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作者： Victoria Rebillas Loredo Universitat Politecnica de Catalunya

学位级别：博士

In real-world logistic operations there are a lot of situations that can be exploited to get better operational strategies. It is important to study these new alternatives, because they can represent significant cost reductions to the companies working with physical distribution. This thesis defines the Multi-Depot Vehicle Routing Problem with Vehicle Interchanges. In this problem, both vehicle capacities and duration limits on the routes of the drivers are imposed. To favor a better utilization of the available capacities and working times, it is allowed to combine pairs of routes at predefined interchange locations. The objective of this thesis is to analyze and solve the Multi-Depot Vehi- cle Routing Problem adding the possibility to interchange vehicles at predefined points. With this strategy, it is possible to reduce the total costs and the number of used routes with respect to the classical approach: the Multi-Depot Vehicle Rout- ing Problem. It should be noted that the Multi-Depot Vehicle Routing Problem is more challenging and sophisticated than the single-depot Vehicle Routing Problem. Besides, most exact algorithms for solving the classical Vehicle Routing Problem are difficult to adapt in order to solve the Multi-Depot Vehicle Routing Problem (Montoya-Torres et al., 2015). From the complexity point of view, the Multi-Depot Vehicle Routing Problem with Vehicle Interchanges is NP-Hard, since it is an exten- sion of the classical problem, which is already NP-Hard. We present a tight bound on the costs savings that can be attained allowing interchanges. Three integer programming formulations are proposed based on the classical vehicle-flow formulations of the Multi-Depot Vehicle Routing Problem. One of these formulations was solved with a branch-and-bound algorithm, and the other two formulations, with branch-and-cut algorithms. Due to its great symmetry, the first formulation is only able to solve small instances. To increase the dimension of the instances

关键词： combinatorial optimization routing the Multi-Depot Vehicle Routing Problem Rich Vehicle Routing Problem vehicle interchanges branch-and-cut algorithm

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Robust model and solution algorithm for the railroad blocking problem under uncertainty

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SCIENTIA IRANICA 2018年第4期25卷 1916-1930页

作者： Hasany, R. M. Shafahi, Y. Sharif Univ Technol Dept Civil Engn POB 11155-8639 Tehran Iran

The railroad blocking problem emerges as an important issue at the tactical level of planning in freight rail transportation. This problem consists of determining the optimal paths for freight cars in a rail network. Often, demand and supply resource indicators are assumed certain;hence, the solution obtained from a certain model might not be optimal or even feasible in practice due to the stochastic nature of these parameters. To address this issue, this paper develops a robust model for this problem with uncertain demand and travel time as supply resource indicators. Since the model combines integer variables and nonlinear functions, a branch-and-cut algorithm is used to solve the linearized version of the robust model. The performance of the proposed algorithm in several instances is examined and discussed. The high efficiency and effectiveness of the proposed algorithm are demonstrated through a comparison with a well-known solver. Finally, this algorithm is applied to a blocking problem of the railways of Iran. The results show that, by ignoring approximately 10% of the optimal value of the deterministic model, we have an optimal solution that remains unchanged with a probability of more than 0.98. (C) 2018 Sharif University of Technology. All rights reserved.

关键词： Railroad blocking problem Robust optimization branch-and-cut algorithm Uncertainty Railway planning

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Blood inventory-routing problem under uncertainty

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JOURNAL OF INTELLIGENT & FUZZY SYSTEMS 2017年第1期32卷 467-481页

作者： Kazemi, Seyed Mahmood Rabbani, Masoud Tavakkoli-Moghaddam, Reza Shahreza, Farid Aboihassani Univ Tehran Sch Ind Engn Coll Engn Tehran Iran Univ Tehran Med Sci Natl Inst Hlth Res Tehran Iran

The problem of delivering blood products from community blood centers to the demand points including hospital blood banks falls within the context of perishable inventory-routing problems (PIRP). This is due to the fact that the delivery should be made on the right time with the right delivery quantity at the right place such that the total possible perished items as well as routing and inventory costs are minimized. However, some unique characteristics of blood logistics including assigned and unassigned inventories, crossmatch release period, transfusion to crossmatch ratio and older-first policy have made the problem more difficult than the routine PIRPs and thus proposing a new modeling of the problem is required. In this paper, we first develop a mixed integer programming formulation for blood inventory-routing problem. Then, to cope with uncertainties, a novel robust possibilistic programming (RPP) approach is proposed. Afterward, a novel iterative branch-and-cut is developed to solve a number of numerical examples to optimality. Finally, by implementing a test scenario on the data inspired from a real Iranian blood supply chain, the significance and applicability of the proposed model and RPP approach is proven.

关键词： Healthcare management blood inventory-routing perishable products robust possibilistic programming branch-and-cut algorithm

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The ring-star problem: A new integer programming formulation and a branch-and-cut algorithm

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DISCRETE APPLIED MATHEMATICS 2011年第16期159卷 1901-1914页

作者： Simonetti, L. Frota, Y. de Souza, C. C. Univ Estadual Campinas Inst Comp BR-13852970 Campinas SP Brazil Univ Fed Fluminense Dept Comp Sci BR-22410240 Niteroi RJ Brazil

A ring star in a graph is a subgraph that can be decomposed into a cycle (or ring) and a set of edges with exactly one vertex in the cycle. In the minimum ring-star problem (MRSP) the cost of a ring star is given by the sum of the costs of its edges, which vary, depending on whether the edge is part of the ring or not. The goal is to find a ring-star spanning subgraph minimizing the sum of all ring and assignment costs. In this paper we show that the MRSP can be reduced to a minimum (constrained) Steiner arborescence problem on a layered graph. This reduction is used to introduce a new integer programming formulation for the MRSP. We prove that the dual bound generated by the linear relaxation of this formulation always dominates the one provided by an early model from the literature. Based on our new formulation, we developed a branch-and-cut algorithm for the MRSP. On the primal side, we devised a GRASP heuristic to generate good upper bounds for the problem. Computational tests with these algorithms were conducted on a benchmark of public domain. In these experiments both our exact and heuristics algorithms had excellent performances, noticeably in dealing with instances whose optimal solution has few vertices in the ring. In addition, we also investigate the minimum spanning caterpillar problem (MSCP) which has the same input as the MRSP and admits feasible solutions that can be viewed as ring stars with paths in the place of rings. We present an easy reduction of the MSCP to the MRSP, which makes it possible to solve to optimality instances of the former problem too. Experiments carried out with the MSCP revealed that our branch-and-cut algorithm is capable to solve to optimality instances with up to 200 vertices in reasonable time. (C) 2011 Elsevier B.V. All rights reserved.

关键词： Ring-star problem Caterpillar trees Integer programming branch-and-cut algorithm

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The ring-star problem: A new integer programming formulation and a branch-and-cut algorithm

The ring-star problem: A new integer programming formulation...

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8th Cologne/Twente Workshop on Graphs and Combinatorial Optimization (CTW 2009)

作者： Simonetti, L. Frota, Y. de Souza, C. C. Univ Estadual Campinas Inst Comp BR-13852970 Campinas SP Brazil Univ Fed Fluminense Dept Comp Sci BR-22410240 Niteroi RJ Brazil

关键词： Ring-star problem Caterpillar trees Integer programming branch-and-cut algorithm

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The multi-terminal vertex separator problem: Complexity, Polyhedra and algorithms

The multi-terminal vertex separator problem: Complexity, Pol...

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作者： Youcef Magnouche PSL Research University

学位级别：博士

This thesis deals with the multi-terminal vertex separator problem. Given a graph G = (V ∪T, E) with V ∪T the set of vertices, where T is a set of terminals, and a weight function w: V → Z, associated with nonterminal nodes, the multi-terminal vertex separator problem consists in partitioning V ∪ T into k + 1 subsets {S, V 1,..., V k } such that there is no edge between two different subsets V i and V j, each V i contains exactly one terminal and the weight of S is minimum. In this thesis, we consider the problem from a polyhedral point of view. We give two integer programming formulations for the problem, for one of them, we investigate the related polyhedron and discuss its polyhedral structure. We describe some valid inequalities and characterize when these inequalities define facets. We also derive separation algorithms for these inequalities. Using these results, we develop a branch-and-cut algorithm for the problem, along with an extensive computational study is presented. We also study the multi-terminal vertex separator polytope in the graphs decompos- able by one node cutsets. If G is a graph that decomposes into G 1 and G 2, we show that the multi-terminal vertex separator polytope in G can be described from two lin- ear systems related to G 1 and G 2. This gives rise to a technique for characterizing the multi-terminal vertex separator polytope in the graphs that are recursively decompos- able. We also obtain a procedure to describe facets for this polytope and show that the multi-terminal vertex separator problem can also be decomposed. Applications of this technique are also discussed. Moreover, we propose three extended formulations for the problem and derive branch- and-Price and branch-and-cut-and-Price algorithms. For each formulation we present a column generation scheme to solve the linear relaxation, the way to compute the dual bound and the branching scheme. We present computational results and discuss the performance of each algorithm. Further,

关键词： Combinatorial optimization Polytope Facet branch-and-cut algorithm branch-and-Price algorithm Composition of polyhedra

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The green vehicle routing problem: A heuristic based exact solution approach

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APPLIED SOFT COMPUTING 2016年 39卷 154-164页

作者： Koc, Cagri Karaoglan, Ismail HEC Montreal CIRRELT Montreal PQ Canada HEC Montreal Canada Res Chair Distribut Management Montreal PQ Canada Selcuk Univ Dept Ind Engn Konya Turkey

This paper develops a simulated annealing heuristic based exact solution approach to solve the green vehicle routing problem (G-VRP) which extends the classical vehicle routing problem by considering a limited driving range of vehicles in conjunction with limited refueling infrastructure. The problem particularly arises for companies and agencies that employ a fleet of alternative energy powered vehicles on transportation systems for urban areas or for goods distribution. Exact algorithm is based on the branch-and-cut algorithm which combines several valid inequalities derived from the literature to improve lower bounds and introduces a heuristic algorithm based on simulated annealing to obtain upper bounds. Solution approach is evaluated in terms of the number of test instances solved to optimality, bound quality and computation time to reach the best solution of the various test problems. Computational results show that 22 of 40 instances with 20 customers can be solved optimally within reasonable computation time. (C) 2015 Elsevier B.V. All rights reserved.

关键词： The green vehicle routing problem Mixed integer programming formulation branch-and-cut algorithm Simulated annealing

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Solving the Single Vehicle Routing Problem with Variable Capacity

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TRANSPORTATION SCIENCE 2016年第2期50卷 708-719页

作者： Louveaux, Francois V. Salazar-Gonzalez, Juan-Jose Univ Namur Dept Business Adm B-5000 Namur Belgium Univ La Laguna DEIOC Tenerife 38271 Spain

This paper considers the classical vehicle routing problem (VRP) where the vehicle capacity is not fixed. Indeed, at the moment of acquiring (or renting) the vehicle that will serve all customers, there is some freedom of choice. A larger vehicle capacity implies a lower total distance travelled but larger operating costs. The reverse is true for a smaller vehicle. This paper gives an approach to select the best capacity and the best route to minimize a function of the acquisition cost and travelled distance. We first consider an enumerative approach, which consists of solving a sequence of VRPs, starting from the one having the largest capacity. The number of VRPs to solve using this approach is unknown. Based on computational experiments, this number is mostly large in our benchmark instances. We then proceed to a direct approach based on the two-index formulation of the VRP. We introduce several valid inequalities that allow us to have an integer linear programming formulation of the VRP with fixed vehicle capacity. We describe separation procedures for these inequalities. We conclude with computational results that confirm the utility of these inequalities when solving benchmark VRP instances.

关键词： vehicle routing problem unknown vehicle capacity branch-and-cut algorithm

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A Heuristic Method Based on the branch and cut algorithm to the Transmission System Expansion Planning Problem

A Heuristic Method Based on the Branch and Cut Algorithm to ...

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General Meeting of the IEEE-Power-and-Energy-Society (PES)

作者： Sousa, Aldir S. Asada, Eduardo N. Univ Sao Paulo Dept Elect Engn Sao Carlos Sch Engn BR-13566590 Sao Carlos SP Brazil

ISBN: (纸本)9781457710018

In this paper we introduce a new heuristic algorithm to the centralized long-term transmission system expansion planning problem. The proposed method introduces cuts (new constraints) to the mathematical model to force generating feasible solutions to the DC model. The application of the strategy resulted in good solutions for the DC model. The computational results demonstrate the efficiency of the proposed method when applied to IEEE-24 bus system, Brazilian Southern System and Colombian system.

关键词： Transmission System Expansion Planning Heuristic Methods branch-and-Bound algorithm branch-and-cut algorithm

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Two-phase branch-and-cut for the mixed capacitated general routing problem

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2015年第1期243卷 17-29页

作者： Irnich, Stefan Lagana, Demetrio Schlebusch, Claudia Vocaturo, Francesca Johannes Gutenberg Univ Mainz Gutenberg Sch Management & Econ Chair Logist Management D-55128 Mainz Germany Univ Calabria Dept Mech Energy & Management Engn I-87036 Arcavacata Di Rende CS Italy ProCom GmbH D-52070 Aachen Germany Univ Calabria Dept Econ Stat & Finance I-87036 Arcavacata Di Rende CS Italy

The Mixed Capacitated General Routing Problem (MCGRP) is defined over a mixed graph, for which some vertices must be visited and some links must be traversed at least once. The problem consists of determining a set of least-cost vehicle routes that satisfy this requirement and respect the vehicle capacity. Few papers have been devoted to the MCGRP, in spite of interesting real-world applications, prevalent in school bus routing, mail delivery, and waste collection. This paper presents a new mathematical model for the MCGRP based on two-index variables. The approach proposed for the solution is a two-phase branch-and-cut algorithm, which uses an aggregate formulation to develop an effective lower bounding procedure. This procedure also provides strong valid inequalities for the two-index model. Extensive computational experiments over benchmark instances are presented. (C) 2014 Elsevier B.V. All rights reserved.

关键词： General routing problem Mixed graph Integer programming branch-and-cut algorithm

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