13 research outputs found

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

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    [EN] This paper addressed the heterogeneous fixed fleet open vehicle routing problem (HFFOVRP), in which the vehicles are not required to return to the depot after completing a service. In this new problem, the demands of customers are fulfilled by a heterogeneous fixed fleet of vehicles having various capacities, fixed costs and variable costs. This problem is an important variant of the open vehicle routing problem (OVRP) and can cover more practical situations in transportation and logistics. Since this problem belongs to NP-hard Problems, An approach based on column generation (CG) is applied to solve the HFFOVRP. A tight integer programming model is presented and the linear programming relaxation of which is solved by the CG technique. Since there have been no existing benchmarks, this study generated 19 test problems and the results of the proposed CG algorithm is compared to the results of exact algorithm. Computational experience confirms that the proposed algorithm can provide better solutions within a comparatively shorter period of time.Yousefikhoshbakht, M.; Dolatnejad, A. (2017). A Column Generation for the Heterogeneous Fixed Fleet Open Vehicle Routing Problem. International Journal of Production Management and Engineering. 5(2):55-71. doi:10.4995/ijpme.2017.5916SWORD557152Aleman, R. E., & Hill, R. R. (2010). A tabu search with vocabulary building approach for the vehicle routing problem with split demands. International Journal of Metaheuristics, 1(1), 55. doi:10.1504/ijmheur.2010.033123Anbuudayasankar, S. P., Ganesh, K., Lenny Koh, S. C., & Ducq, Y. (2012). Modified savings heuristics and genetic algorithm for bi-objective vehicle routing problem with forced backhauls. Expert Systems with Applications, 39(3), 2296-2305. doi:10.1016/j.eswa.2011.08.009Brandão, J. (2009). A deterministic tabu search algorithm for the fleet size and mix vehicle routing problem. European Journal of Operational Research, 195(3), 716-728. doi:10.1016/j.ejor.2007.05.059Çatay, B. (2010). A new saving-based ant algorithm for the Vehicle Routing Problem with Simultaneous Pickup and Delivery. Expert Systems with Applications, 37(10), 6809-6817. doi:10.1016/j.eswa.2010.03.045Dantzig, G. B., & Ramser, J. H. (1959). The Truck Dispatching Problem. Management Science, 6(1), 80-91. doi:10.1287/mnsc.6.1.80Gendreau, M., Guertin, F., Potvin, J.-Y., & Séguin, R. (2006). Neighborhood search heuristics for a dynamic vehicle dispatching problem with pick-ups and deliveries. Transportation Research Part C: Emerging Technologies, 14(3), 157-174. doi:10.1016/j.trc.2006.03.002Gendreau, M., Laporte, G., Musaraganyi, C., & Taillard, É. D. (1999). A tabu search heuristic for the heterogeneous fleet vehicle routing problem. Computers & Operations Research, 26(12), 1153-1173. doi:10.1016/s0305-0548(98)00100-2Lei, H., Laporte, G., & Guo, B. (2011). The capacitated vehicle routing problem with stochastic demands and time windows. Computers & Operations Research, 38(12), 1775-1783. doi:10.1016/j.cor.2011.02.007Li, X., Leung, S. C. H., & Tian, P. (2012). A multistart adaptive memory-based tabu search algorithm for the heterogeneous fixed fleet open vehicle routing problem. Expert Systems with Applications, 39(1), 365-374. doi:10.1016/j.eswa.2011.07.025Li, X., Tian, P., & Aneja, Y. P. (2010). An adaptive memory programming metaheuristic for the heterogeneous fixed fleet vehicle routing problem. Transportation Research Part E: Logistics and Transportation Review, 46(6), 1111-1127. doi:10.1016/j.tre.2010.02.004Penna, P. H. V., Subramanian, A., & Ochi, L. S. (2011). An Iterated Local Search heuristic for the Heterogeneous Fleet Vehicle Routing Problem. Journal of Heuristics, 19(2), 201-232. doi:10.1007/s10732-011-9186-ySaadati Eskandari, Z., YousefiKhoshbakht, M. (2012). Solving the Vehicle Routing Problem by an Effective Reactive Bone Route Algorithm, Transportation Research Journal, 1(2), 51-69.Subramanian, A., Drummond, L. M. A., Bentes, C., Ochi, L. S., & Farias, R. (2010). A parallel heuristic for the Vehicle Routing Problem with Simultaneous Pickup and Delivery. Computers & Operations Research, 37(11), 1899-1911. doi:10.1016/j.cor.2009.10.011Syslo, M., Deo, N., Kowalik, J. (1983). Discrete Optimization Algorithms with Pascal Programs, Prentice Hall.Taillard, E. D. (1999). A heuristic column generation method for the heterogeneous fleet VRP, RAIRO Operations Research, 33, 1-14. https://doi.org/10.1051/ro:1999101Tarantilis, C. D., & Kiranoudis, C. T. (2007). A flexible adaptive memory-based algorithm for real-life transportation operations: Two case studies from dairy and construction sector. European Journal of Operational Research, 179(3), 806-822. doi:10.1016/j.ejor.2005.03.059Wang, H.-F., & Chen, Y.-Y. (2012). A genetic algorithm for the simultaneous delivery and pickup problems with time window. Computers & Industrial Engineering, 62(1), 84-95. doi:10.1016/j.cie.2011.08.018Yousefikhoshbakht, M., Didehvar, F., & Rahmati, F. (2013). Solving the heterogeneous fixed fleet open vehicle routing problem by a combined metaheuristic algorithm. International Journal of Production Research, 52(9), 2565-2575. doi:10.1080/00207543.2013.855337Yousefikhoshbakht, M., & Khorram, E. (2012). Solving the vehicle routing problem by a hybrid meta-heuristic algorithm. Journal of Industrial Engineering International, 8(1). doi:10.1186/2251-712x-8-1

    Solving the Multiple Traveling Salesman Problem by a Novel Meta-heuristic Algorithm

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    The multiple traveling salesman problem (MTSP) is a generalization of the famous traveling salesman problem (TSP), where more than one salesman is used in the solution. Although the MTSP is a typical kind of computationally complex combinatorial optimization problem, it can be extended to a wide variety of routing problems. This paper presents an efficient and evolutionary optimization algorithm which has been developed through combining Modified Imperialist Competitive Algorithm and Lin-Kernigan Algorithm (MICA) in order to solve the MTSP.  In the proposed algorithm, an absorption function and several local search algorithms as a revolution operator are used. The performance of our algorithm was tested on several MTSP benchmark problems and the results confirmed that the MICA performs well and is quite competitive with other meta-heuristic algorithms

    An Efficient Solution for the VRP by Using a Hybrid Elite Ant System

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    The vehicle routing problem (VRP) is a well-known NP-Hard problemin operation research which has drawn enormous interest from many researchers duringthe last decades because of its vital role in planning of distribution systems andlogistics. This article presents a modified version of the elite ant system (EAS) algorithmcalled HEAS for solving the VRP. The new version mixed with insert and swapalgorithms utilizes an effective criterion for escaping from the local optimum points.In contrast to the classical EAS, the proposed algorithm uses only a global updatingwhich will increase pheromone on the edges of the best (i.e. the shortest) route andwill at the same time decrease the amount of pheromone on the edges of the worst(i.e. the longest) route. The proposed algorithm was tested using fourteen instancesavailable from the literature and their results were compared with other well-knownmeta-heuristic algorithms. Results show that the suggested approach is quite effectiveas it provides solutions which are competitive with the best known algorithms in theliterature

    A Mixed Integer Programming Formulation for the Heterogeneous Fixed Fleet Open Vehicle Routing Problem

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    The heterogeneous fixed fleet open vehicle routing problem (HFFOVRP) is one of the most significant extension problems of the open vehicle routing problem (OVRP). The HFFOVRP is the problem of designing collection routes to a number of predefined nodes by a fixed fleet number of vehicles with various capacities and related costs. In this problem, the vehicle doesn’t return to the depot after serving the last customer. Because of its numerous applications in industrial and service problems, a new model of the HFFOVRP based on mixed integer programming is proposed in this paper. Furthermore, due to its NP-hard nature, an ant colony system (ACS) algorithm was proposed. Since there were no existing benchmarks, this study generated some test problems. From the comparison with the results of exact algorithm, the proposed algorithm showed that it can provide better solutions within a comparatively shorter period of time

    Solving the Traveling Salesman Problem: A Modified Metaheuristic Algorithm

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    The traveling salesman problem (TSP) is one of the most important issues in combinatorial optimization problems that are used in many engineering sciences and has attracted the attention of many scientists and researchers. In this issue, a salesman starts to move from a desired node called warehouse and returns to the starting place after meeting n customers provided that each customer is only met once. The aim of this issue is to determine a cycle with a minimum cost for this salesman. One of the major weaknesses of the PSO algorithm in the classical version is that it gets stuck in local optimizations. Therefore, in the proposed algorithm, called MPSO, the best solution in the current iteration is also used in the movement step. In addition, a variety of local search algorithms are provided that are used when better answers are generated than before. Also, a new method for moving the particle towards the best particle is presented, which, in addition to probably increasing the quality of the new answer, prevents the premature convergence of the algorithm due to consideration of the concept of random. The results evaluated with the results of several metaheuristic algorithms in the literature show the efficiency of the MPSO algorithm because it has been able to achieve excellent solutions in most of these instances

    A Benders Decomposition Method for Dynamic Facility Location in Integrated Closed Chain Problem

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    The design for integrating the forward-reverse logistics network has attracted growing attention with the relentless pressures from environmental and social requirements to increase operational efficiency and support sustainable operations. Therefore, a dynamic facility in the closed chain is presented for the first time. In this problem, a set of facilities with determined locations are used based on whether they serve as forward-reverse, or joint facilities dealing with products from both directions. The objective is to minimize the total costs, including fixed location, fixed ordering, inventory holding, transportation, and reprocessing costs. In this paper, a mixed integer nonlinear program (MINLP) of a single type of forwarding product and a single type of returned product is proposed and a Benders decomposition method (BDM) is developed to solve the problem efficiently. The computational results on several randomly generated issues demonstrate that the proposed algorithm can efficiently solve the MINLP model compared to other algorithms

    An Effective Rank Based Ant System Algorithm for Solving the Balanced Vehicle Routing Problem

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    The vehicle routing problem (VRP) is one of the most significant problems of the operational research problems which has numerous applications in industrial and service problems. The VRP is the problem of designing optimal delivery from a given depot in order to satisfy the demand of the customer population by a similar fleet of vehicles. It is noted that a considerable part of the drivers’ benefits is related to their traveled distance; therefore, the balance of the route based on vehicles’ traved distance is important to obtain drivers’ satisfaction. This paper presents a balance based on the vehicles’ traveled route called balanced vehicle routing problem (BCVRP) and then a model integer linear programming is proposed for the BCVRP. Because solving of this problem as same as VRP is difficult, an effective rank based ant system (ERAS) algorithm is proposed in this paper. In addition, to show the efficiency of the proposed ERAS, a number of test problems in both small and large scales involving 10 to 199 customers have been considered and solved. The computational results show that the proposed algorithm results are better than results of classical rank based ans system (RAS) and exact algorithm for solving the BCVRP within a comparatively shorter period of time

    A hybrid modified meta-heuristic algorithm for solving the traveling salesman problem

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    Abstract The traveling salesman problem (TSP) is one of the most important combinational optimization problems that has nowadays received much attention because of its practical applications in industrial and service problems. In this paper, a hybrid twophase meta-heuristic algorithm called MACSGA used forsolving the TSPis presented. At the first stage, the TSP is solved by themodified ant colony system (MACS) in each iteration, and at the second stage, the modified genetic algorithm (GA) and 2-opt local searchare used for improving the solutions of the ants for that iteration. This process avoids the premature convergence and makes better solutions. Computational results on several standard instances of TSP show the efficiency of theproposedalgorithm comparedwith the GA, ant colony optimization and other meta-heuristic algorithms
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