when the core of the vehicle routing game is nonempty.
Abstract: In the vehicle routing cost allocation problem the aim is to find a good cost allocation method, i.e., a method that according to specified criteria allocates the cost of an optimal route configuration among the customers. We formulate this problem as a co-operative game in characteristic function form and give conditions for when the core of the vehicle routing game is nonempty.
One specific solution concept to the cost allocation problem is the nucleolus, which minimizes maximum discontent among the players in a co-operative game. The class of games we study is such that the values of the characteristic function are obtained from the solution of a set of mathematical programming problems. We do not require an explicit description of the characteristic function for all coalitions. Instead, by applying a constraint generation approach, we evaluate information about the function only when it is needed for the computation of the nucleolus.
TL;DR: Efficient techniques that take into account the above concept and which use a neighbourhood structure inspired from computational geometry are presented and a simple version of tabu search is embedded into the methods to improve the solutions further.
Abstract: The concept of 'nested methods' is adopted to solve the location-routeing problem. Unlike the sequential and iterative approaches, in this method we treat the routeing element as a sub-problem within the larger problem of location. Efficient techniques that take into account the above concept and which use a neighbourhood structure inspired from computational geometry are presented. A simple version of tabu search is also embedded into our methods to improve the solutions further. Computational testing is carried out on five sets of problems of 400 customers with five levels of depot fixed costs, and the results obtained are encouraging.
TL;DR: A concurrent scheduling approach, which allocates customers to more than one vehicle and assigns more thanOne customer to a vehicle at a time is proposed, which is a one-phase heuristic that can be reiterated when necessary.
TL;DR: A lower bound on the optimal total cost and a heuristic solution for the vehicle-routing problem are developed, which is shown to converge to the optimal solution, under mildprobabilistic conditions, as fast as N-0.5.
Abstract: In this article we consider a version of the vehicle-routing problem (VRP): A fleet of identical capacitated vehicles serves a system of one warehouse and N customers of two types dispersed in the plane. Customers may require deliveries from the warehouse, back hauls to the warehouse, or both. The objective is to design a set of routes of minimum total length to serve all customers, without violating the capacity restriction of the vehicles along the routes. The capacity restriction here, in contrast to the VRP without back hauls is complicated because amount of capacity used depends on the order the customers are visited along the routes. The problem is NP-hard. We develop a lower bound on the optimal total cost and a heuristic solution for the problem. The routes generated by the heuristic are such that the back-haul customers are served only after terminating service to the delivery customers. However, the heuristic is shown to converge to the optimal solution, under mildprobabilistic conditions, as fast as N-0.5. The complexity of the heuristic, as well as the computation of the lower bound, is U(N’) if all customers have unit demand size and O(N3 log N) otherwise, independently of the demand sizes. 0 1996 John Wiley & Sons, Inc. Improvement of a physical distribution system may have crucial consequences for a business’s performance. In certain sectors of the economy, transportation costs amount to a fifth (lumber and wood products) or even a quarter (petroleum, stone, clay, and glass products) of the average sales dollar; see [ 201. A careful design of the distribution system may thus yield significant cost savings to the company, usually by exploiting joint procurement possibilities to satisfy the needs of multiple locations. This potential for savings arises in particular in systems where goods are distributed through a fleet of vehicles combining visits to distinct locations into efficient routes. The problem we study here deals with a single-period, single-warehouse distribution system with two sets of customers dispersed in the plane. The first set, denoted by D, consists of delivery customers that require a delivery of goods from the warehouse, whereas the second set, denoted by B, consists of back-haul customers that need to deliver goods from their location to the warehouse. It is possible for a customer to require both a delivery and a back haul. (Note that the literature distinguishes between back-haul customers and pickup customers: A pickup customer may deliver goods to any of the delivery customers and the warehouse. In this research we restrict ourselves to delivery and back-haul customers only.) In order to avoid excessive notation we will assume a single-commodity problem, and in Section 5 we explain the modifications needed for the multicommodity case. Each customer is characterized by its geographic location and its requirement size for either delivery or back haul. The company’s fleet of vehicles is used to deliver and back haul stock. All vehicles are assumed to have identical capacities. We use the Euclidean metric as the dis
TL;DR: A competitive neural network model and a genetic algorithm are used to improve the initialization and construction phase of a parallel insertion heuristic for the vehicle routing problem with time windows.
Abstract: A competitive neural network model and a genetic algorithm are used to improve the initialization and construction phase of a parallel insertion heuristic for the vehicle routing problem with time windows. The neural network identifies seed customers that are distributed over the entire geographic area during the initialization phase, while the genetic algorithm finds good parameter settings in the route construction phase that follows. Computational results on a standard set of problems are also reported.
TL;DR: This paper focuses on the unit-demand case, known as the capacitated spanning tree problem, for which it presents computational experience on a range of instances with up to 200 nodes, and considers the general- demand case, based on a cutting plane algorithm.
Abstract: A basic problem in telecommunications network design is that of designing a capacitated centralized processing network. Such a network has a central processor that must be linked via a tree topology to several remote terminals that have specified demands. Each subtree off of the root is constrained to have at most a fixed, limited demand, represented by the sum of the demands of the nodes of the subtree. Finding provably optimal solutions to this class of problems has been surprisingly difficult, particularly for certain types of instances and choices of parameters. This paper presents computational results for the problem, based on a cutting plane algorithm. We first focus on the unit-demand case, known as the capacitated spanning tree problem, for which we present computational experience on a range of instances with up to 200 nodes. We then consider the general-demand case and report on branch-and-cut as well as cutting plane computations on a range of instances, including some from the vehicle routing...
TL;DR: An improvement heuristic for vehicle routing problems that finds complex customer interchanges to improve an initial solution and shows that Simulated Trading is better suited for problems with time windows.
01 Mar 1996
TL;DR: FleetManager as discussed by the authors is a decision support system (DSS) developed for use by New Zealand milk tanker schedulers and is designed to aid them in creating or improving milk tanker routes using their experience and preferences.
Abstract: We report on a decision support system (DSS) that recommends solutions to a particular version of the vehicle routing problem occurring in the New Zealand dairy industry. FleetManager is a DSS developed for use by New Zealand milk tanker schedulers and is designed to aid them in creating or improving milk tanker routes using their experience and preferences. The DSS uses multiple, resizable, overlapping windows to assist schedulers in their tasks. Users can also interact with the system through a graphical interface which displays a road map of the area and the location of the milk processing plants and milk suppliers. FleetManager also contains the option of automatically creating vehicle routes, which can be modified by the users. The system can be used to analyze a wide variety of “What-if?” scenarios with potential cost impacts.
TL;DR: An integer linear programming formulation of SVRAP is presented and it is shown how SVR AP provides a unifying framework for understanding a number of the papers and problems presented in the literature.
Abstract: In this paper the Vehicle Routing-Allocation Problem (VRAP) is presented. In VRAP not all customers need be visited by the vehicles. However customers not visited either have to be allocated to some customer on one of the vehicle tours or left isolated. We concentrate our discussion on the Single Vehicle Routing-Allocation Problem (SVRAP). An integer linear programming formulation of SVRAP is presented and we show how SVRAP provides a unifying framework for understanding a number of the papers and problems presented in the literature. Specifically the covering tour problem, the covering salesman problem, the median tour problem, the maximal covering tour problem, the travelling salesman problem, the generalised travelling salesman problem, the selective travelling salesman problem, the prize collecting travelling salesman problem, the maximum covering/shortest path problem, the maximum population/shortest path problem, the shortest covering path problem, the median shortest path problem, the minimum covering/shortest path problem and the hierarchical network design problem are special cases/variants of SVRAP.