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Integrated bi-objective project selection and scheduling using Bayesian networks: A risk-based approach

SCIENTIA IRANICA 2019年第6期26卷 3695-3711页

作者： Namazian, A. Yakhchali, S. Haji Rabbani, M. Univ Tehran Coll Engn Dept Ind Engn POB 14155-6619 Tehran Iran

This paper presents a novel formulation for the integrated bi-objective problem of project selection and scheduling. The first objective was to minimize the aggregated risk by evaluating the expected value of schedule delay and the second objective was to maximize the achieved benefit. To evaluate the expected aggregated impacts of risks, an objective function based on the Bayesian Networks was proposed. In the extant mathematical models of the joint problem of project selection and scheduling, projects are selected and scheduled without considering the risk network of the projects indicating the individual and interaction effects of risks impressing the duration of the activities. To solve the model, two solution approaches were developed, one exact and one metaheuristic approach. Goal programming (GP) method was adopted to optimally select and schedule projects. Since the problem was NP-hard (Non-deterministic Polynomial-time), an algorithm combining GP method and Genetic Algorithm (GA) was proposed, hence named GPGA. Finally, the efficiency of the proposed algorithm was assessed not only based on small-size instances, but also by generating and testing representative datasets of larger instances. The results of the computational experiments indicated that it had acceptable performance in handling large-size and more realistic problems. (C) 2019 Sharif University of Technology. All rights reserved.

关键词： Project selection and scheduling Risk analysis Bayesian networks multi-objective programming Genetic algorithm

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Spatio-temporal evolution analysis of land use change and landscape ecological risks in rapidly urbanizing areas based on multi-Situation simulation - a case study of Chengdu Plain

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ECOLOGICAL INDICATORS 2024年 166卷

作者： Wei, Yali Zhou, Peiyun Zhang, Luoqi Zhang, Yan Sichuan Agr Univ Sch Resources Chengdu 611130 Peoples R China

Land use change in emerging nations raises landscape ecological risks (LERS), hastens the deterioration of urban and rural ecosystem services, endangers human well-being, and undermines sustainable development in the face of rapidly increasing urbanization. Here, using the Chengdu Plain as the study area and long time series data from 2000 to 2020, the optimal time span is selected for multi-context spatio-temporal simulation. The land use map of Chengdu Plain in 2025 under the four scenarios of "Natural Development" (ND), "Economic Priority Development" (END), "Ecological Priority Development" (ELD), and "Sustainable Development" (SD) was simulated, and the multi-indicator landscape ecological risk index (ERI) was generated to compare and analyze the differences between land use and landscape ecological risk under different policy preferences. Subsequently, the land use data from 2025 to 2040 were simulated, the landscape ecological risk pattern was mapped, and the spatial and temporal evolution analysis from 2010 to 2040 was conducted to explore the spatial evolution law of land use change and landscape ecological risk. Based on the results, the high ecological risk aggregation areas are prone to appear in END scenarios, whereas medium-ecological risk aggregation areas are more likely to appear in ELD scenarios, and the government should focus its policy on arable land protection. Moreover, the land use pattern of cultivated land surrounding construction land and forested land surrounding cultivated land, caused by the irrational single-core development pattern and the policy of returning farmland to forests, has exacerbated the landscape ecological risk of the Chengdu Plain, constituting a unique landscape ecological risk pattern. It's also important to remember that the Chengdu Plain's less economically developed regions need to focus on the high-quality development of ecological land use. We adopted high-precision simulation methods to simulate the complex land

关键词： Landscape ecological risk multi-contextual simulation Time-space evolution multi-objective programming PLUS model

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Modelling and solving the airport slot-scheduling problem with multi-objective, multi-level considerations

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TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES 2021年 124卷 102914-102914页

作者： Katsigiannis, Fotios A. Zografos, Konstantinos G. Fairbrother, Jamie Univ Lancaster Ctr Transport & Logist CENT Dept Management Sci Management Sch Lancaster LA1 4YX England

In overly congested airports requests for landing and take-off slots are allocated according to the IATA World Scheduling Guidelines (WSG). A central concept of these guidelines is the prioritization of the satisfaction of the requested slots according to a hierarchy that recognizes historic usage rights of slots. A number of criteria have been proposed in the literature to optimize airport slot allocation decisions. multi-objective programming models have been proposed to investigate the trade-offs of the slot allocation objectives for the same level of the slot hierarchy. However, the literature currently lacks models that can study in a systematic way the trade-offs among the scheduling objectives across all levels of the hierarchy and the airport schedule as a whole. To close the existing literature gap, we are proposing a new tri-objective slot allocation model (TOSAM) that considers total schedule displacement, maximum schedule displacement and demand-based fairness, and we introduce a multi-level, multi-objective algorithm to solve it. We are using real world slot request and airport capacity data to demonstrate the applicability of the proposed approach. Our computational results suggest that the systematic consideration of the interactions among the objectives of the different levels of the slot hierarchy, results to improved schedule-wide slot scheduling performance. In particular, we found that small sacrifices made for the attainment of the scheduling objectives of the upper echelons of the slot hierarchy, result in significant improvements of the schedule-wide objectives.

关键词： Airport slot allocation multi-objective programming Airport demand management Airport scheduling multi-level decision-making

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Joint chance-constrained multi-objective multi-commodity minimum cost network flow problem with copula theory

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COMPUTERS & OPERATIONS RESEARCH 2023年第1期156卷

作者： Khezri, Somayeh Khodayifar, Salman Inst Adv Studies Basic Sci IASBS Dept Math Zanjan *** Iran

This study focuses on a specific problem in network optimization, namely the minimum cost multi-commodity network flow (MCNF) problem. The problem is complicated by the presence of uncertain parameters, including various types of costs associated with each arc in the network. The study presents a multi-objective approach to solving this problem, where the coefficients of the capacity constraints are modelled as random variables with a normal distribution, and the dependence between them is modelled using an Archimedean copula. The capacity constraints are presented as joint chance constraints, and a multi-objective problem is formulated to deal with the uncertainty. This uncertain multi-objective problem is then converted into a certain multi-objective problem using fuzzy programming. The resulting certain multi-objective MCNF problem is converted to a certain single objective problem using second-order cone programming (SOCP), which is solved using either piecewise tangent approximation or piecewise linear approximation methods. The proposed ap- proaches are tested using numerical examples and experimental tests to demonstrate their effectiveness in solving large-scale network problems efficiently. The results show that the proposed approaches are a useful tool for solving uncertain multi-objective MCNF problems in real-world applications.

关键词： Minimum cost network flow problem multi-objective programming Joint chance-constrained optimization Copula theory

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Location selection of agricultural Machinery sheds for improved scheduling and efficiency under sustainability goals

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ECOLOGICAL INDICATORS 2023年 155卷

作者： Liu, Yang Ma, Xu Jiang, Mingjun Huang, Weilun Ren, Haisong Bengbu Univ Sch Econ & Management Bengbu Anhui Peoples R China Wenzhou Business Coll Sch Management Wenzhou Peoples R China Wenzhou Business Coll Sch Finance & Trade Wenzhou Peoples R China

The storage of agricultural machinery (AM) poses a critical operational challenge that requires attention to attain China's "Carbon Peaking and Carbon Neutrality" objectives, due to the carbon emissions and fuel consumption associated with AM operations. Nevertheless, this matter has not garnered adequate consideration. Existing studies have rarely focused on optimizing the parking locations for AM to mitigate emissions and advance sustainability. This study employs the TOPSIS-MCGP method to explore sustainable location selection for Chinese AM sheds. The principal factors influencing location selection include carbon emissions, fuel consumption, operational distance, total cost, and timeliness, which were thoroughly examined for their impact. A weighted selection approach was utilized to ascertain key factors and their optimization implications. The AM shed location within the AM dispatching system was developed through the following steps: (1) Evaluation of influential factors for sustainable AM dispatching, encompassing carbon emissions, fuel consumption rate, AM dispatching distance, cost, and timeliness. (2) Quantification of the manager's experience in the AM service center as an index weight using the Fuzzy Delphi Method (FDM). (3) Adoption of the TOPSIS-MCGP model to establish the relationship between operation points and AM shed locations during sustainable AM operations. A preliminary investigation was carried out in a company located in Harbin City, yielding an optimal solution encompassing a 13,500 mu working area, 3,300 total building area, and a 28-million RMB investment. The outcomes underscore the model's compatibility and its utility for optimizing sustainable AM service operations. In conclusion, this study underscores the significance of addressing AM storage to foster sustainability and emissions reduction. The TOPSIS-MCGP approach proves effective in selecting sustainable AM shed locations. By considering diverse factors like carbon emissions, f

关键词： Agricultural machinery TOPSIS-MCGP Sustainable dispatch Emissions multi-objective programming

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Supply Chain Coordination Under Ramp-Type Price and Effort Induced Demand Considering Revenue Sharing Contract

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ASIA-PACIFIC JOURNAL OF OPERATIONAL RESEARCH 2015年第2期32卷 1550004-1550004页

作者： Saha, Subrata Sarmah, S. P. Inst Engn & Management Dept Math Kolkata 700091 W Bengal India Indian Inst Technol Dept Ind & Syst Engn Kharagpur 721302 W Bengal India

In this paper, a revenue sharing contract is designed to coordinate a distribution channel where the demand of the product is ramp-type price and effort sensitive. It is shown that traditional revenue sharing contract does not coordinate the system. As an alternative, two new mechanisms are proposed (i) revenue sharing with coordinated effort of the retailer alone and (ii) both revenue and effort sharing contract. In addition, a crucial modification of revenue sharing fraction is also proposed. To enhance the applicability of revenue sharing contract, the contract parameters are determined by using bi-level multi-objective fuzzy goal programming technique where manufacturer sets the wholesale price greater than the marginal cost. Numerical examples are presented to illustrate all the models.

关键词： Supply chain coordination revenue sharing ramp-type demand multi-objective programming

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Self-adaptive metaheuristic-based emissions reduction in a collaborative vehicle routing problem

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SUSTAINABLE CITIES AND SOCIETY 2024年 110卷

作者： Kahalimoghadam, Masoud Thompson, Russell G. Rajabifard, Abbas Univ Melbourne Fac Engn & IT Dept Infrastruct Engn Parkville Australia

Global climate change-related initiatives such as the 2015 Paris Agreement have highlighted the necessity of sustainable transportation. Nevertheless, the rapid growth of e-commerce has notably escalated vehicle kilometres travelled (VKT) and CO2 emissions within cities, posing a direct challenge to sustainability initiatives. To address these challenges, this study formulates a collaborative multi-depot green vehicle routing problem. This model utilises micro-consolidation centres (MCCs) as shared hubs alongside a microscopic approach linking emission rates to vehicle and route characteristics, in order to assess MCCs' effectiveness in reducing CO2 emissions. Introduced here is an innovative self-adaptive metaheuristic algorithm hybridising intelligent water drops and simulated annealing. This methodology differs from established approaches by incorporating a feedback control system that actively monitors the algorithm's performance and convergence towards the global minimum solution. Through continuous adjustments to algorithm parameters via a feedback loop, this methodology strikes a balance between exploitation and exploration. The algorithm is tested in a context-specific approach, first applying it to the Cordeau benchmark and comparing it with previous state-of-the-arts, followed by a case study comparing the collaborative network to an independent one. This approach achieves 43 % and 25 % reductions in VKT and emissions, respectively, enhancing urban logistics networks' efficiency and sustainability.

关键词： MDVRP multi-objective programming Network distribution design Hybrid metaheuristics algorithm Comprehensive Modal Emission Model Knowledge-based systems

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Improving the AquaCrop model to achieve direct simulation of evapotranspiration under nitrogen stress and joint simulation-optimization of irrigation and fertilizer schedules

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AGRICULTURAL WATER MANAGEMENT 2022年第0期266卷

作者： Wu, Hui Yue, Qiong Guo, Ping Xu, Xiaoyu Huang, Xi China Agr Univ Ctr Agr Water Res China Beijing 100083 Peoples R China Res Stn Efficient Water Use Oasis Agr Wuwei Gansu Natl Field Sci Observat Wuwei 733000 Gansu Peoples R China

Water and fertilizer management strategy profoundly influences crop yield, water and nitrogen use efficiency. In this study, a framework for joint simulation-optimization of irrigation and fertilizer schedules (JSOIFS) was established by coupling the improved AquaCrop model, W*N-Jensen model and multi-objective programming. Firstly, the AquaCrop model was modified to simulate evapotranspiration (ET) under nitrogen stress through introducing the concept of shoot actual, critical and minimal nitrogen concentration. The accuracy and applicability of the improved AquaCrop model to simulate ET were verified, taking seed maize of Shiyanghe River Basin as a case. On the basis, an optimization model with the objective of maximum yield calculated by W*NJensen model and water use efficiency was developed under the scenarios of different levels of available water and nitrogen, and initial soil mineral nitrogen content. Results showed that the improved model can simulate canopy cover (CC) and ET well with and without water stress. Meanwhile, the precision for CC, biomass, ET and yield of seed maize can be guaranteed when water and nitrogen stress coexist. It indicated that the improved model can be used for irrigation and fertilizer management. The optimal irrigation and fertilizer schedules pointed out that the irrigation and nitrogen application, and initial soil mineral nitrogen all have significant effects on yield. In low fertility soils, irrigation should be concentrated during tasseling stage and fertilization is as critical as irrigation. Conversely, in high fertility soils, irrigation should be dispersed throughout the growth period. Water and nitrogen use efficiency have been promoted compared with the status quo. The recommended water and nitrogen application for seed maize are 150-200 mm and 100-150 kg N/ha, respectively, in study area with the mean soil mineral nitrogen of 182 kg N/ha. The improvement of ET simulation performance of AquaCrop model under simultaneou

关键词： Optimization Irrigation and fertilizer management AquaCrop multi-objective programming

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Efficient and equitable irrigation management: A fuzzy multi-objective optimization model integrating water movement processes

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JOURNAL OF ENVIRONMENTAL MANAGEMENT 2024年 371卷 123164页

作者： Chang, Hong Li, Gang Zhang, Chenglong Huo, Zailin China Agr Univ Ctr Agr Water Res China Beijing 100083 Peoples R China China Agr Univ State Key Lab Efficient Utilizat Agr Water Resourc Beijing 100083 Peoples R China

This study presents a robust multi-objective model for optimizing irrigation water allocation to balance economic benefits, water equity and irrigation efficiency in irrigation decisions under uncertainty. Daily water movement among irrigation, soil, groundwater, and drainage is modeled through water balance simulation and integrated into an optimization model considering economic, social, and resource objectives. To effectively manage conflicts arising from multiple objectives under uncertainty, interval multi-objective programming and fuzzyboundary interval programming are employed. Here, interactive algorithms are used to align constraint feasibility with objective satisfaction to generate optimal solutions for irrigation water allocation. The model's applicability is demonstrated within the Hetao Irrigation District, addressing the rising conflicts between irrigation water supply and demand. The optimization model aims to maximize net economic benefits, minimize Gini coefficient and the proportion of blue water utilization in irrigation water, incorporating daily soil water and groundwater movement processes. By setting five feasibility levels, optimal water allocation solutions are derived for five irrigation subareas and three crops across their entire growth periods. The results analysis shows that an increased feasibility level makes the uncertainty range of the objective values decrease while lower feasibility levels lead to higher satisfaction with the objective values. Moreover, it is found that the decision satisfaction peaks at a feasibility level of 0.9 after balancing feasibility and objective satisfaction, aligning more closely with the decision maker's expectations. At this level, the economic benefit is [3.62, 13.60] x 109 Yuan. Compared to a feasibility level of 1.0, the average range of the economic benefits increases by 122.50 x 106 Yuan, and the Gini coefficient decreases from [0.7973, 0.7997] to [0.7963, 0.7996]. Therefore, the above results c

关键词： multi-objective programming Irrigation planning Physical processes Interactive fuzzy programming Uncertainty Decision-making

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An integrated two dimensional cutting stock and lot sizing problem with two criteria

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EUROPEAN JOURNAL OF INDUSTRIAL ENGINEERING 2023年第5期17卷 766-+页

作者： Sanan, Ayse Burcu Azizoglu, Meral METU Dept IE TR-06800 Ankara Turkiye

In this study, we consider an integrated two dimensional cutting stock and lot sizing problem arising in an aircraft manufacturing plant. The items are to be cut from steel panels of identical size to satisfy all periodic demands over a specified planning horizon. Two objectives, minimising the number of panels cut and the total inventory carrying cost of the items, are defined and all non-dominated objective vectors concerning the defined objectives are generated. To generate each non-dominated objective vector, we propose a mixed integer linear programming model whose efficiency is improved by optimality properties and bounding mechanisms. The results of our experiments have revealed that the instances with few items can be solved for up to 14 periods and the instances with more items can be solved for up to seven periods, in two hours. [Submitted: 29 March 2022;Accepted: 7 August 2022]

关键词： two dimensional cutting stock problems 2DCSPs lot sizing problems integrated problems multi-objective programming

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