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A bi-level programming problem of medicine procurement and production optimization

JOURNAL OF GLOBAL OPTIMIZATION 2025年 1-35页

作者： Fan, Wenjuan Zhang, Jingwei Shao, Kaining Lan, Shaowen Zhu, Shuwan Hefei Univ Technol Sch Management Hefei Peoples R China Minist Educ Key Lab Proc Optimizat & Intelligent Decis Making Hefei Peoples R China Chuzhou Univ Sci & Technol Dept Chuzhou Peoples R China Hangzhou Dianzi Univ Sch Management Hangzhou Peoples R China Fuzhou Univ Sch Econ & Management Fuzhou Peoples R China

The emerging medical alliance in some countries enables the joint optimization for its members through timely necessary information exchanging and sharing. This paper investigates a joint decision-making optimization problem between a focal hospital and multiple pharmaceutical manufacturers in a medical alliance, to optimize both parties' objectives from the supply chain management perspective. Specifically, the hospital makes the decision on the medicine procurement from multiple candidate pharmaceutical manufacturers to minimize its total procurement cost, and each chosen pharmaceutical manufacturer determines the production plan for the different types of medicine procured by the hospital to maximize its total profit. Given that the hospital and pharmaceutical manufacturers make decisions under their objective functions and constraints while the decisions affect each other's objective mutually, a bi-level programming mathematical model is established, with the hospital acting as the leader and the pharmaceutical manufacturers as multiple independent followers. We propose an improved hierarchical loop framework, including the upper solving, the lower solving, and the improvement module. Specifically, we embed the variable neighborhood search (VNS) algorithm in the lower-solving module and apply a set of heuristic rules in the improvement module. To test the performance of the proposed algorithm, we replace the VNS algorithm in the lower solving module with PSO, GA, and SA, and compare their performance in small, medium, and large-scale instances. Besides, we also validate the effectiveness of the improvement module by comparing the performance of the algorithm with and without the module. The computational experiments prove the effectiveness and efficiency of the proposed approach.

关键词： Bi-level programming Procurement Production planning variable neighborhood search algorithm

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Routing Design and Departure Time Determination of Customized Buses Based on Reserved Trip Request 7

Routing Design and Departure Time Determination of Customize...

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IEEE 7th International Conference on Intelligent Transportation Engineering (ICITE)

作者： Cheng, Zhuxuan Xiong, Jie Li, Tongfei Chen, Yanyan Minist Transport Key Lab Technol Intelligent Transportat Syst Beijing Peoples R China Beijing Univ Technol Beijing Key Lab Traff Engn Beijing 100124 Peoples R China

ISBN: (纸本)9781665460071

This paper investigates an integrated optimization problem of routing design and departure time determination of customized buses based on demand-responsive service. The problem aims to optimize both a set of customized routes and the departure time of each route based on a set of reserved trip requests. A mixed integer programming model is formulated to address the problem. The model aims to minimize the sum of the operator cost of the bus company and the total travel cost of passengers so that the buses can be efficiently used to provide high-quality services to passengers. To solve the model, a departure time determination method based on a time window backpropagation process is first proposed to optimize the bus departure time for a given route. Then a variable neighborhood search (VNS) algorithm with customized operators is designed to generate the optimized routes. Finally, different numerical tests are conducted to verify the effectiveness of the proposed model and the algorithm, then the sensitivity analysis on key parameters follows.

关键词： customized bus routing design departure time determination variable neighborhood search algorithm

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Train timetabling with dynamic and random passenger demand: A stochastic optimization method

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TRANSPORTATION REsearch PART C-EMERGING TECHNOLOGIES 2021年 123卷

作者： Gong, Congcong Shi, Jungang Wang, Yanhui Zhou, Housheng Yang, Lixing Chen, Dewang Pan, Hanchuan Beijing Jiaotong Univ State Key Lab Rail Traff Control & Safety Beijing 100044 Peoples R China East China Jiaotong Univ Coll Transportat & Logist Nanchang 330013 Jiangxi Peoples R China Fuzhou Univ Coll Math & Comp Sci Fuzhou 350116 Peoples R China Shanghai Univ Engn Sci Sch Urban Rail Transportat Shanghai 201620 Peoples R China

Considering the dynamics and randomness of passenger demand, this paper investigates a train timetabling problem in the stochastic environment for an urban rail transit system. With the scenario-based representation of passenger distribution, an integer nonlinear programming (INLP) model is first formulated to simultaneously optimize the total number of train services, headway settings and speed profile selection decision during the planning time horizon, in which the expected total service cost is treated as the objective function. Through an analysis of the features of the nonlinear constraints, a reformulation method is proposed to develop an equivalent integer linear programming (ILP) model that can be easily solved by commercial software. Moreover, a variable neighborhood search algorithm is developed to find the approximate optimal solutions for large-scale problems within the tolerable computing time. Finally, two sets of numerical experiments, with the operation environments of a simple urban rail transit line and Fuzhou Metro Line 1, are implemented to verify the solution quality and effectiveness of the proposed methods.

关键词： Urban rail transit Train timetable Stochastic optimization variable neighborhood search algorithm

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Optimization of energy-efficiency train schedule considering passenger demand and rolling stock circulation plan of subway line

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ENERGY 2023年第1期275卷

作者： Huang, Yu Zhou, Wenliang Qin, Jin Deng, Lianbo Cent South Univ Sch Traff & Transportat Engn Changsha 410000 Hunan Peoples R China

An energy-efficiency train schedule greatly contributes to alleviating some environmental issues such as carbon emissions. However, the pursuit of reducing train energy consumption often leads to passengers' longer travel time, and more operation cost of rolling stocks. Thus, it is necessary to consider costs of passengers and rolling stocks when optimizing the energy-efficiency schedule for better satisfying passenger demand and reducing trains' total operating cost. In this paper, a mixed integer nonlinear programming model of energy-efficiency train schedule considering passenger demand and rolling stock circulation plan is established for minimizing passengers' travel cost and trains' operating cost. More specifically, this model devotes to simultaneously optimizing: (1) passengers' travel choices to reduce passengers' waiting time and travel time, (2) the selection of train traction strategy in the section to reduce the traction energy consumption, and (3) the train connection scheme to ensure the economy of the rolling stock circulation plan. This paper designs a variable neighborhood search algorithm combined with CPLEX solver to solve the model efficiently. Based on the data of Guangzhou Metro Line 9, the optimization method proposed in this paper can reduce the train operation cost by 9.73% and the total passenger travel cost by 18.11%.

关键词： Subway line Energy-efficient train scheduling Passenger demand Rolling stock circulation planning variable neighborhood search algorithm

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A decision model on human-robot collaborative routing for automatic logistics

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ADVANCED ENGINEERING INFORMATICS 2022年 53卷

作者： Zhu, Shengyan Wang, Huiwen Zhang, Xiaoqin He, Xueting Tan, Zheyi Yibin Univ Sanjiang Res Inst Artificial Intelligence & Robot Yibin Sichuan Peoples R China Shanghai Univ Sch Management Shanghai Peoples R China

This paper studies an integrated human-robot routing problem arising in collaborative order picking systems. Travelling routes of pickers and robots interact with each other and simultaneously determine the start time of tasks. A mixed-integer programming model is proposed which aims to minimize the total task completion time by optimizing both pickers' and robots' routes. Moreover, a variable neighborhood search and dynamic programming -based heuristic algorithm is developed for solving the problem in large-scale environments. Numerical experiments are conducted to prove the necessity of the proposed model and also validate the efficiency of the proposed heuristic algorithm. The results indicate the methodology can yields solutions with smaller optimality gap within a reasonable period of time, in comparison with an intuitive but common decision rule. A sensitivity analysis is also conducted to derive a number of managerial implications regarding the configuration of pickers and robots and robots' speed setting.

关键词： Order picking system Human -robot collaborative environment Autonomous mobile robots Vehicle routing problem variable neighborhood search algorithm Dynamic programming

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RETRACTED: A Hybrid Intelligent Optimization algorithm for Solving the Producing Work Order Group Furnace Problem (Retracted Article)

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ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING 2023年第2期48卷 2579-2579页

作者： Liu, Yefeng Li, Shaowu Pang, Xinfu Zhao, Yuan Yu, Shengping Shenyang Inst Technol Liaoning Key Lab Informat Phys Fusion & Intellige Fushun 113122 Liaoning Peoples R China Hubei Univ Nationalities Sch Informat Engn Enshi Peoples R China Shenyang Inst Engn Sch Automat Shenyang 110136 Peoples R China Northeastern Univ State Key Lab Synthet Automat Proc Ind Shenyang 110819 Liaoning Peoples R China

A hybrid optimization method for the production of work order group furnaces was proposed in this paper. First, a working order group furnace model was constructed including performance index, the constraint condition and the decision variable to fit the problems in working order group furnaces. The hybrid optimization method consists of an optimal priority and a variable neighborhood search algorithm. In the algorithm, we have adopted a lot of rules and corresponding grade limits on stock production. Based on the proposed algorithm's calculation results, the delivery time deviation, grade deviation and priority deviation of the 20 group furnace production orders are reduced from 58 to 42 with reduction rate of 27.59%. The satisfaction rate for grade preparation is increased from 4 to 6, which has a rate of increase of 50%. In order to prove the effectiveness of the proposed algorithm, the proposed algorithm is compared with other literature algorithms such as a discrete particle swarm algorithm, a variable neighborhood search algorithm and an adaptive variable neighborhood search algorithm.

关键词： Furnace group problem Hybrid optimization method Best priority Manufacturing Model variable neighborhood search algorithm Discrete particle swarm algorithm Adaptive variable neighborhood search algorithm

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Ring hierarchical hub network design problem: Exact and heuristic solution methods

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EURO JOURNAL ON TRANSPORTATION AND LOGISTICS 2022年 11卷

作者： Eydi, Alireza Khaleghi, Amir Barzegar, Khaled Univ Kurdistan Dept Ind Engn Sanandaj Iran Univ Kurdistan Ind Engn Sanandaj Iran Univ Kurdistan Ind Engn Sanandaj Iran

In this paper, we study the hierarchical hub network design problem with a ring-star-star structure. In this problem, the hubs are located in two layers. In the first layer, central hubs (main hubs) are located in a ring structure, and in the second layer, secondary hubs are located. Each secondary hub is allocated to a central hub. Other demand points can also be allocated to each of these hubs (central hubs or secondary hubs). The objective is to minimize transportation costs on the network. This problem applies to communication networks when establishing direct links between demand nodes is not cost-effective, and there are two levels of service for customers. Also, the ring structure is used to reduce costs associated with full communication between central hubs. We present a mixed-integer programming model for the problem and report the results of the problem solving for a numerical example on the CAB dataset. Also, we present three solution methods for the problem. First, by exploiting the decomposable structure of the proposed model, we introduce an accelerated Benders decomposition algorithm. Then, we present a hybrid genetic algorithm that uses the Dijkstra algorithm to evaluate solutions. Next, we present a hybrid variable neighborhood search algorithm that uses the Dijkstra algorithm to calculate the cost of each solution. Also, a relax-and-fix algorithm is proposed to find near-optimal feasible solutions for the problem. Computational results are presented on the USA423 dataset. The results show that the proposed relax-and-fix algorithm can solve instances with up to 100 nodes. Also, the proposed hybrid algorithms can solve instances with up to 423 nodes. The performance of the proposed hybrid variable neigh-borhood search is better than the proposed hybrid genetic algorithm in solving large-sized instances.

关键词： Transportation Ring hierarchical hub network Ring network Benders decomposition Genetic algorithm variable neighborhood search algorithm Relax-and-fix algorithm

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Green logistics oriented tug scheduling for inland waterway logistics

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ADVANCED ENGINEERING INFORMATICS 2021年 49卷

作者： Zhu, Shengyan Gao, Jiajing He, Xueting Zhang, Shuanglu Jin, Ying Tan, Zheyi Yibin Univ Sanjiang Res Inst Artificial Intelligence & Robot Chengdu Sichuan Peoples R China Shanghai Univ Sch Management Shang Da Rd 99 Shanghai 200444 Peoples R China

Under the global consensus on reducing emissions, shipping companies are undertaking the social responsibility of greenhouse gas emission reduction. Meanwhile, it is a top priority for shipping companies to arrange the tugs and barges reasonably and achieve the goal of energy saving as well as emission reduction. Based on the above problem, this paper proposes a Mixed Integer Programming (MIP) model to jointly optimize the transport routes of tugs considering the barge transshipment, with the objective of minimizing the sum of the carbon emissions for barges handling, tugs travelling and waiting. In the view of specific problem, a variable neighborhood search (VNS) algorithm is designed to solve this MIP model effectively. Numerical experiments based on different sizes of instances are implemented to validate the effectiveness of the proposed algorithm. Computational results indicate that the proposed model reduces carbon emissions by about 46.93% compared to the dispatching rule. Moreover, the consideration of barge transshipment in the model can reduce carbon emissions by about 10.46%. In addition, the VNS algorithm yields solutions with optimality gaps about 0.29% in a short time.

关键词： Inland waterway logistics Sustainable logistics Transshipment of barges Mixed Integer Programming variable neighborhood search algorithm

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Research on the station location problem for public bicycle systems under dynamic demand

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COMPUTERS & INDUSTRIAL ENGINEERING 2019年 127卷 971-980页

作者： Cao, Jin Xin Xue, Cong Cong Jian, Mei Ying Yao, Xue Ru Inner Mongolia Univ Inst Traff Engn Hohhot Peoples R China Inner Mongolia Engn Res Ctr Urban Transportat Dat Hohhot Peoples R China Inner Mongolia Univ Sch Math Sci Hohhot Peoples R China

This paper proposes a station location problem for public bicycle systems under a zoning scheme with consideration for multi-period demand. The objective of the problem is to minimize the fixed construction costs and variable operational costs of the public bicycle stations. A mixed integer programming model is formulated for the problem. Owing to the computational intractability of the problem under study, a genetic algorithm and a variable neighborhood search algorithm are developed to solve the problem. Comprehensive computational experiments are conducted to illustrate the effectiveness and efficiency of the proposed approach.

关键词： Public bicycle system Facility location problem Mixed integer programming Genetic algorithm variable neighborhood search algorithm

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Composite multi-objective optimization on a new collaborative vehicle routing problem with shared carriers and depots

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JOURNAL OF CLEANER PRODUCTION 2020年 274卷

作者： Zhang, Wenyu Chen, Zixuan Zhang, Shuai Wang, Weirui Yang, Shuiqing Cai, Yishuai Zhejiang Univ Finance & Econ Sch Informat Management & Artificial Intelligence Hangzhou 310018 Peoples R China Zhejiang Univ Sch Mech Engn Hangzhou 310027 Peoples R China

The collaborative vehicle routing problem for logistic optimization is a fundamental part of the sustainable supply chain, and has increasingly been of concern in recent years. This study proposes a novel logistics collaboration model to address the collaborative vehicle routing problem that involves shared carriers and depots (CVRP-SCD). This is inspired by the fact that a depot often has orders for multiple carriers, and a carrier often delivers orders to multiple depots. This problem involves decreasing transportation distances and improving capacity utilization by extending supply-side unilateral logistics collaborations to simultaneously consider collaborations between supplyand demand-sides. Further, the proposed CVRP-SCD model uses a composite objective that is a weighted sum of four objectives including quality, reliability, cost, and time to accurately evaluate and analyze the efficiency improvement. An extended variable neighborhood search algorithm is presented based on three matrices, including the carrier collaboration matrix, depot collaboration matrix, and transportation sequence matrix. This algorithm aims to address the trade-offs among multiple objectives for the CVRPSCD model by incorporating new operators based on specific features involved in the problem. Simulation experiments are performed on two sets of instances to evaluate the proposed algorithm's effectiveness as well as the savings produced from the proposed model. Further, a comparison experiment between different objective optimization also verifies the rationality of the proposed composite multi objective optimization. (c) 2020 Elsevier Ltd. All rights reserved.

关键词： Vehicle routing problem Carrier collaboration Depot collaboration Composite multi-objective optimization variable neighborhood search algorithm

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