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Chinese Automation Congress (CAC)

作者： Zhou, Min Liu, Xuan Hou, Zhuopu Shang, Jingfan Yue, Yixiang Song, Haifeng Beijing Jiaotong Univ State Key Lab Rail Traff Control & Safety Beijing Peoples R China Beijing Jiaotong Univ Sch Traff & Transportat Beijing Peoples R China Beijing Jiaotong Univ Sch Elect & Informat Engn Beijing Peoples R China

ISBN: (纸本)9781728176871

The integrated optimization of train operation control and dynamic dispatching and the generation of integrated strategy is an important challenge to enhance the essence of emergency response capability of high-speed railway systems (HSRs) when dealing with emergencies. Considering that in actual high-speed railways, there are already preset optimized speed trajectories inside ATO. On this basis, this paper proposes a real-time train rescheduling approach that integrates preset speed trajectory selection and timetable optimization is to reduce the weighted sum of total delay time and energy consumption as much as possible, and the mixed-integer linear programming (MILP) model is established and solved in CPLEX. The simulation experiment at a train delay scenario is performed and the results show that the proposed method can reduce train delay and energy consumption compared with the integrated method without considering energy consumption and other non-integrated methods.

关键词： Integrated optimization Dynamic dispatching Speed trajectory mixed integer linear programming model

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Building a Decision Support System for Vehicle Routing Problem: A Real-Life Case Study from Turkey 19th

Building a Decision Support System for Vehicle Routing Probl...

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19th International Symposium for Production Research, ISPR 2019

作者： Doğan, Ayşenur Bilici, İrem Demiral, Osman Kaan Erdoğan, Mehmet Serdar Kabadurmuş, Özgür International Logistics Management Yasar University Izmir Turkey

ISBN: (纸本)9789811509490

One of the most costly operations in logistics is the distribution of goods. Inefficient vehicle routes increase distribution costs, especially for companies performing distribution operations daily. Vehicle Routing Problem (VRP) addresses this inefficiency and optimizes the distribution routes of vehicles. In this study, we developed a decision support system to solve the Vehicle Routing Problem with Time Windows and Split Delivery and applied it to a real-life case company. The data of the problem were obtained by a real logistic company, which is one of the leading Turkish logistics companies located in Izmir, Turkey. The company distributes goods to the customers located in various cities in Turkey and currently does not use any decision-making tool to optimize the routes of its trucks. We formulated the mathematical model as mixed integer linear programming (MILP) and solved it by using IBM OPL CPLEX. Our proposed decision support system clusters the customers into geographical groups and then optimizes the routes within the clusters. The results of the decision support system can be manually adjusted by the decision maker to fine-tune the routes. We demonstrated the efficiency of our proposed methodology on the regional distribution of the company. The results of the study showed that our proposed model decreases the total distribution distance by 16% and total distribution time by approximately 13%. © 2020, Springer Nature Switzerland AG.

关键词： Heterogeneous Fleet mixed integer linear programming model Optimization Time windows Vehicle Routing Problem

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Optimization of Costs in Empty Container Repositioning 19th

Optimization of Costs in Empty Container Repositioning

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19th International Symposium for Production Research, ISPR 2019

作者： Göçen, Mehmet Yasin Çağlar, Öykü Ercan, Elif Kizilay, Damla Department of Industrial Engineering Yasar University Bornova Turkey Department of Industrial Engineering Dokuz Eylul University İzmir Turkey

ISBN: (纸本)9789811509490

In this study, the empty container repositioning problem in a liner shipping company is considered. The research includes necessary information about the company and maritime transportation, highlighting the importance of empty container storage. As the worldwide containerized trade increases, the container traffic increases. Consequently, the surplus containers are repositioned to locations where they are required, which causes high costs. Therefore, in the existing system, the company deals with higher prices. In this study, the storage location of the empty containers, which are coming from the vessels to the ports, are determined according to the different cost policies of the warehouses. Thus, our problem is defined as an empty container repositioning problem. The primary objective of this study is to build an operations-research based decision-making system in order to minimize the total cost, regarding changing prices of warehouses and transportation cost of containers. In the decision-making process, this study will help the company to overcome the complexity about repositioning empty containers regarding the container size, storage day of the containers, changing inventory holding costs of the warehouses, and the transportation costs of the containers from port to the corresponding warehouses. Taking into consideration all these parts of the problem, this study will eventually help in reducing inventory holding and transportation costs of the empty container storage. As a solution methodology, the mixed integer linear programming model is proposed, and optimal solutions are obtained in a concise time. © 2020, Springer Nature Switzerland AG.

关键词： Cost reduction Decision support system Empty container repositioning mixed integer linear programming model Optimization

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Integrated approach for the bucking and production planning problems in forest industry

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COMPUTERS & CHEMICAL ENGINEERING 2019年 125卷 155-163页

作者： Vanzetti, Nicolas Broz, Diego Montagna, Jorge M. Corsano, Gabriela CONICET UTN INGAR Inst Desarrollo & Diseno Avellaneda 3657S3002GJC Santa Fe Argentina Univ Nacl Litoral Fac Ingn Quim Santiago Estero 2829 Santa Fe Argentina UNAM CONICET FCF Bertoni 124N3382GDD Eldorado Misiones Argentina

The appropriate integration among production activities is a key factor for the development of the forest industry in the northeast of Argentina. Sawmills are one of the main logs consumers. However, production planning of sawmills has been managed independently of the forest production. In this work, a mixed integer linear programming formulation is proposed in order to achieve an adequate logs supply that allows carrying out an efficient lumber production plan. Bucking decisions, as the number of stems to be harvested and the employed bucking patterns, are jointly solved with sawmill planning decisions, like the number and type of processed logs and the used cutting patterns, in order to fulfill the boards demands maximizing the net profit along the time horizon composed by several time periods (days). Through examples, the capabilities of the proposed approach are highlighted and the computational results are analyzed. (C) 2019 Elsevier Ltd. All rights reserved.

关键词： Bucking Log procurement policy Sawmill production planning mixed integer linear programming model

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Alternative solution algorithm for winner determination problem with quantity discount of transportation service procurement

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PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS 2019年 535卷 122286-122286页

作者： Yang, Fang Huang, Yao-Huei Li, Jun Southwest Jiaotong Univ Sch Econ & Management Chengdu 610031 Sichuan Peoples R China Fu Jen Catholic Univ Dept Informat Management New Taipei Taiwan

This study examines the winner determination problem (WDP) for the procurement of transportation service. The problem contains three important roles, namely, shippers, carriers, and third-party carriers. Shippers determine the service lanes that can be outsourced to carriers so that the transportation service cost may be reduced. The WDP can be formulated as a mixed integer linear programming (MILP) model. However, when solving a general MILP model, it is easy to fall into the imbalanced issue of branch-and-bound trees, such that the computational time becomes longer. This study proposes a deterministic model with a powerful and significant theoretical mechanism to conquer the imbalanced issue. Solving the proposed model can minimize the service costs subject to each lane being served by carriers and consider the quantity discount. The most important objective in this study is to identify an iterative algorithm that embeds the proposed model, which presents all alternative solutions for shippers to consider better options. Numerical experiment is also presented to confirm the usefulness of the proposed method. (C) 2019 Elsevier B.V. All rights reserved.

关键词： Winner determination problem Transportation service mixed integer linear programming model Alternative solutions

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linear daily UC model to improve the transient stability of power system

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IET GENERATION TRANSMISSION & DISTRIBUTION 2019年第13期13卷 2877-2888页

作者： Naghdalian, Salar Amraee, Turaj Kamali, Sadegh KN Toosi Univ Technol Fac Elect Engn Tehran Iran

As coherency of generators decreases, the risk of rotor angle instability increases, especially under severe contingencies. The slow coherency as a network characteristic may be controlled by the locations of committed generators. Unit commitment (UC) problem is conventionally carried out regarding operational and network constraints. In this study, a two-step strategy is developed to promote the slow coherency via the network constrained UC (NCUC) model on a daily horizon. First, conventional NCUC is executed. The most important generators with both economic and coherency merits are then determined as representative generators. In the second step, the Slow Coherency Based Unit Commitment (SCBUC) is re-optimisedaccording to the results obtained from the first step, using a multi-objective function. The first part of the multi-objective function is devoted to the cost of generation, start-up, and shutdown of generators. The goal of the second part of the multi-objective function is to maximise the coherency between the committed generators to reach a transient stability margin. The proposed model is converted to a mixed integer linear programming model. The performance of the proposed method of promoting transient stability is investigated using the dynamic IEEE 118-bus test system.

关键词： linear programming power generation dispatch IEEE standards power generation economics power generation scheduling integer programming power system transient stability load flow power system security linear daily UC model power system generators decreases rotor angle instability increases severe contingencies slow coherency network characteristic committed generators unit commitment problem two-step strategy daily horizon conventional NCUC important generators representative generators multiobjective function transient stability margin mixed integer linear programming model

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Enhancing supply chain resilience using ontology-based decision support system

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INTERNATIONAL JOURNAL OF COMPUTER INTEGRATED MANUFACTURING 2019年第7期32卷 642-657页

作者： Singh, Sube Ghosh, Soumava Jayaram, Jayanth Tiwari, Manoj Kumar Indian Inst Technol Kharagpur Dept Ind & Syst Engn Kharagpur W Bengal India Indian Inst Technol Kharagpur Dept Mech Engn Kharagpur W Bengal India Univ South Carolina Darla Moore Sch Business Dept Management Sci Columbia SC 29208 USA

Today's scenario of manufacturing and supply chain is full of uncertainty because of numerous types of disruptions and failures such as fire, storm, machine failure, are a few names. Always supply chain disruptions present disastrous impacts, although probabilities of happening are low. In the recent robust as well as flexible supply chain has captured the focus of researchers in designing a supply chain network with consideration of disruption's risk. In this work, an ontology-based decision support system is proposed to intensify the supply chain resilience during a disruption. The concept of semantic and ontology is adopted in developing the knowledge base for the entire supply chain network including manufacturing units. Protege is used for defining the classes and sub-classes along with numerous types of properties and expressed in a rule-based system using semantic web rule language (SWRL). Furthermore, a mixed integer linear programming model with an objective of maximising quantified resilience to fulfil the demand. A hybrid particle swarm optimisation - differential evolution (PSO-DE) is utilised as an optimisation technique for the defined problem. In performing the study, a set of simulated data is formed and then interpreted in the ontology for an optimal selection of recovery activity.

关键词： Supply chain resilience ontology mixed integer linear programming model hybrid particle swarm optimisation semantic web rule language

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Joint production and transportation scheduling in flexible manufacturing systems

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JOURNAL OF GLOBAL OPTIMIZATION 2019年第4期74卷 879-908页

作者： Fontes, Dalila B. M. M. Homayouni, Seyed Mahdi Univ Porto INESC TEC LIAAD Porto Portugal Islamic Azad Univ Lenjan Branch Dept Ind Engn Esfahan Iran Univ Porto Fac Econ Porto Portugal

This work proposes an integrated formulation for the joint production and transportation scheduling problem in flexible manufacturing environments. In this type of systems, parts (jobs) need to be moved around as the production operations required involve different machines. The transportation of the parts is typically done by a limited number of Automatic Guided Vehicles (AGVs). Therefore, machine scheduling and AGV scheduling are two interrelated problems that need to be addressed simultaneously. The joint production and transportation scheduling problem is formulated as a novel mixed integer linear programming model. The modeling approach proposed makes use of two sets of chained decisions, one for the machine and another for the AGVs, which are inter-connected through the completion time constraints both for machine operations and transportation tasks. The computational experiments on benchmark problem instances using a commercial software (Gurobi) show the efficiency of the modeling approach in finding optimal solutions.

关键词： Flexible manufacturing system Integrated scheduling mixed integer linear programming model

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THE CYCLE SHOP SCHEDULING: MATHEMATICAL model, PROPERTIES AND SOLUTION ALGORITHMS

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RAIRO-OPERATIONS RESEARCH 2019年第1期53卷 111-128页

作者： Naderia, Bahman Goharib, Sheida Kharazmi Univ Dept Ind Engn Fac Engn Tehran Iran Univ Windsor Fac Engn Dept Mech Automot & Mat Windsor ON Canada SUNY Binghamton Dept Syst Sci & Ind Engn Binghamton NY USA

Conventionally, in scheduling problems it is assumed that each job visits each machine once. This paper studies a novel shop scheduling called cycle shop problems where jobs might return to each machine more than once. The problem is first formulated by two mixed integer linear programming models. The characteristics of the problem are analyzed, and it is realized that the problem suffers from a shortcoming called redundancy, i.e., several sequences represents the same schedule. In this regard, some properties are introduced by which the redundant sequences can be recognized before scheduling. Three constructive heuristics are developed. They are based on the shortest processing time first, insertion neighborhood search and non-delay schedules. Then, a metaheuristic based on scatter search is proposed. The algorithms are equipped with the redundancy prevention properties that greatly reduce the computational time of the algorithms. Two sets of experiments are conducted. The proposed model and algorithms are evaluated. The results show the high performance of model and algorithms.

关键词： Scheduling cycle shop mixed integer linear programming model metaheuristic algorithm constructive heuristics

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Optimal port call adjustment for liner container shipping routes

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TRANSPORTATION RESEARCH PART B-METHODOLOGICAL 2019年 128卷 107-128页

作者： Wang, Yadong Meng, Qiang Jia, Peng Nanjing Univ Sci & Technol Sch Econ & Management Nanjing 210094 Jiangsu Peoples R China Natl Univ Singapore Dept Civil & Environm Engn Singapore 117576 Singapore Dalian Maritime Univ Sch Maritime Econ & Management Dalian 116026 Peoples R China

Container shipping companies usually alter their shipping networks in response to the seasonally changing shipping demand and freight rate. Rather than redesigning their shipping networks from scratch, they often choose to make small adjustments to the shipping routes by skipping some ports or adding additional calls to several ports. Inspired by above industrial practice in shipping network alteration, this study solves the port call adjustment problem (PCAP) to determine which port calls should be removed and which should be inserted for each route of a shipping network under the new shipping market patterns. A two-phase solution method is developed for the PCAP. In Phase 1, the candidate port calls for removal and insertion operations in each shipping route are determined. In Phase 2, the port call adjustment strategy is obtained by solving a mixed integer linear programming (MILP) model to select the port calls from these candidates identified in Phase 1 for actual removal and insertion operations. Considering the difficulties in solving the MILP model efficiently, two heuristic methods are also proposed to give near-optimal solutions in an acceptable computational time. Numerical experiments demonstrate that the proposed two-phase method is able to find a port call adjustment strategy that significantly reduces the operating cost. (C) 2019 Elsevier Ltd. All rights reserved.

关键词： Port call adjustment Liner container shipping Network design Service alteration mixed integer linear programming model Heuristic methods

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