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Joint production and transportation scheduling in flexible manufacturing systems

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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Coordinated allocation of soft open point and converter-based energy storage systems in PV penetrated active distribution networks

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IET RENEWABLE POWER GENERATION 2023年第2期17卷 400-412页

作者： Zhou, Niancheng Tao, Anqi Wang, Jian Wang, Qianggang Chongqing Univ State Key Lab Power Transmiss Equipment & Syst Sa Chongqing Peoples R China Hohai Univ Coll Energy & Elect Engn Nanjing 213022 Jiangsu Peoples R China

Soft open point-based energy storage (SOP-based ES) can realize the real-time adjustment of transmission power in space and peak load shaving in time, further promoting the integration of distributed generations (DGs) and decreasing the allocation cost. This article proposed an optimal planning model for coordinated allocation of SOP-based ES and conventional independent ES systems in PV penetrated Active Distribution Networks (ADN). First, the planning models of SOP-based ES, battery of ES systems and its lifetime are established. Second, the proposed coordinated allocation model aims to minimize the total planning cost, including power exchange cost, investment cost, operation cost, battery degradation cost and loss cost. In order to solve the uncertainty of PV output and load demand, the stochastic optimization model is established with scenarios reduced by the K-means clustering technique. Third, the linearization model of the battery degradation cost is derived to transform the optimization model into a mixed integer linear programming (MILP) model. Finally, the presented model is implemented on an IEEE 33-node distribution system to confirm its effectiveness. The case study results show that the coordinated allocation of SOP and converter-based ES can effectively reduce the allocation cost of ES and promote the integration of DGs.

关键词： investment cost Distribution networks battery powered vehicles Optimisation techniques peak load shaving power exchange cost Solar power stations and photovoltaic power systems stochastic optimization model battery degradation cost energy storage total planning cost power distribution planning Power system planning and layout mixed integer linear programming model allocation cost linearization model active distribution networks coordinated allocation model distributed power generation loss cost integer programming converter-based energy storage systems optimal planning model operation cost distributed generations power distribution economics open point-based energy storage electric vehicle charging planning models PV photovoltaic power systems linear programming power convertors SOP-based ES Distributed power generation soft open point IEEE 33-node distribution system

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Multi-haul quasi network flow model for vertical alignment optimization

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ENGINEERING OPTIMIZATION 2017年第10期49卷 1777-1795页

作者： Beiranvand, Vahid Hare, Warren Lucet, Yves Hossain, Shahadat Univ British Columbia Dept Comp Sci Kelowna BC Canada Univ British Columbia Dept Math Kelowna BC Canada

The vertical alignment optimization problem for road design aims to generate a vertical alignment of a new road with a minimum cost, while satisfying safety and design constraints. A new model called multi-haul quasi network flow (MH-QNF) for vertical alignment optimization is presented with the goal of improving the accuracy and reliability of previous mixed integer linear programming models. The performance of the new model is compared with two state-of-the-art models in the field: the complete transportation graph (CTG) and the quasi network flow (QNF) models. The numerical results show that, within a 1% relative error, the proposed model is robust and solves more than 93% of test problems compared to 82% for the CTG and none for the QNF. Moreover, the MH-QNF model solves the problems approximately eight times faster than the CTG model.

关键词： Vertical alignment road design optimization mixed integer linear programming model earthwork allocation variable hauling costs

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Hybridizing Basic Variable Neighborhood Search With Particle Swarm Optimization for Solving Sustainable Ship Routing and Bunker Management Problem

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IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS 2020年第3期21卷 986-997页

作者： De, Arijit Wang, Junwei Tiwari, Manoj Kumar Newcastle Univ Business Sch Newcastle Upon Tyne NE1 7RU Tyne & Wear England Univ Hong Kong Shenzhen Inst Res & Innovat Hong Kong Peoples R China Univ Hong Kong Shenzhen Inst Res & Innovat Dept Ind & Mfg Syst Engn Hong Kong Peoples R China IIT Kharagpur Dept Ind & Syst Engn Kharagpur 721302 W Bengal India

This paper studies a novel sustainable ship routing problem considering a time window concept and bunker fuel management. Ship routing involves the decisions corresponding to the deployment of vessels to multiple ports and time window concept helps to maintain the service level of the port. Reducing carbon emissions within the maritime transportation domain remains one of the most significant challenges as it addresses the sustainability aspect. Bunker fuel management deals with the fuel bunkering issues faced by different ships, such as selection of bunkering ports and total bunkered amount at a port. A novel mathematical model is developed capturing the intricacies of the problem. A hybrid particle swarm optimization with a basic variable neighborhood search algorithm is proposed to solve the model and compared with the exact solutions obtained using Cplex and other popular algorithms for several problem instances. The proposed algorithm outperforms other popular algorithms in all the instances in terms of the solution quality and provides good quality solutions with an average cost deviation of 5.99% from the optimal solution.

关键词： Fuels Marine vehicles Routing Carbon dioxide Transportation Mathematical model Microsoft Windows Ship routing bunker fuel management mixed integer linear programming model variable neighborhood search algorithm

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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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Finding optimal dwell points for automated guided vehicles in general guide-path layouts

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INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS 2015年第PartC期170卷 850-861页

作者： Ventura, Jose A. Pazhani, Subramanian Mendoza, Abraham Penn State Univ Harold & Inge Marcus Dept Ind & Mfg Engn University Pk PA 16802 USA Univ Panamer Zapopan Dept Ind Engn Zapopan 45010 Jalisco Mexico

The dwell points for idle vehicles in an automated guided vehicle (AGV) system determine the response times for pick-up requests and thus affect the performance of automated manufacturing systems. In this paper, we address the problem of optimally locating dwell points for a given number of AGVs in a general guide-path layout. Based on an optimality property, we propose new mixed integer linear programming (MILP) formulations for three versions of the problem: (i) minimizing the mean response time in the system, (ii) minimizing the maximum response time in the system, and (iii) minimizing the maximum response time in the system considering time restrictions on vehicle availability. Given that the computational time required to solve the MILP models significantly increases with the size of the guide-path network and number of available AGVs, we also develop a generic genetic algorithm (GA) that can be applied to all three versions of the problem. A computational study is carried out on the single-loop layout and two special cases of two-dimensional grid networks with the objectives of minimizing mean response time and minimizing the maximum response time. The results show that the proposed GA procedure can yield optimal or near optimal solutions in reasonable time. (C) 2015 Elsevier B.V. All rights reserved.

关键词： Automated guided vehicle system Dwell point location mixed integer linear programming model Genetic algorithm

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A risk-based resilient distribution system planning model against extreme weather events

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IET RENEWABLE POWER GENERATION 2022年第10期16卷 2125-2135页

作者： Zare-Bahramabadi, Majid Ehsan, Mehdi Farzin, Hossein Sharif Univ Technol Dept Elect Engn Ctr Excellence Power Syst Management & Control Tehran *** Iran Shahid Qumran Univ Ahvaz Fac Engn Ahvaz Iran

Due to the accelerated climate change, it is anticipated that the number and severity of natural disasters such as hurricanes, blizzards, and floods will be increased in the coming years. In this regard, this paper presents a distribution system planning model to improve the system resilience against hurricane. A scenario-based mathematical model is proposed to capture the random nature of weather events. Moreover, a stochastic optimization model is developed to simultaneously harden the distribution lines and place different types of distributed generation (DG) units such as microturbines (MTs), wind turbines (WTs), and photovoltaic cells (PVs). The conditional value at risk (CVaR) is used as a risk index to manage the system risk against different failure scenarios. The problem is formulated as a mixed integer linear programming (MILP) model that can be solved by various commercial solvers. Finally, to illustrate the effectiveness of the proposed model, it is implemented on the IEEE 33 bus system, and various case studies are defined. The results show the effectiveness of our mathematical model in improving the distribution system resiliency and managing the system risk.

关键词： distributed power generation linear programming scenario-based mathematical model stochastic optimization model mixed integer linear programming model risk-based resilient distribution system planning model distribution system resiliency integer programming natural disasters disasters risk index extreme weather events system risk accelerated climate change different failure scenarios distribution lines system resilience wind turbines distributed generation units IEEE 33 bus system hurricane

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Exact methods for sensor deployment problem with connectivity constraint in wireless sensor networks

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INTERNATIONAL JOURNAL OF SENSOR NETWORKS 2016年第3期21卷 157-168页

作者： Rebai, Maher Afsar, Hasan Murat Snoussi, Hichem Univ Technol Troyes CNRS UMR 6281 ICD LM2S BP2060 F-10010 Troyes France Univ Technol Troyes CNRS UMR 6281 ICD LOSI BP2060 F-10010 Troyes France Univ Technol Troyes CNRS UMR 6281 ICD LM2S BP2060 F-10010 Troyes France

In wireless sensor networks, coverage and connectivity are two essential issues. They indicate how all the points of an area of interest are covered and how the sensor devices of the wireless sensor network are connected in an efficient way. In this study, the problem of minimising total grid coverage cost with connectivity constraint is considered. The connectivity constraint means that each deployed sensor has to find a path, composed of connected sensors, until to reach the base station (the sink). The problem may be reduced to a 2-dimensional critical grid coverage problem which is anNP-Complete problem. We propose mixed integer linear programming models to solve the problem optimally. We verify by computational experiments that the developed approaches can provide the optimal solution of grid sizes of (15 x 15) (width x length) in a reasonable time. We also show that one of the proposed methods is more efficient than some methods developed for similar problems.

关键词： wireless sensor networks total grid coverage problem mixed integer linear programming model location problem

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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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Production and transport scheduling in flexible job shop manufacturing systems

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JOURNAL OF GLOBAL OPTIMIZATION 2021年第2期79卷 463-502页

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

This paper addresses an extension of the flexible job shop scheduling problem by considering that jobs need to be moved around the shop-floor by a set of vehicles. Thus, this problem involves assigning each production operation to one of the alternative machines, finding the sequence of operations for each machine, assigning each transport task to one of the vehicles, and finding the sequence of transport tasks for each vehicle, simultaneously. Transportation is usually neglected in the literature and when considered, an unlimited number of vehicles is, typically, assumed. Here, we propose the first mixed integer linear programming model for this problem and show its efficiency at solving small-sized instances to optimality. In addition, and due to the NP-hard nature of the problem, we propose a local search based heuristic that the computational experiments show to be effective, efficient, and robust.

关键词： Flexible job shop Transport mixed integer linear programming model Late acceptance hill climbing

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