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Multistation coordinated and dynamic passenger inflow control for a metro line

IET INTELLIGENT TRANSPORT SYSTEMS 2020年第9期14卷 1068-1078页

作者： Wang, Xingrong Wu, Jianjun Yang, Xin Guo, Xin Yin, Haodong Sun, Huijun Beijing Jiaotong Univ State Key Lab Rail Traff Control & Safety Beijing Peoples R China Beijing Jiaotong Univ Key Lab Transport Ind Big Data Applicat Technol C Minist Transport Beijing Peoples R China

Passenger inflow control is an efficient way to relieve peak passenger flow and reduce security risks in metro networks. However, station operators develop passenger inflow control strategies independently, thus ignore the interactions among stations and lines in the actual operation. Subsequently, the single-fixed control intensity usually fails to satisfy dynamic temporal passenger demand, resulting in great stranded passengers. To address this problem, a coordinated and dynamic inflow control method is proposed to generate an optimal demand-driven control pattern in metro systems. First, a mixed integer programming model with the concept of the equivalent time interval is formulated to minimise the total number of stranded passengers on one line. Second, special consideration is paid to the transfer passengers with the aim of ensuring the safety of transfer stations. Finally, an actual passenger flow and train operation data in Beijing Batong line is conducted to test the performance of the approach. Compared with the non-coordinated and dynamic inflow control method, results show that the proposed model can balance the utilisation of transportation capacity and reduce the total number of stranded passengers by 20.6%. Sensitivity analysis results indicate that both transportation capacity and transfer capability are the main factors affecting the inflow control.

关键词： integer programming rail traffic rapid transit systems sensitivity analysis transportation railways transfer stations actual passenger flow train operation data Beijing Batong line dynamic inflow control method dynamic passenger inflow control metro line peak passenger flow security risks metro networks station operators passenger inflow control strategies single-fixed control intensity dynamic temporal passenger demand great stranded passengers coordinated inflow control method optimal demand-driven control pattern metro systems mixed integer programming model transfer passengers

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An epsilon-free approach for finding the most efficient unit in DEA

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APPLIED MATHEMATICAL modelLING 2014年第13期38卷 3182-3192页

作者： Toloo, Mehdi Tech Univ Ostrava Fac Econ Dept Business Adm Ostrava Czech Republic

Data envelopment analysis (DEA), considering the best condition for each decision making unit (DMU), assesses the relative efficiency and partitions DMUs into two sets: efficient and inefficient. Practically, in traditional DEA models more than one efficient DMU are recognized and these models cannot rank efficient DMUs. Some studies have been carried out aiming at ranking efficient DMUs, although in some cases only discrimination of the most efficient unit is desirable. Furthermore, several investigations have been done for finding the most CCR-efficient DMU. The basic idea of the majority of them is to introduce an integrated model which achieves an optimal common set of weights (CSW). These weights help us identify the most efficient unit in an identical condition. Recently, Toloo (2012) [13] proposed a new mixed integer programming (MIP) model to find the most BCC-efficient unit. Based on this study, we propose a new basic integrated linear programming (LP) model to identify candidate DMUs for being the most efficient unit;next a new MIP integrated DEA model is introduced for determining the most efficient DMU. Moreover, these models exclude the non-Archimedean epsilon and consequently the optimal solution of these models can be obtained, straightforwardly. We claim that the most efficient unit, which could be obtained from all other integrated models, has to be one of the achieved candidates from the basic integrated LP model. Two numerical examples are illustrated to show the variant use of these models in different important cases. (C) 2013 Elsevier Inc. All rights reserved.

关键词： Data envelopment analysis mixed integer programming model Epsilon-free approach The most efficient unit Common set of weights Facility layout design

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Resource allocation and route planning under the collection price uncertainty for the biomass supply chain

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BIOSYSTEMS ENGINEERING 2024年 241卷 68-82页

作者： Wang, Xiang Ting Cao, Jin Xin Lv, Ying Beijing Jiaotong Univ Sch Syst Sci Beijing 100044 Peoples R China Inner Mongolia Acad Sci & Technol Hohhot 010010 Peoples R China Inner Mongolia Univ Inst Transportat Engn Hohhot 010070 Peoples R China

The escalating severity of global warming has drawn worldwide attention to ecological problems. Nevertheless, with the introduction of environmental policies, biomass resources have been effectively developed as a renewable energy source. This paper investigates an advanced biomass supply chain design wherein biomass resources are initially converted into bio-oil through widely distributed fast pyrolysis facilities, and are subsequently transported to a centralised biorefinery for further refining into biofuels. This novel biomass supply chain addressed three key issues: (1) The number of fast pyrolysis facilities, (2) The allocation of resources, and (3) The routes of resources transport. In respect of these problems, a two-stage stochastic mixed integer programming model is established to minimise the total cost of the biomass supply chain considering the uncertainty collection price of fast pyrolysis facilities. A hybrid simulated annealing algorithm which incorporates the sample average approximation method is proposed to solve the stochastic model and is effectiveness for large-scale examples. Finally, a sensitivity analysis is performed using the proposed algorithm and the results show that the proposed stochastic model outperforms the deterministic model under uncertain collection price. The model allows optimising the biomass supply chain economic performances and minimise financial risk on investment by determining the fast pyrolysis facility locations, reasonable resource allocation and optimal transport routes under uncertain collection price.

关键词： Stochastic programming mixed integer programming model Hybrid simulated annealing algorithm Sample average approximation

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A Location-allocation model for Bio-waste Management in the Hospitality Sector

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NETWORKS & SPATIAL ECONOMICS 2023年第3期23卷 611-639页

作者： Santos-Penate, Dolores R. Suarez-Vega, Rafael R. de la Nuez, Carmen Florido Univ Las Palmas Gran Canaria Dpto Metodos Cuantitat Econ & Gest TIDES Las Palmas De GC Spain Univ Las Palmas Gran Canaria Dpto Anal Econ Aplicado TIDES Las Palmas De GC Spain

Tourism generates huge amounts of waste. It has been estimated that about half of the waste generated by hotels is food and garden bio-waste. This bio-waste can be used to make compost and pellets. In turn, pellets can be used as an absorbent material in composters and as an energy source. In this paper, we consider the problem of locating composting and pellet-making facilities so that the bio-waste generated by a chain of hotels can be managed at or close to the generation points. The general objective is twofold: i) to avoid waste transportation from generation to treatment points and product transportation from production to demand points, and ii) to implement a circular model in which the hotels themselves become the suppliers of the products they need (compost and pellets) by transforming the bio-waste that they generate. Any bio-waste not processed by the hotels has to be treated at private or state-run plants. A mathematical optimization model is presented to locate the facilities and allocate the waste and products. The application of the proposed location-allocation model is illustrated with an example.

关键词： Circular economy Tourism Sustainability mixed integer programming model

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A MILP model and memetic algorithm for the Hub Location and Routing problem with distinct collection and delivery tours

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COMPUTERS & INDUSTRIAL ENGINEERING 2019年 135卷 105-119页

作者： Yang, Xiao Bostel, Nathalie Dejax, Pierre Shanghai Customs Coll Dept Customs Adm Shanghai 201204 Peoples R China Univ Nantes LS2N CNRS F-44000 Nantes France CNRS LS2N IMT Atlantique F-44300 Nantes France

In this paper, we study the capacitated single allocation Hub Location-Routing Problem (CSAHLRP) with independent collection and delivery processes. We focus on the design of less-than-truck load (LTL) transport networks for the transport of goods between many shippers and their clients using flow concentration hubs. We seek to integrate the hub location and vehicle routing strategies such that the location of the hubs, the allocation of supplier/client nodes to hubs, the design of routes between nodes allocated to the same hub, as well as the inter-hub freight transportations, can be determined efficiently. We propose a mixed integer linear programming model for the problem with the aim of minimizing the total fixed and variable costs. Computational experiments based on the Australian Post (AP) data set geographical network are conducted with the CPLEX solver. Furthermore, we propose a memetic algorithm (MA) to solve large problems. Computational results show that the exact method can find optimal solutions for small instances and good feasible solutions for some medium-sized tests. In addition to also solving small problems to optimality, the MA succeeds in finding high quality solutions for medium and large CSAHLRPs efficiently.

关键词： Hub Location-Routing Problem LTL transport mixed integer programming model Memetic algorithm

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A two-echelon location-routing problem for biomass logistics systems

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BIOSYSTEMS ENGINEERING 2021年 202卷 106-118页

作者： Cao, Jin Xin Wang, Xiangting Gao, Jiachen Inner Mongolia Univ Inst Transportat 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

Biomass has attracted considerable attention from both researchers and practitioners as an important renewable energy source that can help achieve sustainable development. However, inefficient biomass logistics systems hinder the development of biomass utilisation. This study investigates a two-echelon biomass resource location-routing problem (2E-BRLRP). Considering a predetermined supply of biomass resources, a mixed integer programming model for the 2EBRLRP is established to determine the best locations for biomass collection facilities and corresponding vehicle routes. To address the computational complexity, a hybrid heuristic algorithm that embeds variable neighbourhood search into the tabu search framework is developed. A set of comprehensive computational examples are used to test the effectiveness and efficiency of the proposed approach. (c) 2020 IAgrE. Published by Elsevier Ltd. All rights reserved.

关键词： Biomass logistics systems Location-routing problem mixed integer programming model Tabu search Variable neighbourhood search

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mixed integer linear formulation for undervoltage load shedding to provide voltage stability

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IET GENERATION TRANSMISSION & DISTRIBUTION 2018年第9期12卷 2095-2104页

作者： Javadi, Masoud Amraee, Turaj KN Toosi Univ Technol Fac Elect Engn Tehran Iran

Undervoltage load shedding (UVLS) is the last resort against voltage instability in critical situations. Here, the UVLS scheme is formulated as a mixed integer programming (MIP) model. The aim of the proposed UVLS model is to provide a predetermined value of loading margin with minimum amount of load shed. The full non-linear AC power flow equations are linearised using a piecewise linear technique. The proposed linear AC power flow is then integrated into the UVLS problem. A ZIP load model is utilised to demonstrate the fulfilment of the MIP-based UVLS model under non-linear static loads. The efficacy of the developed linear AC power flow is verified under different operational conditions and contingencies. The results of the proposed MIP-based UVLS model are compared with the original non-linear programming UVLS formulation. To verify the performance of the developed load shedding strategy, the proposed MIP-based UVLS model is implemented in IEEE 14-bus and IEEE 118-bus test systems.

关键词： load shedding linear programming integer programming power system stability load flow piecewise linear techniques voltage stability undervoltage load shedding critical situations mixed integer programming model nonlinear AC power flow equations piecewise linear technique ZIP load model MIP-based UVLS model nonlinear static loads operational conditions IEEE 14-bus test systems IEEE 118-bus test systems

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An asset-management oriented methodology for mine haul-fleet usage scheduling

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RELIABILITY ENGINEERING & SYSTEM SAFETY 2018年第Dec.期180卷 336-344页

作者： Nakousi, C. Pascual, R. Anani, A. Kristjanpoller, F. Lillo, P. Univ Concepcion Mech Engn Dept Edmundo Larenas 219 Concepcion Chile Pontificia Univ Catolica Chile Min Engn Dept Vicuna Mackenna 4860 Santiago Chile Univ Tecn Federico Santa Maria Dept Ind Engn Av Espana 1680 Valparaiso 2340000 Chile

Different complexities force mining companies to find efficient ways to respond to demand challenges and ensure long-term sustainability. It explains, in part, the increase in the use of prescriptive analytics to optimize physical-asset life-cycle costs and decrease greenhouse gas (GHG) emissions. Mining, being an asset-intensive industry, provides huge improvement opportunities. This is especially true for scheduling practices of mine haulage fleet usage in long term planning. Fleet aging implies important cost increases in maintenance and repair (M&R), and overhauls. Fleets are often heterogeneous in term of truck performance, fuel consumption and GHG emissions. Sub-optimal scheduling decisions may induce severe cost over-runs and increased emissions. This paper proposes an original mixed integer programming formulation to optimize mine haulage equipment scheduling in the long term. The model considers the effects of equipment aging, fuel consumption, payload capacity and cycle times. Our formulation handles different aspects that according to author's knowledge have not been considered in the literature as a whole: (i) joint minimization of fuel, M&R, and overhaul costs, (ii) reduction of GHG emissions, (iii) heterogeneous equipment performance metrics, (iv) increase in cycle times due to mine aging. The case study shows a cost reduction of 13% in the discounted flows associated with fuel, M&R, and overhauls in a time horizon of 10 years. This figure translates into an NPV gain of 13.1 million USD. Additionally, GHG emissions are reduced by an average of 3470 t/year or 11% overall.

关键词： Physical asset management Greenhouse gas emissions mixed integer programming model Haulage fleet scheduling

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Improved estimation of distribution algorithm for the problem of single-machine scheduling with deteriorating jobs and different due dates

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COMPUTATIONAL & APPLIED MATHEMATICS 2014年第3期33卷 557-573页

作者： Wu, Hua-Pin Huang, Min Northeastern Univ Coll Informat Sci & Engn State Key Lab Synthet Automat Proc Ind Shenyang 110819 Liaoning Peoples R China

This paper investigates single-machine scheduling problem, which is an NP-hard problem, with deteriorating jobs and different due dates tominimize total tardiness. First, two special polynomially solvable cases of the problem and a mixed-integer programming (MIP) model are proposed. Since the large-scale problem needs a long time when the MIP is solved using the CPLEX, the improved estimation of distribution algorithm (EDA) is proposed to solve the problem with a large size. EDA depends on the probabilistic model, which denotes the distribution of decision variables in the feasible region space. Meanwhile, EDA owns efficient search capability and convergence. To obtain an improved initial population, an efficient initialization scheme based on the feature of two special cases and a heuristic algorithm are adopted in the process of constructing the initial population. The probabilistic model is composited based on elite solutions from each generation. Simultaneously, mutation is embedded tomaintain the diversity of the population. Compared with the results, numerical experiments show that the proposed algorithm can obtain good near-optimal solutions within a short period.

关键词： Single machine Deteriorating jobs Tardiness Estimation of distribution algorithm mixed integer programming model

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A hybrid multi-stage stochastic programming-robust optimization model for maximizing the supply chain of a forest-based biomass power plant considering uncertainties

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JOURNAL OF CLEANER PRODUCTION 2016年第Part4期112卷 3285-3293页

作者： Shabani, Nazanin Sowlati, Taraneh Univ British Columbia Dept Wood Sci Ind Engn Res Grp Vancouver BC V6T 1Z4 Canada

Electricity generated from forest-based biomass is an attractive source of renewable energy. However, the cost of generating heat and/or electricity from it is relatively high due to the low energy density of wood, high moisture content and variations in its quality and availability. models have been developed to optimize the supply chain and reduce the cost per kilowatt hour generated. This paper focuses on incorporating uncertainty in the supply chain of such a model. The model considers the tactical supply chain planning of a power plant over a one-year time horizon with monthly time steps. Uncertain parameters which impact the net profit of the power plant include 'biomass quality,' namely moisture content and higher heating value, and 'monthly available biomass' from different suppliers. Robust optimization is used to model uncertainty in the quality of biomass. Then a hybrid, multi-stage, 'stochastic programming-robust optimization' model is presented in order to simultaneously include uncertainty in biomass quality and biomass availability. It is demonstrated that the hybrid model takes advantage of both modelling approaches to balance the profit estimates and the tractability to various circumstances. The model provides solution considering all instances of the uncertain parameters within the defined sets and scenario tree. The results revealed a major trade-off between profit and range of biomass quality. Profit decreased by up to 23% when there was +/- 13% variation in moisture content and +/- 5% change in higher heating value. The model achieved a biomass purchase cost that was lower than the current commercial costs at the power plant. Implementing the model could prevent production curtailment and undesirable fluctuation in storage levels which occurred in the past due to variations in biomass availability and quality. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： Forest-based biomass Uncertainty mixed integer programming model Supply chain optimization Multi-stage stochastic model Robust optimization

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