VNU-UET Repository: No conditions. Results ordered -Date Deposited. 2024-03-28T16:22:23ZEPrintshttp://eprints.uet.vnu.edu.vn/images/sitelogo.pnghttps://eprints.uet.vnu.edu.vn/eprints/2020-09-14T02:55:49Z2020-09-14T02:55:49Zhttp://eprints.uet.vnu.edu.vn/eprints/id/eprint/4061This item is in the repository with the URL: http://eprints.uet.vnu.edu.vn/eprints/id/eprint/40612020-09-14T02:55:49ZA new constraint programming model and a linear programming-based adaptive large neighborhood search for the vehicle routing problem with synchronization constraintsWe consider a vehicle routing problem which seeks to minimize cost subject to time window and synchronization constraints. In this problem, the fleet of vehicles is categorized into regular and special vehicles. Some customers require both vehicles’ services, whose service start times at the customer are synchronized. Despite its important real-world application, this problem has rarely been studied in the literature. To solve the problem, we propose a Constraint Programming (CP) model and an Adaptive Large Neighborhood Search (ALNS) in which the design of insertion operators is based on solving linear programming (LP) models to check the insertion feasibility. A number of acceleration techniques is also proposed to significantly reduce the computational time. The computational experiments show that our new CP model finds better solutions than an existing CP-based ALNS, when used on small instances with 25 customers and with a much shorter running time. Our LP-based ALNS dominates the CP-based ALNS, in terms of solution quality, when it provides solutions with better objective values, on average, for all instance classes. This demonstrates the advantage of using linear programming instead of constraint programming when dealing with a variant of vehicle routing problems with relatively tight constraints, which is often considered to be more favorable for CP-based methods. We also adapt our algorithm to solve a well-studied variant of the problem, and the obtained results show that the algorithm provides good solutions as state-of-the-art approaches and improves four best known solutions.Minh Hoang Haminhhoang.ha@vnu.edu.vnTat Dat NguyenDuy Thinh NguyenHoang Giang PhamThuy DoLouis-Martin Rousseau2020-09-14T02:52:10Z2020-09-14T02:52:41Zhttp://eprints.uet.vnu.edu.vn/eprints/id/eprint/4060This item is in the repository with the URL: http://eprints.uet.vnu.edu.vn/eprints/id/eprint/40602020-09-14T02:52:10ZSolving the k-dominating set problem on very large-scale networksThe well-known minimum dominating set problem (MDSP) aims to construct the minimum-size subset of vertices in a graph such that every other vertex has at least one neighbor in the subset. In this article, we study a general version of the problem that extends the neighborhood relationship: two vertices are called neighbors of each other if there exists a path through no more than k edges between them. The problem called “minimum k-dominating set problem” (MkDSP) becomes the classical dominating set problem if k is 1 and has important applications in monitoring large-scale social networks. We propose an efficient heuristic algorithm that can handle real-world instances with up to 17 million vertices and 33 million edges. This is the first time such large graphs are solved for the minimum k-dominating set problemMinh Hai NguyenMinh Hoang Haminhhoang.ha@vnu.edu.vnDiep Nguyen NDiep.Nguyen@uts.edu.auThe Trung Trantrung@fpt.edu.vn2019-12-10T15:47:06Z2019-12-12T11:18:02Zhttp://eprints.uet.vnu.edu.vn/eprints/id/eprint/3674This item is in the repository with the URL: http://eprints.uet.vnu.edu.vn/eprints/id/eprint/36742019-12-10T15:47:06ZOn The Capacitated Scheduling Problem with Conflict JobsThe paper is concerned with scheduling jobs on parallel identical machines under the restrictions imposed by a conflict graph. The nodes of this conflict graph represent jobs and each edge indicates that the jobs associated with the nodes, incident to this edge, can not be processed concurrently. The jobs have a common due date and each job has the associated weight. The goal is to maximise the total weight of jobs which completion times do not exceed the due date. The considered scheduling model was motivated by the problem arising in the telecommunication industry. The paper identifies polynomially solvable and NP-hard particular cases and presents two mixed integer linear programming formulations together with their comparison by means of computational experiments.Minh Hoang Haminhhoang.ha@vnu.edu.vnDuy Manh VuYakov ZinderTrung Thanh Nguyen2019-12-09T03:34:11Z2019-12-09T03:34:11Zhttp://eprints.uet.vnu.edu.vn/eprints/id/eprint/3741This item is in the repository with the URL: http://eprints.uet.vnu.edu.vn/eprints/id/eprint/37412019-12-09T03:34:11ZImproved Particle Swarm Optimization of Three-Dimensional Path Planning for Fixed Wing Unmanned Aerial VehiclePath planning for Unmanned Aerial Vehicle (UAV) targets at generating an optimal global path to the target, avoiding collisions and optimizing the given cost function under constraints. In this paper, the path planning problem for UAV in pre-known 3D environment is presented. Particle Swarm Optimization (PSO) was proved the efficiency for various problems. PSO has high convergence speed yet with its major drawback of premature convergence when solving large-scale optimization problems. In this paper, the improved PSO with adaptive mutation to overcome its drawback in order to applied PSO the UAV path planning in real 3D environment which composed of mountains and constraints. The effectiveness of the proposed PSO algorithm is compared to Genetic Algorithm, standard PSO and other improved PSO using 3D map of Daklak, Dakrong and Langco Beach. The results have shown the potential for applying proposed algorithm in optimizing the 3D UAV path planning.Thi Huong Giang Dangdthgiang@uneti.edu.vnQuang Huy Vuonghuyvq1997@gmail.comMinh Hoang Haminhhoang.ha@vnu.edu.vnMinh Trien Phamtrienpm@vnu.edu.vn2019-11-29T03:37:53Z2019-11-29T03:37:53Zhttp://eprints.uet.vnu.edu.vn/eprints/id/eprint/3671This item is in the repository with the URL: http://eprints.uet.vnu.edu.vn/eprints/id/eprint/36712019-11-29T03:37:53ZA hybrid genetic algorithm for the traveling salesman problem with droneThis paper addresses the traveling salesman problem with drone (TSP-D), in which a truck and drone are used to deliver parcels to customers. The objective of this problem is to either minimize the total operational cost (min-cost TSP-D) or minimize the completion time for the truck and drone (min-time TSP-D). This problem has gained a lot of attention in the last few years reflecting the recent trends in a new delivery method among logistics companies. To solve the TSP-D, we propose a hybrid genetic search with dynamic population management and adaptive diversity control based on a split algorithm, problem-tailored crossover and local search operators, a new restore method to advance the convergence and an adaptive penalization mechanism to dynamically balance the search between feasible/infeasible solutions. The computational results show that the proposed algorithm outperforms two existing methods in terms of solution quality and improves many best known solutions found in the literature. Moreover, various analyses on the impacts of crossover choice and heuristic components have been conducted to investigate their sensitivity to the performance of our method.Quang Minh HaYves DevilleQuang Dung PhamMinh Hoang Haminhhoang.ha@vnu.edu.vn2019-11-29T03:37:33Z2019-11-29T05:53:49Zhttp://eprints.uet.vnu.edu.vn/eprints/id/eprint/3673This item is in the repository with the URL: http://eprints.uet.vnu.edu.vn/eprints/id/eprint/36732019-11-29T03:37:33ZAn Efficient Algorithm for the k-Dominating Set Problem on Very Large-Scale NetworksThe minimum dominating set problem (MDSP) aims to construct the minimum-size subset D⊂V of a graph G=(V,E) such that every vertex has at least one neighbor in D. The problem is proved to be NP-hard [5]. In a recent industrial application, we encountered a more general variant of MDSP that extends the neighborhood relationship as follows: a vertex is a k-neighbor of another if there exists a linking path through no more than k edges between them. This problem is called the minimum k-dominating set problem (MkDSP) and the dominating set is denoted as D_k. The MkDSP can be used to model applications in social networks [2] and design of wireless sensor networks [3]. In our case, a telecommunication company uses the problem model to supervise a large social network up to 17 millions nodes via a dominating subset in which k is set to 3.Minh Hai NguyenMinh Hoang Haminhhoang.ha@vnu.edu.vnThai Hoang DinhNguyen DiepEryk DutkiewiczThe Trung Tran2019-06-25T15:42:55Z2019-06-25T15:42:55Zhttp://eprints.uet.vnu.edu.vn/eprints/id/eprint/3509This item is in the repository with the URL: http://eprints.uet.vnu.edu.vn/eprints/id/eprint/35092019-06-25T15:42:55ZOn three soft rectangle packing problems with guillotine constraintsWe investigate how to partition a rectangular region of length L1 and height L2 into n rectangles of given areas (a1,…,an) using two-stage guillotine cuts, so as to minimize either (i) the sum of the perimeters, (ii) the largest perimeter, or (iii) the maximum aspect ratio of the rectangles. These problems play an important role in the ongoing Vietnamese land-allocation reform, as well as in the optimization of matrix multiplication algorithms. We show that the first problem can be solved to optimality in O(nlogn) , while the two others are NP-hard. We propose mixed integer linear programming formulations and a binary search-based approach for solving the NP-hard problems. Experimental analyses are conducted to compare the solution approaches in terms of computational efficiency and solution quality, for different objectives.Quoc Trung BuiThibaut VidalMinh Hoang Haminhhoang.ha@vnu.edu.vn2017-12-11T17:19:12Z2017-12-12T07:54:51Zhttp://eprints.uet.vnu.edu.vn/eprints/id/eprint/2761This item is in the repository with the URL: http://eprints.uet.vnu.edu.vn/eprints/id/eprint/27612017-12-11T17:19:12ZSolving the staff rescheduling problem in Lai Chau hydropower stationThis article studies the complex staff rescheduling problem arising in the context of Lai Chau hydropower station. Currently, rescheduling task is implemented manually by agreement of switching shifts among workers or by a scheduler. It is a complex and time-consuming operation but obtained schedules have been far below the expectation of the staff as they in general violate working rules and contract agreements. In this research, we propose an approach based on Mixed Integer Programming to support the scheduler solving the problem. Our model includes multiple objectives which minimize the number of changed shifts and the number of affected employees. Experimental results show the effectiveness of our method.Thuy DoHoang Giang PhamXuan Khoi TranMinh Hoang Haminhhoang.ha@vnu.edu.vnBach Do2017-12-11T09:38:43Z2019-02-18T04:14:15Zhttp://eprints.uet.vnu.edu.vn/eprints/id/eprint/2748This item is in the repository with the URL: http://eprints.uet.vnu.edu.vn/eprints/id/eprint/27482017-12-11T09:38:43ZOn the min-cost traveling salesman problem with droneOver the past few years, unmanned aerial vehicles (UAV), also known as drones, have been adopted as part of a new logistic method in the commercial sector called "last-mile delivery". In this novel approach, they are deployed
alongside trucks to deliver goods to customers to improve the quality of service and reduce the transportation cost. This approach gives rise to a new variant of the traveling salesman problem (TSP), called TSP with drone (TSP-D). A variant of this problem that aims to minimize the time at which truck and drone finish the service (or, in other words, to maximize the quality of service) was studied in the work of Murray and Chu (2015). In contrast, this paper considers a new variant of TSP-D in which the objective is to minimize operational costs including total transportation cost and one created by
waste time a vehicle has to wait for the other. The problem is first formulated mathematically. Then, two algorithms are proposed for the solution. The first
algorithm (TSP-LS) was adapted from the approach proposed by Murray and Chu (2015), in which an optimal TSP solution is converted to a feasible TSP-D solution by local searches. The second algorithm, a Greedy Randomized Adaptive Search Procedure (GRASP), is based on a new split procedure that optimally splits any TSP tour into a TSP-D solution. After a TSP-D solution has been generated, it is then improved through local search operators. Numerical results obtained on various instances of both objective functions with different sizes and characteristics are presented. The results show that GRASP outperforms TSP-LS in terms of solution quality under an acceptable running time.Quang Minh HaYves DevilleQuang Dung PhamMinh Hoang Haminhhoang.ha@vnu.edu.vn2017-10-16T08:14:57Z2017-10-16T08:14:57Zhttp://eprints.uet.vnu.edu.vn/eprints/id/eprint/2574This item is in the repository with the URL: http://eprints.uet.vnu.edu.vn/eprints/id/eprint/25742017-10-16T08:14:57ZThe vehicle routing problem with service level constraintsWe consider a vehicle routing problem which seeks to minimize cost subject to service level constraints on several groups of deliveries. This problem captures some essential challenges faced by a logistics provider which operates transportation services for a limited number of partners and should respect contractual obligations on service levels. The problem also generalizes several important classes of vehicle routing problems with profits. To solve it, we propose a compact mathematical formulation, a branch-and-price algorithm, and a hybrid genetic algorithm with population management, which relies on problem-tailored solution representation, crossover and local search operators, as well as an adaptive penalization mechanism establishing a good balance between service levels and costs. Our computational experiments show that the proposed heuristic returns very high-quality solutions for this difficult problem, matches all optimal solutions found for small and medium-scale benchmark instances, and improves upon existing algorithms for two important special cases: the vehicle routing problem with private fleet and common carrier, and the capacitated profitable tour problem. The branch-and-price algorithm also produces new optimal solutions for all three problems.Teobaldo BulhõesMinh Hoang Haminhhoang.ha@vnu.edu.vnRafael MartinelliThibaut Vidal2017-10-16T08:13:57Z2017-10-16T08:13:57Zhttp://eprints.uet.vnu.edu.vn/eprints/id/eprint/2573This item is in the repository with the URL: http://eprints.uet.vnu.edu.vn/eprints/id/eprint/25732017-10-16T08:13:57ZSolving the multi-vehicle multi-covering tour problemThe well-known multi-vehicle covering tour problem (m-CTP) involves finding a minimum-length set of vehicle routes passing through a subset of vertices, subject to constraints on the length of each route and the number of vertices that it contains, such that each vertex not included in any route is covered. Here, a vertex is considered as covered if it lies within a given distance of at least a vertex of a route. This article introduces a generalized variant of the m-CTP that we called the multi-vehicle multi-covering Tour Problem (mm-CTP). In the mm-CTP, a vertex must be covered at least not only once but several times. Three variants of the problem are considered. The binary mm-CTP where a vertex is visited at most once, the mm-CTP without overnight where revisiting a vertex is allowed only after passing through another vertex and the mm-CTP with overnight where revisiting a vertex is permitted without any restrictions. We first propose graph transformations to convert the last two variants into the binary one and focus mostly on solving this variant. A special case of the problem is then formulated as an integer linear program and a branch-and-cut algorithm is developed. We also develop a Genetic Algorithm (GA) that provides high-quality solutions for the problem. Extensive computational results on the new problem mm-CTP as well as its other special cases show the performance of our methods. In particular, our GA outperforms the current best metaheuristics proposed for a wide class of CTP problems.Tuan Anh PhamMinh Hoang Haminhhoang.ha@vnu.edu.vnXuan Hoai Nguyen