检索结果-内蒙古大学图书馆

Z-TRAPEZOIDAL RISK ASSESSMENT FOR MULTI-OBJECTIVE HAZMAT routing MODEL WITH time windows

RAIRO-OPERATIONS RESEARCH 2022年第6期56卷 4229-4250页

作者： Zandieh, Fatemeh Ghannadpour, Seyed Farid Iran Univ Sci & Technol Dept Ind Engn Tehran *** Iran

Hazardous material (Hazmat) transportation is an inseparable section of the industry, despite its major financial and health risks. In order to optimize Hazmat transportation, a multi-objective Hazmat routing model with time windows is employed where the risk and distance are minimized. Due to the uncertainty of Hazmat transportation risk, a Z-number fuzzy approach is used to estimate the risk, in which the probability of occurrence and the severity is considered in the context of Z-information. The severity of the event includes the affected population and depends on the amount of transported Hazmat and the number of individuals affected by the explosion. To tackle the proposed model, the present paper utilizes a multi-objective hybrid genetic algorithm, the validity of which is tested by Solomon's problems. Furthermore, the optimization of a case study concerning the Hazmat distribution in Iran is analyzed using the suggested approach to assess the efficiency of the proposed fuzzy problem in real-world applications.

关键词： vehicle routing problem with time windows hazardous material risk Z-number

来源：评论

学校读者我要写书评

暂无评论

A new warmstarting strategy for the primal-dual column generation method

引用

MATHEMATICAL PROGRAMMING 2015年第1-2期152卷 113-146页

作者： Gondzio, Jacek Gonzalez-Brevis, Pablo Univ Edinburgh Maxwell Inst Sch Math Edinburgh EH9 3JZ Midlothian Scotland Univ Desarrollo Sch Engn Concepcion Chile

This paper presents a new warmstarting technique in the context of a primal-dual column generation method applied to solve a particular class of combinatorial optimization problems. The technique relies on calculating an initial point and on solving auxiliary linear optimization problems to determine the step direction needed to fully restore primal and dual feasibilities after new columns arrive. Conditions on the maximum size of the cuts and on a suitable initial point are discussed. Additionally, the strategy ensures that the duality gap of the warmstart is bounded by the old duality gap multiplied with a (small) constant, which depends on the relation between the old and modified problems. Computational experiments demonstrate the gains achieved when compared to a coldstart approach.

关键词： Interior point methods Warmstarting Column generation Linear programming Cutting stock problem vehicle routing problem with time windows

来源：评论

学校读者我要写书评

暂无评论

A genetic algorithm for the simultaneous delivery and pickup problems with time window

引用

COMPUTERS & INDUSTRIAL ENGINEERING 2012年第1期62卷 84-95页

作者： Wang, Hsiao-Fan Chen, Ying-Yen Natl Tsing Hua Univ Dept Ind Engn & Engn Management Hsinchu 30013 Taiwan

This paper concerns a Simultaneous Delivery and Pickup problem with time windows (SDPPTW). A mixed binary integer programming model was developed for the problem and was validated. Due to its NP nature, a co-evolution genetic algorithm with variants of the cheapest insertion method was proposed to speed up the solution procedure. Since there were no existing benchmarks, this study generated some test problems which revised from the well-known Solomon's benchmark for vehicle routing problem with time windows (VRPTW). From the comparison with the results of Cplex software and the basic genetic algorithm, the proposed algorithm showed that it can provide better solutions within a comparatively shorter period of time. (C) 2011 Elsevier Ltd. All rights reserved.

关键词： Bi-directional logistics Simultaneous delivery and pickup vehicle routing problem with time windows Co-evolution genetic algorithm

来源：评论

学校读者我要写书评

暂无评论

vehicle route planning in e-waste mobile collection on demand supported by artificial intelligence algorithms

引用

TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT 2018年 63卷 1-22页

作者： Nowakowski, Piotr Szwarc, Krzysztof Boryczka, Urszula Silesian Tech Univ Fac Transport Ul Krasinskiego 8 PL-40019 Katowice Poland Univ Silesia Univ Silesia Katowice Inst Comp Sci Ul Bedzinska 39 PL-41205 Sosnowiec Poland

Mobile collection of e-waste on demand is one of the methods that can contribute to an increase in the collection rate of waste. In this method, a person requests the waste pick up from a household at a preferred time. To support such a collection method an efficient algorithm and information system for convenient waste disposal for residents has to be applied. Our study investigates using artificial intelligence algorithms for solving the vehicle routing problem with time windows for a heterogeneous fleet of waste collection vehicles. We present an algorithm and a productive model of the online system enabling comprehensive communication for people that request waste equipment for collection, registering of data and solving the VRPTW. The system includes parametric models of four algorithms (simulated annealing, tabu search, greedy, bee colony optimization). The result of the optimization is the assignment of a minimal number of collection vehicles, a vehicle routing plan, timely collection of waste from a household and collection cost reduction. The study includes the simulation of e-waste collection requests in Tokyo, Philadelphia and Warsaw to compare algorithms for various urban arrangements of streets and buildings. The results show that the best of the four algorithms, to facilitate e-waste mobile collection on demand, is simulated annealing and the worst is tabu search. The proposed model and algorithm can bring significant improvement in planning the routes of the vehicles in the e-waste collection, including a positive social impact on the new method of waste collection, especially in urban areas.

关键词： Transportation of waste Mobile collection of e-waste Optimization methods Artificial intelligence vehicle routing problem with time windows IT system supporting transportation planning

来源：评论

学校读者我要写书评

暂无评论

A two-stage scheduling method for hot rolling and its application

引用

CONTROL ENGINEERING PRACTICE 2009年第6期17卷 629-641页

作者： Zhao, Jun Wang, Wei Liu, Quanli Wang, Zhigang Shi, Peng Dalian Univ Technol Res Ctr Informat & Control Dalian 116024 Peoples R China Univ Glamorgan Dept Comp & Math Sci Pontypridd CF37 1DL M Glam Wales

Hot rolling scheduling is a difficult problem in the steel processing industry. It involves many objectives and constraints in both technical and practical respects. A two-stage scheduling method is proposed in this paper. Batch planning of staple material is formulated as a VRPTW, which is solved with a modified PGA. Then, batches of the established units are optimized by adjusting rolling sequences using intelligent search algorithms to reach higher hot charge ratios. This method has been applied to a hot strip mill belonging to Baosteel in China. Our results demonstrate that the proposed technique can improve production efficiency and offer significant economic benefits. (C) 2008 Elsevier Ltd. All rights reserved.

关键词： Hot rolling production scheduling vehicle routing problem with time windows Heuristics Intelligent search algorithms

来源：评论

学校读者我要写书评

暂无评论

Lot sizing versus batching in the production and distribution planning of perishable goods

引用

INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS 2013年第1期146卷 208-218页

作者： Amorim, P. Belo-Filho, M. A. F. Toledo, F. M. B. Almeder, C. Almada-Lobo, B. Univ Porto Fac Engn INEC TEC P-4600001 Oporto Portugal Univ Sao Paulo Inst Ciencias Matemat & Comp BR-13560970 Sao Carlos SP Brazil Europa Univ Viadrina Frankfurt Oder Dept Supply Chain Management D-15230 Frankfurt Oder Germany

Joint production and distribution planning at the operational level has received a great deal of attention from researchers. In most industries these processes are decoupled by means of final goods inventory that allow for a separated planning of these tasks. However, for example, in the catering industry, an integrated planning framework tends to be more favorable due to the perishable nature of the products that forces a make-to-order production strategy. So far this planning problem has only been addressed by allowing the batching of orders. The main contribution of this paper is to extend this approach and prove the importance of lot sizing for make-to-order systems when perishability is explicitly considered. The value of considering lot sizing versus batching is further investigated per type of production scenario. Overall, results indicate that lot sizing is able to deliver better solutions than batching. On average, for the improved instances, the cost savings ascend to 6.5% when using lot sizing. The added flexibility of lot sizing allows for a reduction on production setup costs and both fixed and variable distribution costs. The savings derived from lot sizing are enhanced by customer oriented time windows and production systems with non-triangular setups. (C) 2013 Elsevier B.V. All rights reserved.

关键词： Integrated planning Lot sizing and scheduling Batching vehicle routing problem with time windows Perishability

来源：评论

学校读者我要写书评

暂无评论

An Adaptive Large Neighborhood Search for an E-grocery Delivery routing problem

引用

COMPUTERS & OPERATIONS RESEARCH 2016年 69卷 109-125页

作者： Emec, Ugur Catay, Bulent Bozkaya, Burcin Sabanci Univ Fac Engn & Nat Sci TR-34956 Istanbul Turkey Sabanci Univ Sch Management TR-34956 Istanbul Turkey

Online shopping has become ever more indispensable to many people with busy schedules who have a growing need for services ranging for a wide variety of goods, which include standard (or "staple") goods as well as "premium" goods, i.e. goods such as organic food, specialty gifts, etc. that offer higher value to consumers and higher profit margins to retailers. In this paper, we introduce a new mathematical programming formulation and present an efficient solution approach for planning the delivery services of online groceries to fulfill this diverse consumer demand without incurring additional inventory costs. We refer to our proposed model as the E-grocery Delivery routing problem (EDRP) as it generically represents a family of problems that an online grocery is likely to face. The EDRP is based on a distribution network where premium goods are acquired from a set of external vendors at multiple locations in the supply network and delivered to customers in a single visit. To solve this problem, we develop an improved Adaptive Large Neighborhood Search (ALNS) heuristic by introducing new removal, insertion, and vendor selection/allocation mechanisms. We validate the performance of the proposed ALNS heuristic through an extensive computational study using both the well-known vehicle routing problem with time windows instances of Solomon and a set of new benchmark instances generated for the EDRP. The results suggest that the proposed solution methodology is effective in obtaining high quality solutions fast. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： E-grocery Delivery routing problem Home Delivery Services vehicle routing problem with time windows Premium Good Premium Customer Adaptive Large Neighborhood Search

来源：评论

学校读者我要写书评

暂无评论

Dynamic parameterization of the particle swarm optimization and genetic algorithm hybrids for vehicle routing problem with time window

引用

International Journal of Hybrid Intelligent Systems 2015年第1期12卷 13-25页

作者： Masrom, S. Abidin, Siti Z.Z. Omar, N. Nasir, K. Abd Rahman, A.S. Faculty of Computer and Mathematical Sciences Universiti Teknologi MARA Perak Malaysia Faculty of Computer and Mathematical Sciences Universiti Teknologi MARA Shah Alam Malaysia Faculty of Science and Information Technology Universiti Teknologi PETRONAS Perak Malaysia

Particle Swarm Optimization (PSO) is a well known technique for solving various kinds of combinatorial optimization problems including scheduling, resource allocation and vehicle routing. However, basic PSO suffers from premature convergence problem. Many techniques have been proposed for alleviating this problem. One of the alternative approaches is hybridization. Genetic Algorithms (GAs) are one of the possible techniques used for hybridization. Most often, a mutation scheme is added to the PSO, but some applications of crossover have been added more recently. Some of these schemes use dynamic parameterization when applying the GA operators. In this work, dynamic parameterized mutation and crossover operators are combined with a PSO implementation individually and in combination to test the effectiveness of these additions. The results indicate that all the PSO hybrids with dynamic probability have shown satisfactory performance in finding the best distance of the vehicle routing problem with time windows.

关键词： Hybridization particle swarm optimization genetic algorithm dynamic parameterization vehicle routing problem with time windows

来源：评论

学校读者我要写书评

暂无评论

Home health care routing and scheduling problem considering temporal dependencies and perishability with simultaneous pickup and delivery

引用

IFAC-PapersOnLine 2019年第13期52卷 118-123页

作者： Shahnejat-Bushehri, S. Tavakkoli-Moghaddam, R. Momen, S. Ghasemkhani, A. Tavakkoli-Moghaddam, H. School of Industrial Engineering College of Engineering University of Tehran Tehran Iran Arts et Métiers ParisTech LCFC Metz France School of Industrial and Systems Engineering Tarbiat Modares University Tehran Iran

Home health care (HHC) companies provide a wide range of medical and social services to patients in their own homes to help them rehabilitate after illness or injury. Providing high-quality services and reducing operating costs are accessible through proper planning of different sectors of HHC companies. This study presents a mathematical model integrated with real-life constraints to address a home health care routing and scheduling problem (HHCRSP). The planning takes into account temporal precedence and synchronization constraints and limited allowable times for transferring collected biological samples to the laboratory in the pickup and delivery environment. This problem is a new variant of the vehicle routing problem with time windows (VRPTW) with the aim of minimizing the cost related to the transportation and the idle time of caregivers by assigning proper caregivers with required qualifications to patients based on their disjunctive needs. Simulated annealing (SA) and tabu search (TS) are two meta-heuristics applied in two phases for each instance to schedule primary tasks in the first step, and then synchronized services in the next phase. The Solomon's benchmark is used for generating comparative experiments. © 2019, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Home health care Heuristic algorithms Operating costs Patient rehabilitation Pickups Scheduling Service industry Simulated annealing Synchronization Tabu search vehicle routing Comparative experiments Meta heuristic algorithm Perishability routing and scheduling Simultaneous pickup and deliveries Synchronization constraints Temporal dependencies vehicle routing problem with time windows

来源：评论

学校读者我要写书评

暂无评论

A Hybrid Particle Swarm Optimization Algorithm for Multi-Objective Pickup and Delivery problem with time windows

引用

JOURNAL OF COMPUTERS 2013年第10期8卷 2583-2589页

作者： Zou, Shuilong Li, Jin Li, Xueqian Nanchang Inst Sci & Technol Nanchang Jiangxi Peoples R China Zhejiang Gongshang Univ Sch Comp Sci & Informat Engn Hangzhou Zhejiang Peoples R China Zhejiang Gongshang Univ Contemporary Business & Trade Res Ctr Hangzhou Zhejiang Peoples R China Univ Shanghai Sci & Technol Sch Business Shanghai Peoples R China

This paper studies the multi-objective pickup and delivery problem with time windows (PDPTW), in which a fleet of homogeneous vehicles with the same capacities located in a depot serve a collection of given transportation requests. Each request is composed of a pickup location, a delivery location and a given load. The PDPTW is to determine a vehicle scheduling strategy with the objectives of minimizing the number of vehicles utilized, the total travel distances and the total waiting times. A mixed integer programming model is built to formulate this multiobjective PDPTW. Then a novel hybrid particle swarm optimization (HPSO) is proposed to solve this problem. This algorithm adds particles neighbor information to diversify the particle swarm and use the variable neighborhood search (VNS) to enhance the convergence speed. Finally, some numerical experiments based on existing benchmark instances are given to show the effectiveness and feasibility of the algorithm.

关键词： vehicle routing problem with time windows pickup and delivery transportation particle swarm optimization algorithm

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：