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Evaluation of the Trade-Off between Ground Delays and Intersecting Departures under Various Pilot Acceptance Rate Scenarios

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TRANSPORTATION RESEARCH RECORD 2023年第7期2677卷 733-746页

作者： Donmez, Kadir Samsun Univ Aircraft Maintenance Dept Samsun Turkiye

The increasing demand for air traffic at airports necessitates the efficient utilization of ground facilities such as runways and taxiways. Intersecting departures, in which one or more aircraft take off from intersecting points on the runway, is a commonly used approach to increase runway capacity and reduce ground delays and taxi times, as well as noise and air pollution. However, the procedure carries potential risks such as runway incursion and excursion. This creates a trade-off between minimizing the number of intersecting departures and minimizing ground delays. In practice, the decision to perform an intersecting departure is ultimately up to the pilot, resulting in uncertainty in the acceptance rate of these types of takeoffs. In this study, a departure sequencing model was developed for a single-runway airport that considers intersecting departures and various pilot acceptance rate scenarios. The primary objective of the model is to minimize total ground delay, including taxi delays, runway holds, and conflict holds. The secondary objective is to minimize the number of intersecting departures by directing the most operationally critical aircraft to the intersection takeoff. The epsilon constraint method-a multi-objective scalarization method-was used to reveal the trade-offs between the objective functions. The results of the model were compared with a traditional scenario that only allows take offs from the beginning of the runway. As a result, average delay savings ranged from 17.1% to 31.5% in various acceptance rate scenarios, as well as average taxi time savings ranging from 4.9% to 8.4% compared with the traditional scenario.

关键词： departure sequencing intersection takeoff multi-objective programming pilot acceptance uncertainty delay minimization

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A multiple objective Hybrid Algorithm for Daily Ore Blend in Oil Sands Mines

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INTERNATIONAL JOURNAL OF MINING RECLAMATION AND ENVIRONMENT 2023年第9期37卷 667-682页

作者： Nikbin, Vahid Afrapoli, Ali Moradi Univ Zanjan Fac Engn Min Grp Zanjan Iran Laval Univ Dept Min Met & Mat Engn Quebec City PQ Canada Laval Univ Dept Min Met & Mat Engn 1065 Ave Med Adrien Pouliot Pavillon QC 1745-E Quebec City PQ Canada

Oil sands mining contributes to the Canadian daily oil production by producing 1.617 million barrels per day. Processing oil sands is a complex operation with a critical sensitivity to the properties of the blended ore at the crusher that must follow the slurry pipeline and separation tank requirements. The blend optimisation in oil sands mines is a tedious work performed mostly manually by the mining engineers at the mine sites and requires fine-tuning as shovels move from one block to another in the same mining face. Miscalculations leading to deviation from the target properties cause inevitable economically and operationally expensive issues to the value chain including but not limited to sanding the pipeline, separation tank hick-ups, etc. Herein, we present a hybrid multi-objective algorithm addressing abovementioned issues in daily blending process and providing the operation crew with a clear practical production target at each mining face. The algorithm takes the processing targets as inputs and minimises deviations from each desired target by considering material properties at mining faces, the capacity of trucks, and production rates of active shovels.

关键词： Mining oil sands optimization blending multi-objective programming

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HRFF: Hierarchical and Recursive Floorplanning Framework for NoC-Based Scalable multi-Die FPGAs

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS 2023年第11期70卷 4295-4308页

作者： Luo, Jianwen Liu, Xinzhe Chen, Fupeng Ha, Yajun ShanghaiTech Univ Sch Informat Sci & Technol Shanghai 201210 Peoples R China Chinese Acad Sci Shanghai Inst Microsyst & Informat Technol Shanghai 200050 Peoples R China Univ Chinese Acad Sci Sch Elect Elect & Commun Engn Beijing 101408 Peoples R China Synopsys VCS Constraint Team Shanghai 200065 Peoples R China Shanghai Engn Res Ctr Energy Efficient & Custom AI Shanghai 201210 Peoples R China

Emerging applications are calling for significantly larger FPGAs with multi-dies. However, the interconnection architecture of existing FPGAs lacks scalability. The execution time and failure probability of their RTL-to-Silicon process increase dramatically with the growth of design and the number of dies. To address this issue, we propose both an NoC-based scalable multi-die FPGA architecture and a corresponding floorplanning framework, namely Hierarchical and Recursive Floorplanning Framework (HRFF). First, from the architecture side, we introduce an interconnection architecture with a class of scalable hierarchical topology. Second, for the algorithm side, we formulate the generic floorplanning problem for NoC-based architectures as a multi-objective Mixed Integer Linear programming (MILP) problem, balancing the design timing and interconnection workload. Third, we develop a novel recursive approximate method to efficiently solve the multi-objective MILP formulation over the proposed architecture, with a configurable trade-off between solution quality and solver run time. Experimental results show that the scalability of our proposed technique is at least 1.5x on all and 3x on certain benchmarks as that of the state-of-the-art solutions with no loss of design throughput.

关键词： NoC-Based multi-die FPGA floorplanning framework mixed integer linear programming multi-objective programming convolutional neural network

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OPTIMIZATION OF A LINEAR FUNCTION OVER AN INTEGER EFFICIENT SET

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JOURNAL OF INDUSTRIAL AND MANAGEMENT OPTIMIZATION 2023年第12期19卷 8633-8656页

作者： Pherna Sharma, Vikas Thapar Inst Engn & Technol Sch Math Patiala India

Optimizing a function over an efficient set is an interesting approach in decision-making situations. It helps a decision-maker to discriminate among efficient solutions and choose his preferred solution. In this paper, ranked solutions of an integer linear programming problem are utilized for optimizing a linear function over an efficient set of a multi-objective integer linear programming problem (MOILP). For enumerating ranked solutions of an integer linear programming problem, successive optimization of an integer linear programming problem is used. Theoretically, we have shown that the proposed algorithms optimize a linear function over an efficient set of a MOILP in a finite number of iterations. We have compared the working of proposed algorithms with existing algorithms using a numerical example taken from the literature. We have also included a comparison with existing methods based on computational experiments using large number of variables and objectives.

关键词： multi-objective programming integer programming efficient set

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SOLVING DISCRETE LINEAR FRACTIONAL BILEVEL PROGRAMS WITH multiPLE objectiveS AT THE UPPER LEVEL

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JOURNAL OF INDUSTRIAL AND MANAGEMENT OPTIMIZATION 2023年第4期19卷 2639-2654页

作者： Fali, Fatima Moulai, Mustapha USTHB Dept Operat Res BP 32 El Alia Algiers 16111 Algeria

This paper proposes an exact method to solve an integer linear fractional bilevel problem with multiple objectives at the upper level, designated by IFMOBP. The proposed algorithm generates a set of efficient solutions using a branch and cut algorithm based on a continuous upper level linear fractional problem. Then, the integer optimal solution obtained is tested for optimality of the lower level problem. First, the integer optimal solution of the bilevel problem is sought with a single objective function at each level. After that, an efficient cut is added and new integer solutions are determined. The efficient set is updated each time a candidate bilevel feasible solution non dominated is got and the process ends when there are no unexplored parts of the original domain. The proposed method is based on a dantzig cut to find the next best integer solution of the first objective function of the upper level, an efficient cut to get the set of efficient solutions for the main problem, and the classical branch and bound technique for integer decision variables. After the presentation of the algorithm, a numerical example and computational experiments are provided.

关键词： multi-objective programming bilevel programming integer programming linear fractional programming branch and cut

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Evaluation of the performance of the multi-objective scalarization methods for the aircraft sequencing and scheduling problem using multi-criteria decision-making

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AIRCRAFT ENGINEERING AND AEROSPACE TECHNOLOGY 2023年第4期95卷 501-511页

作者： Donmez, Kadir Samsun Univ Dept Air Traff Control Samsun Turkey

Purpose This study aims to evaluate the performance of the most popular multi-objective programming scalarization methods in the literature for the aircraft sequencing and scheduling problem (ASSP). These methods are the weighted sum method, weighted goal programming, the epsilon-constraint method, the elastic constraint method, weighted Tchebycheff and augmented weighted Tchebycheff. Design/methodology/approach First, the ASSP for a single runway case was modeled using mixed-integer programming considering the safety and operational constraints and the objectives of the minimization of total delay and total flight time for a sample airport. The objectives were then combined by using the multi-objective programming scalarization methods and various expected times of arrival-departure samples were run for the mathematical models. Finally, the methods were evaluated in terms of the number of nondominated solutions, superior nondominated solution and the average solution time using the Measurement of Alternatives and Ranking according to Compromise Solution method, which is a popular multi-criteria decision-making method. Findings Augmented Weighted Tchebycheff was found to be the most effective approach to ASSP in terms of the evaluation criteria followed by Weighted Tchebycheff and then weighted sum method. Practical implications The methodology presented in this study could provide more efficient air traffic management in terminal maneuvering areas when multiple objectives need to be optimized. Originality/value Although there are studies including the comparison of several scalarization methods for other problems, the comparison of the methods for ASSP has not yet been handled in the literature. As there are several stakeholders in the air traffic system, ASSP includes several objectives, and as a result, this problem can benefit from analyses using this comparison.

关键词： Aircraft sequencing and scheduling problem multi-objective scalarization methods multi-criteria decision-making Mixed-integer programming multi-objective programming

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An integrated fuzzy-grey relational analysis approach to portfolio optimization

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APPLIED INTELLIGENCE 2023年第4期53卷 3804-3835页

作者： Mehlawat, Mukesh Kumar Gupta, Pankaj Khan, Ahmad Zaman Univ Delhi Dept Operat Res New Delhi 110007 India Flat 01 Kamayani Kunj Apartment Delhi 110092 India

This paper combines two approaches (Fuzzy set theory and Grey Relational Analysis) for modelling an investor's imprecise linguistic expectations and the uncertain returns of assets. We propose a novel maximization-type risk measure capable of incorporating the investor's individual preferences. The investor provides the expectations of what is considered the "ideal" return from the portfolio. We use Credibility theory to capture the investors' subjective and imprecise expectations in a precise mathematical form. We construct a portfolio return sequence using the assets' actual return data and an ideal sequence based on investors' preferences. Subsequently, we calculate the Grey similitude and the closeness incidence degree between the two sequences. The closer the portfolio return is to the ideal return, the better. In this manner, we develop a new risk measure that can quantify an investor's perception of risk. This measure is intuitive and easy to calculate. It does not involve estimating many parameters, something which would increase the estimation risk. We use a genetic algorithm to solve the resulting portfolio optimization model. We illustrate this method with two case studies: (i) a case study of 100 assets of the U.S. stock market's NASDAQ-100 index and (ii) a case study of 50 assets of the Indian stock market's NIFTY-50 index. We comprehensively analyze the model's out-of-sample performance and discuss its implications. The portfolios obtained using the proposed approach exhibit healthy growth outside the in-sample period. We also compare the out-of-sample performance of the proposed model with several approaches in the literature to establish its superiority.

关键词： Portfolio optimization Credibility theory Grey incidence analysis multi-objective programming Fuzzy set theory Genetic algorithm

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Two-stage stochastic formulation for relief operations with multiple agencies in simultaneous disasters

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OR SPECTRUM 2023年第2期45卷 477-523页

作者： Rodriguez-Espindola, Oscar Aston Univ Aston Business Sch Birmingham W Midlands England

The increasing damage caused by disasters is a major challenge for disaster management authorities, especially in instances where simultaneous disasters affect different geographical areas. The uncertainty and chaotic conditions caused by these situations combined with the inherent complexity of collaboration between multiple stakeholders complicates delivering support for disaster victims. Decisions related to facility location, procurement, stock prepositioning and relief distribution are essential to ensure the provision of relief for these victims. There is a need to provide analytical models that can support integrated decision-making in settings with uncertainty caused by simultaneous disasters. However, there are no formulations tackling these decisions combining multiple suppliers, multiple agencies, and simultaneous disasters. This article introduces a novel bi-objective two-stage stochastic formulation for disaster preparedness and immediate response considering the interaction of multiple stakeholders in uncertain environments caused by the occurrence of simultaneous disasters. At the first stage, decisions related to the selection of suppliers, critical facilities, agencies involved, and pre-disaster procurement are defined. Resource allocation, relief distribution and procurement of extra resources after the events are decided at the second stage. The model was tested on data from the situation caused by simultaneous hurricanes and storms in Mexico during September of 2013. The case is contrasted with instances planning for disasters independently. The results show how planning for multiple disasters can help understand the real boundaries of the disaster response system, the benefits of integrated decision-making, the impact of deploying only the agencies required, and the criticality of considering human resources in disaster planning.

关键词： Humanitarian logistics multi-objective programming Procurement Simultaneous disasters Disaster preparedness

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Integrated multi-objective stochastic fuzzy programming and AHP method for agricultural water and land optimization allocation under multiple uncertainties

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JOURNAL OF CLEANER PRODUCTION 2019年 210卷 12-24页

作者： Ren, Chongfeng Li, Zhehao Zhang, Hongbo Minist Educ Key Lab Subsurface Hydrol & Ecol Effect Arid Reg Xian Shaanxi Peoples R China Changan Univ Sch Environm Sci & Engn YantaSt 126 Xian 710054 Shaanxi Peoples R China

Optimization allocation of agricultural water and land is a very complex system involves multiple objectives. Moreover, weights of each objective were signed by subjective judgement of decision makers is unreasonable. Furthermore, uncertainties are inevitable in the optimization allocation of irrigation water and land. In order to solve the above problems, this paper developed an improved multi-objective stochastic fuzzy programming method. The developed model was then applied to a case study in Wuwei City, Gansu Province, China. Maximum net benefit, maximum agricultural water productivity, and minimum irrigation area were regarded as planning objectives. A series of optimal irrigation and planting structure schemes were obtained under multiple uncertainties. From the results, water resources shortage in Wuwei city is very severely and it could not satisfy Wuwei's water demand even if the risk probability P-i reaches 0.25. Moreover, water and irrigation area would vary in different crops. Such changes would mainly take place in potato, vegetable and cucurbit, which have the same characteristics with higher yield, lower cost or lower irrigation quota than other crops. Furthermore, the decision makers could make reasonable decisions on the optimal use of irrigation water and land resources under multiple objective and uncertainties based on the obtained results. (C) 2018 Published by Elsevier Ltd.

关键词： Irrigation water optimal allocation multi-objective programming Analytic hierarchy process method Chance-constrained programming Fuzzy sets multiple uncertainties

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Optimisation of multi-level logistics network for agricultural products under community group buying model

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INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE-OPERATIONS & LOGISTICS 2023年第1期10卷

作者： Li, Chenxing Shi, Xianliang Beijing Jiaotong Univ Sch Econ & Management Beijing 100044 Peoples R China

This paper introduces a rapidly developing new online retail model, community group buying, and proposes a three-level agricultural logistics network optimisation model. Under the community group buysing model, it is necessary to use different types of vehicles for transportation of agricultural products with different temperature control requirements. The study establishes a multi-objective mixed integer programming model with the objectives of shortest transportation time and minimum total cost, taking into account the freshness penalty cost incurred during transport. The multi-objective problem is transformed into a single objective by normalisation and weighting methods. According to the calculation for the actual case, this paper solves the problems of community group buying grid warehouse location, multiple vehicles use strategy, loading capacity, transportation path optimisation and self-pickup station demand allocation. In addition, through sensitivity analysis, the management insights of community group buying enterprises are obtained: (1) The community group buying enterprises should use brokers of the community group buying model to enhance customer stickiness;(2) The enterprises should focus on developing business in less developed regions;(3) The enterprises need to adjust the proportion of time efficiency and logistics costs according to the real situation.

关键词： Community group buying agricultural logistics network multi-objective programming multi-commodity and multi-vehicle freshness penalty

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