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Energy-Efficient Data Gathering Framework-Based Clustering via Multiple UAVs in Deadline-Based WSN Applications

IEEE ACCESS 2018年 6卷 72275-72286页

作者： Albu-Salih, Alaa Taima Seno, Seyed Amin Hosseini Ferdowsi Univ Mashhad Comp Engn Dept Mashhad *** Iran

This paper proposes a new method for energy-efficient data gathering using multiple unmanned aerial vehicles (UAVs) in deadline-based wireless sensor networks (WSNs). This method collects WSN node data in minimum energy by providing the optimal position and trajectory of UAVs, the minimum travel time, and the minimum number of UAVs in a determined deadline. First, in order to minimize the energy consumption of WSN nodes and determine the positions of where to place UAVs for receiving network nodes data, this paper clusters the nodes in a distributed form and considers the centers of these clusters as a place to meet the UAVs. Then, beginning and ending virtual nodes are used for controlling the minimum number of UAVs. This paper attempts to complete the proposed solution and obtain the minimum travel time of UAV required for collecting data from the network. In order to find the optimal solution for this problem, a mixed integer linear programming mathematical model is presented, followed by normalizing and putting weights on each part of an objective function. Results obtained in the simulation step show that the presented model has an optimal performance in providing the position and optimal trajectory of UAVs, energy consumption, minimum travel time, and the number of UAVs used.

关键词： Data gathering wireless sensor networks unmanned aerial vehicles mixed integer linear programming model deadline clustering

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Heuristic approach for the multiobjective optimization of the customized bus scheduling problem

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IET INTELLIGENT TRANSPORT SYSTEMS 2022年第3期16卷 277-291页

作者： Liu, Kaijun Liu, Jianming Zhang, Jingwei Guilin Univ Elect Technol Guangxi Key Lab Trusted Software Guilin 541004 Peoples R China

Customized bus is a typical demand-responsive transit (DRT) service that allows passengers to customize their bus route on demand and be picked up and dropped off at their desired location. A set of ride requests sent at various times by geographically dispersed passengers are operated in real time by the controller and then assigned to the shared bus with the assurance of maintaining the minimum vehicle and driver costs, which introduces a new challenge to scheduling. In this paper, a mixed integer linear programming (MILP) model is presented to solve the customized bus scheduling problem. To quickly generate satisfactory scheduling solutions in the case of single- and multi-depots, a heuristic multi-objective optimization algorithm based on preemptive scheduling is proposed, which can converge to the optimal solution among a set of vehicle blocks (consecutive trips by one bus). A real-world customized bus scheduling problem from the public transport company of Chengdu, China that contains 2,000-trip instances operated on a day is used to demonstrate that the proposed approach reduces total operating costs by 30.51% and 30.71%, compared with the simulated annealing algorithm and genetic algorithm, respectively.

关键词： linear programming geographically dispersed passengers mixed integer linear programming model public transport integer programming optimisation multiobjective optimization algorithm driver costs satisfactory scheduling solutions vehicle routing one bus preemptive scheduling typical demand-responsive transit bus route scheduling customized bus scheduling problem minimum vehicle simulated annealing shared bus genetic algorithms

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Optimisation-based switch allocation to improve energy losses and service restoration in radial electrical distribution systems

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IET GENERATION TRANSMISSION & DISTRIBUTION 2016年第11期10卷 2792-2801页

作者： Lopez, Juan Camilo Franco, John Fredy Rider, Marcos J. UNICAMP Univ Estadual Campinas Dept Sistemas Energia Eletr Fac Engn Engn Eletr & Comp Sao Paulo Brazil UNESP Univ Estadual Paulista Dept Engn Eletr Fac Engn Ilha Solteira Sao Paulo Brazil

This study presents a new methodology for the optimal allocation of switching devices in radial electrical distribution systems (EDSs). A specialised greedy randomised adaptive search procedure (GRASP) algorithm defines the location of a number of switching devices in order to simultaneously improve the following optimisation subproblems related to the use of the allocated switches: (i) the optimal reconfiguration of EDS and (ii) the optimal service restoration of EDS. Eventually, the objective function of the proposed switch allocation algorithm minimises the cost of the total expected energy not supplied, computed after deploying the service restoration, plus the cost of the total annual energy loss computed for every load level in a year, plus the investment costs associated with the number of installed switches. Both optimisation subproblems, i.e. the reconfiguration and the restoration of EDS, are represented by mixed-integer non-linear programming (MINLP) models and transformed into mixed-integer linear programming (MILP) models, using linearisation strategies. MILP models guarantee convergence to optimality by using convex optimisation techniques. Finally, all tests were carried out using a real 136-node distribution system, considering dispatchable and non-dispatchable distributed generation resources.

关键词： power system restoration power distribution reliability search problems randomised algorithms greedy algorithms power distribution economics cost reduction integer programming linear programming linearisation techniques convex programming power generation dispatch distributed power generation power generation economics optimisation-based switch allocation energy loss improvement radial electrical distribution system greedy randomised adaptive search procedure algorithm optimisation subproblem EDS optimal reconfiguration EDS optimal service restoration cost minimisation switch allocation algorithm objective function investment cost mixed integer nonlinear programming model mixed integer linear programming model MILP model linearisation strategy convex optimisation tools 136-node distribution system dispatchable DG resource nondispatchable DG resource

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Improved artificial immune algorithm for the flexible job shop problem with transportation time

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MEASUREMENT & CONTROL 2020年第9-10期53卷 2111-2128页

作者： Chen, Xiao-long Li, Jun-qing Han, Yu-yan Sang, Hong-yan Shandong Normal Univ Sch Informat Sci & Engn Jinan 250014 Peoples R China Liaocheng Univ Sch Comp Liaocheng Shandong Peoples R China

The flexible job shop problem (FJSP), as one branch of the job shop scheduling, has been studied during recent years. However, several realistic constraints including the transportation time between machines and energy consumptions are generally ignored. To fill this gap, this study investigated a FJSP considering energy consumption and transportation time constraints. A sequence-based mixed integer linear programming (MILP) model based on the problem is established, and the weighted sum of maximum completion time and energy consumption is optimized. Then, we present a combinational meta-heuristic algorithm based on a simulated annealing (SA) algorithm and an artificial immune algorithm (AIA) for this problem. In the proposed algorithm, the AIA with an information entropy strategy is utilized for global optimization. In addition, the SA algorithm is embedded to enhance the local search abilities. Eventually, the Taguchi method is used to evaluate various parameters. Computational comparison with the other meta-heuristic algorithms shows that the improved artificial immune algorithm (IAIA) is more efficient for solving FJSP with different problem scales.

关键词： Flexible job shop transportation time energy consumption mixed integer linear programming model improved artificial immune algorithm

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An optimization approach to design forest road networks and plan timber transportation

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OPERATIONAL RESEARCH 2022年第3期22卷 2973-3001页

作者： Mesquita, Marta Marques, Susete Marques, Marlene Marto, Marco Constantino, Miguel Borges, Jose G. Univ Lisbon Fac Ciencias Ctr Matemat Aplicacoes Fundamentais & Invest Oper C6 Campo Grande P-1749016 Lisbon Portugal Ctr Estudos Florestais & Lab TERRA P-1349017 Lisbon Portugal Univ Lisbon Inst Super Agron P-1349017 Lisbon Portugal Univ Lisbon Fac Ciencias DEIO C6 Campo Grande P-1749016 Lisbon Portugal

The provision of ecosystem services depends on the landscape-level distribution of forest management options over extended planning horizons. Nevertheless, transportation costs are an important fraction of total procurement costs. Therefore, forest managers are challenged by the need to make decisions regarding the design of the road network needed to have access to forest management units (e.g., stands) as well as the transportation of forest products over this network. The objective of this research is to develop an approach to integrate the design and maintenance of a forest roads' network and to provide solutions to the timber loading location site and the timber transportation problems. The emphasis is on the combination of mathematical programming formulations and heuristic solution techniques to minimize the sum of road building, road maintenance, timber loading and transportation costs. Specifically, a mixed integer programming model is built to represent the problem while a heuristic algorithm, based on a Graph Simplification procedure and a big-M Estimation procedure, is proposed to solve the underlying optimization problem. Results from an application to a large-scale forest management problem in Northwest Portugal involving 1137 management units are discussed. Results suggest that this approach may help address efficiently the need by forest managers to integrate road design, road maintenance, timber loading location and transportation concerns.

关键词： Forest road network design Road building Road maintenance Timber transportation mixed integer linear programming model Big-M estimation procedure

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A network flow-based algorithm for bus driver rerostering

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OR SPECTRUM 2021年第2期43卷 543-576页

作者： Paias, Ana Mesquita, Marta Moz, Margarida Pato, Margarida Univ Lisbon Fac Ciencias Ctr Matemat Aplicacoes Fundamentais & Invest Oper C6 P-1749016 Lisbon Portugal Univ Lisbon Fac Ciencias DEIO C6 P-1749016 Lisbon Portugal Univ Lisbon Inst Super Agron P-1349017 Lisbon Portugal Univ Lisbon ISEG Rua Quelhas 6 P-1200781 Lisbon Portugal

Bus driver rostering generates the work plan for a pool of drivers during a planning period of predefined length. This plan, called the roster, must consider the balance between the pressure of costs, the provision of a service of high quality, labour agreements, and the goodwill of the workers. The bus driver rerostering problem occurs during real-time operational planning, when unexpected events-such as non-planned absences of drivers-disrupt the roster. To reconstruct a roster which is originally built in a context of days off schedules for drivers, we propose a reactive methodology based on a multicommodity flow assignment mixed integer linear programming model. The objective is to minimise the number of depot drivers who are assigned to drive and the number of postponed days off, as well as the dissimilarity between the reconstructed and the original roster and the balancing of the workload. The proposed algorithm enables the disrupted roster to be reconstructed at the expense of a relatively small number of changes in drivers' work and rest periods, while, at the same time, controlling the dimension of the multicommodity flow network. Computational experience based on real-life based instances revealed that the algorithm has the ability to produce reconstructed rosters with few changes to the drivers' original work assignment, in a short CPU time.

关键词： Bus driver rerostering Bus driver rostering mixed integer linear programming model Multicommodity flow assignment model

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A MILP model for an integrated project scheduling and multi-skilled workforce allocation with flexible working hours

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IFAC-PapersOnLine 2017年第1期50卷 13964-13969页

作者： Karam, Ahmed Attia, El-Awady Duquenne, Philippe Benha University Cairo Egypt Industrial Engineering Department Toulouse University INPT Toulouse cedex 4 France

In this paper, we integrate two decision problems arising in various applications such as production planning and project management: the project scheduling problem, which consists in scheduling a set of precedence-constrained tasks, where each task requires executing a set of skills to be performed, and the workforce allocation problem which includes assigning workers as scarce resources to the skills of each task. These two problems are interrelated as the tasks durations are not predefined, but depend on the number of workers assigned to that task as well as their skill levels. We here present a mixed integer linear programming model that considers important real life aspects related to the flexibility in the use of human resources, such as multi-skilled workers whose skill levels are different and measured by their efficiencies. Hence, execution times of the same workload by different workers vary according to these efficiencies. Moreover, the model considers the flexible working time of employees; i.e. the daily and weekly workload of a given worker may vary from one period to another according to the work required. Furthermore, efficient team building is incorporated in this model; i.e. assigning an expert worker and one or more apprentice worker(s) together with the purpose of skill development thanks to knowledge transfer. A numerical example is provided to check the performance of the model. © 2017

关键词： Scheduling Efficiency Human resource management integer programming Knowledge management Multitasking Production control Allocation problems mixed integer linear programming mixed integer linear programming model Production Planning Project scheduling problem Skilled workers Workforce flexibility Working time

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Multi-objective no-wait flowshop scheduling problems: models and algorithms

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INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 2012年第10期50卷 2592-2608页

作者： Naderi, B. Aminnayeri, M. Piri, M. Yazdi, M. H. Ha'iri Univ Tehran Dept Ind Engn Fac Engn Tehran Iran Amirkabir Univ Technol Dept Ind Engn Tehran Iran Iran Univ Sci & Technol Dept Ind Engn Tehran Iran Univ Tehran Sch Mech Engn Fac Engn Tehran Iran

This article studies multi-objective no-wait flowshop scheduling problems to minimise both makespan and total tardiness. This problem is commonly denoted by F/nwt/TT, C-max. This article mathematically formulates the problem using two effective multi-objective mixed integer linear programming models. The multi-objective mathematical models are then solved by a multiple criteria decision making approach, called Fuzzy programming method. Moreover, the article proposes a novel multi-objective iterated local search algorithm incorporating three types of local search engine: greedy, moderate and curtailed fashions. The algorithm is carefully evaluated for its performance against two available algorithms by means of multi-objective performance measures and statistical tools. The results show that the proposed solution method outperforms the others.

关键词： no-wait flowshop scheduling multi-objective iterated local search algorithm mixed integer linear programming model

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Optimal sizing and multi-energy management strategy for PV-biofuel-based off-grid systems

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IET SMART GRID 2020年第1期3卷 83-97页

作者： Kumar, Arun, V Sharma, Sumedha Verma, Ashu Indian Inst Technol Delhi Ctr Energy Studies New Delhi India

This study proposes a comprehensive framework for developing a multi-energy off-grid microgrid with the decoupled flow of thermal and electrical energies in a rural setting. A carbon-neutral microgrid with a hybrid generation system constituting a photovoltaic unit and a biofuel generator is proposed. In order to enhance the fuel utilisation efficiency, the biofuel generator is operated in combined cooling, heating, and power mode, and the recovered thermal energy forms the heat distribution network in the microgrid. The flexibility of system operation is improved by suitable multi-energy (electrical and thermal) storage. Firstly, an optimal sizing framework has been developed for the system as a mixed integer linear programming model. Secondly, a coordinated multi-energy management system (MEMS) has been developed for combined optimal dispatch of multiple generation and storage resources. The MEMS has been developed as a mixed integer non-linear programming model, which minimises system operational cost while considering minimum battery degradation to prolong its lifetime. Finally, a detailed economic analysis of the proposed system has been presented, highlighting the levellised cost of energy and net present value. Extensive case studies and simulation results depict the effectiveness and suitability of the proposed MEMS for the rural off-grid microgrid.

关键词： nonlinear programming energy management systems cogeneration biofuel hybrid power systems linear programming integer programming photovoltaic power systems distributed power generation power generation economics PV-biofuel-based off-grid systems decoupled flow rural setting carbon-neutral microgrid hybrid generation system photovoltaic unit biofuel generator fuel utilisation efficiency recovered thermal energy forms heat distribution network system operation optimal sizing framework mixed integer linear programming model multienergy management system MEMS combined optimal dispatch storage resources mixed integer nonlinear programming model system operational cost combined cooling heating and power mode multi-energy off-grid microgrid levelised cost of energy net present value B0260 Optimisation techniques B8110B Power system management, operation and economics B8210 Energy resources B8230 Thermal power stations and plants B8250 Solar power stations and photovoltaic power systems B8120K Distributed power generation

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Sustainable open vehicle routing with release-time and time-window: A two-echelon distribution system

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IFAC-PapersOnLine 2019年第13期52卷 571-576页

作者： Babagolzadeh, M. Shrestha, A. Abbasi, B. Zhang, S. Atefi, R. Woodhead, A. School of Commerce University of Southern Queensland ToowoombaQLD Australia School of Management and Enterprise University of Southern Queensland ToowoombaQLD Australia School of Business IT and Logistics RMIT University Melbourne Australia Department of Industrial Engineering Ferdowsi university of Mashhad Mashhad Iran University of Southern Queensland ToowoombaQLD Australia

In an increasingly competitive economic environment, outsourcing for logistics has emerged as a cost-efficient strategy during freight transportation. The open vehicle routing problem is a type of classical vehicle routing problem, in which businesses outsource logistics to a third-party company and the vehicles do not return to the depot at the end of their journey. This paper develops a mixed integer linear programming model for two-echelon open vehicle routing problem that integrates city distribution constraints such as time-window and release-time. The release-time refers to the time at which products become ready at satellites for downstream distribution, and it is influenced by limited available resources and work load of each satellite. The proposed model determines the optimal configuration of the routes while minimizing the handling costs, penalty costs, and transportation costs. We use a comprehensive emission model that accounts for load, distance, speed and vehicle characteristics to estimate fuel consumption. Finally, we utilize a numerical example to illustrate the proposed model and explore the effects of release-time on total cost. © 2019, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Vehicle routing Freight transportation integer programming Supply chains Vehicles Distribution systems mixed integer linear programming model Open vehicle routing problems Release time Sustainable supply chains Time windows Vehicle characteristics Vehicle Routing Problems

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