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Primary logistics planning of oil products under the imbalance of supply and demand

Petroleum Science 2022年第4期19卷 1915-1925页

作者： Rui Qiu Yong-Tu Liang Qi Liao Ying-Qi Jiao Bo-Hong Wang Yi Guo Hao-Ran Zhang National Engineering Laboratory for Pipeline Safety/Beijing Key Laboratory of Urban Oil and Gas Distribution Technology China University of Petroleum-BeijingFuxue Road No.18Changping DistrictBeijing102249PR China School of Petrochemical Engineering and Environment Zhejiang Ocean UniversityZhoushan316022China Sustainable Process Integration Laboratory–SPIL NETME CentreFaculty of Mechanical EngineeringBrno University of Technology–VUT BrnoTechnická2896/261669BrnoCzech Republic Oil&Gas Pipeline Control Center PipeChinaDongtucheng Road No.5Chaoyang DistrictBeijing100013PR China Center for Spatial Information Science The University of Tokyo5-1-5 KashiwanohaKashiwa-shiChiba277-8568Japan

This paper intends to complete the primary logistics planning of oil products under the imbalance of supply and demand. An integrated mathematical programming model is developed to simultaneously find the balance between supply and demand, and optimize the logistics scheme. The model takes minimum logistics cost and resource adjustment cost as the objective function, and takes supply and demand capacity, transportation capacity, mass balance, and resource adjustment rules as *** adjustment rules are considered in the model, including resource adjustment within oil suppliers,within oil consumers, and between oil consumers. The model is tested on a large-scale primary logistics of a state-owned petroleum enterprise, involving 37 affiliated refineries, 31 procurement departments,286 market depots and dedicated consumers. After the unified optimization, the supply and demand imbalance is eased by 97% and the total cost is saved by 7%, which proves the effectiveness and applicability of the proposed model.

关键词： Oil product logistics Supply and demand imbalance Petroleum enterprise Resource adjustment mathematical programming model

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Optimal project portfolio selection with reinvestment strategy considering sustainability in an uncertain environment: a multi-objective optimization approach

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KYBERNETES 2022年第8期51卷 2437-2460页

作者： Zarjou, Mohammadali Khalilzadeh, Mohammad Islamic Azad Univ Sci & Res Branch Dept Ind Engn Tehran Iran CENTRUM Catolica Grad Business Sch Lima Peru Pontificia Univ Catolica Peru Lima Peru

Purpose This study aims to develop a model for project portfolio selection considering organizational goals such as budgets, sustainability cash flow and reinvestment strategy under an uncertain environment. Design/methodology/approach A multi-objective mathematical programming model is proposed for project selection, which takes the social, environmental and financial aspects into account as the objectives of the project portfolio selection problem. The project evaluation and selection process in one of the large capitals in the Middle East with numerous urban construction projects was considered as a real case study, in which the subjects of environmental and social sustainability are of great importance. Then, the most significant criteria for project evaluation and selection based on sustainability were identified and ranked using the fuzzy best-worst method (BWM). Findings The criterion of "defining clear and real objectives" was ranked first, "project investment return period" was ranked second, "minimum changes in the predicted range" was ranked third, and the other ten sustainability indicators were ranked as well. Next, the presented mathematical programming model was solved using the augmented e-constraint method. The sensitivity analysis indicated that increasing the amount of investments in projects would increase their net present value. Also, increased investment had no effect on sustainability, while decreased investment caused sustainability to not being optimal. Originality/value This study focuses on the impact of the amount of investments on projects, and the associated costs of sustainable projects. Further to the authors' knowledge, there has been no relevant study taking uncertainty into account. Also, very few studies proposed a mathematical programming model for the project portfolio selection problem. Moreover, this research uses the brainstorming and Delphi method to identify the sustainability indicators influencing the organization and sc

关键词： Project portfolio selection Sustainability mathematical programming model Fuzzy BWM Reinvestment strategy Construction projects

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Optimal site selection for wind energy: a case study

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ENERGY SOURCES PART A-RECOVERY UTILIZATION AND ENVIRONMENTAL EFFECTS 2022年第3期44卷 6660-6677页

作者： Derse, Onur Yilmaz, Ebru Tarsus Univ Dept Management & Org Logist TR-33400 Tarsus Mersin Turkey Cukurova Univ Fac Engn Dept Ind Engn Adana Turkey

Renewable energy sources (RES) have gained attraction in recent years. The optimal site selection problem is one of the most important problems in the area of RES. In this study, the optimum site selection problem for wind energy, which is one of the RES types, is discussed. Eighty-one provinces in Turkey are evaluated using the Pareto diagram and the provinces with high potential wind energy are obtained. Long-term electricity consumption estimates are performed for the 13 provinces using ARIMA and Time Series Analysis methods. Also, in the article, an integrated optimum site selection problem in GAMS 23.5 software is modeled by the predicted future energy demand. As a result of the study, the total 41 installation decisions are made for the strategic optimal site selection decision between 2021 and 2025 years. Minimizing the total cost proposed as an objective function of the developed mathematical programming model, the total cost is found as 52526500 currency unit. It is seen that the decision to install the power plant is mostly made for Balikesir, canakkale and Izmir, and the number of plants for the provinces are 6, 6 and 5, respectively. The computational results show that the developed model produces effective solutions and minimizes the total cost by focusing on strategic optimal site decisions. According to the sensitivity analysis results, increasing the percentage of use in wind energy approximately 4-5% from 3.5% in total percentage will reduce the total cost by approximately 3.62%.

关键词： Renewable energy sources wind energy mathematical programming model prediction methods optimal site selection

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Identification and selection of stakeholder engagement strategies: case study of an Iranian oil and gas construction project

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INTERNATIONAL JOURNAL OF CONSTRUCTION MANAGEMENT 2023年第3期23卷 484-494页

作者： Khalilzadeh, Mohammad Kebriyaii, Omid Rezaei, Raman CENTRUM Catolica Grad Business Sch Lima Peru Pontificia Univ Catolica Peru Lima Peru Iran Univ Sci & Technol Dept Ind Engn Tehran Iran Islamic Azad Univ Sci & Res Branch Dept Ind Engn Tehran Iran

Despite emphasizing the great importance of stakeholder management, there is a gap in applying a decision support system to adopt sustainable strategies for stakeholder engagement and conflict resolution especially in oil and gas projects. This paper presents a new framework for adopting the strategies in one of the largest oil and gas projects in Iran. In this proposed framework, firstly, the hybrid SWOT analysis and fuzzy Delphi method are used to identify and rank the sustainable stakeholder engagement strategies for managing conflicts. Then, a mathematical programming model was proposed to select the optimal strategies to maximize stakeholder engagement. The findings indicate that the results of the hybrid SWOT analysis and fuzzy Delphi method and the mathematical programming model are the same and the high ranked strategies obtained by the hybrid SWOT analysis and fuzzy Delphi method are selected in the proposed mathematical programming model as well. Also, each selected strategy can cover more than one conflict and improve stakeholder engagement.

关键词： Stakeholder engagement strategy selection SWOT analysis fuzzy Delphi method mathematical programming model oil and gas project sustainability

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Curbing methane emissions from Italian cattle farms. An agroeconomic modelling simulation of alternative policy tools

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JOURNAL OF ENVIRONMENTAL MANAGEMENT 2024年 351卷 119880页

作者： Coderoni, Silvia Dell'Unto, Davide Cortignani, Raffaele Univ Teramo Dept Biosci & Agr & Environm Technol Teramo Italy Univ Tuscia Dept Agr & Forest Sci Viterbo Italy Univ Tuscia Dept Agr & Forest Sci DAFNE Via San Camillo De Lellis I-01100 Viterbo Italy

Methane (CH4) emissions from cattle farms have been prioritised on the EU agenda, as shown by recent legislative initiatives. This study employs a supply-side agroeconomic model that mimics the behaviour of heterogeneous individual farms to simulate the application of alternative economic policy instruments to curb CH4 emissions from Italian cattle farms, as identified by the 2020 Farm Accountancy Data Network survey. Simulations consider increasing levels of a tax on each tonne of CH4 emitted or of a subsidy paid for each tonne of CH4 curbed with respect to the baseline. Individual marginal abatement costs are also derived. Besides, to consider possible technological options to curb emissions, a mitigation strategy is simulated, with different levels of costs and benefits to appraise the potential impacts on the *** reductions in operating income are foreseen, the most substantial in farm types and size classes characterised by lower levels of carbon productivity. The introduction of the mitigation strategy shows that the outcome in terms of mitigation potential, without undermining production level, highly depends on the implementation costs, but can also vary widely due to heterogeneous farms' economic performances. Policy implications are also derived.

关键词： mathematical programming model Livestock sector Methane emissions Economic policy tools Marginal abatement costs

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Design of Man-Machine Cooperative Assembly Line Based on mathematical model and Simulation 21st

Design of Man-Machine Cooperative Assembly Line Based on Mat...

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21st International Conference on Man-Machine-Environment System Engineering (MMESE)

作者： Lai, Chaoan Yao, Jianying South China Univ Technol Sch Business Adm Ind Engn Dept Guangzhou Peoples R China

ISBN: (纸本)9789811659638;9789811659621

By the example of small appliances assembly, we propose the man- machine collaborative assembly line design steps, including: demand analysis, feasibility assessment, product structure analysis and assembly process analysis, assembly line design and improvement. By researching the functions of robot and production line respectively, the mathematical programming model of assembly line was constructed and combined with simulation technology to simulate a production process, analyzing the rationality of the assembly structure and improving the production line. Simultaneously, it's important to evaluate and verify the improved production efficiency and balance rate continuously that can improve production and design efficiency and reduce equipment idle time.

关键词： Assembly line Robot System simulation mathematical programming model

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The impacts of environmental and climate targets on agriculture: Policy options in Italy

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JOURNAL OF POLICY modelING 2022年第6期44卷 1095-1112页

作者： Cortignani, R. Coderoni, S. Univ Tuscia Dept Agr & Forest Sci Viterbo Italy Univ Teramo Dept Biosci & Environm & Agri Food Technol Teramo Italy

This study is aimed at proposing a model to assess the economic private costs for farms deriving from the implementation of some of the environmental targets set by the European Farm to Fork strategy and the objective of a carbon-neutral agricultural sector, by also evaluating the synergies and trade-offs between environmental objectives. An agro-economic supply model, based on mathematical programming and microdata from the Farm Accountancy Data Network, is used. The model is applied to Italian agriculture as a case study. Results show losses in added value, higher level of resource efficiency and synergies among different targets. Policy implications include exploiting the synergies and accompanying the transition with measures aimed at compensating the most impacted sectors.(c) 2022 The Society for Policy modeling. Published by Elsevier Inc. All rights reserved.

关键词： GHG emissions Agricultural income mathematical programming model Input use Farm to Fork

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Practicable total-site heat integration plan for retrofitting multiple heat exchanger networks

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CHEMICAL ENGINEERING RESEARCH & DESIGN 2021年 174卷 137-157页

作者： Lo, Fang-Yi Hsu, Ching-Hsiang Chang, Chuei-Tin Natl Cheng Kung Univ Dept Chem Engn Tainan 70101 Taiwan

Total-site heat integration (TSHI) is one of effective ways to improve energy efficiency for the process industry. Generally, the existing chemical plants in an industrial park were rarely constructed simultaneously and it is highly possible that each has already been equipped with an optimal heat exchanger network (HEN) at the time when its construction is completed. To further improve the overall performance of the entire site, a novel retrofit design strategy of these HENs is developed in this study using intermediate fluid(s). A two-stage procedure has been adopted to produce a practicable retrofitting plan. Three different revamp strategies are proposed in this work, while any of them can be applied to generate the costoptimal designs first via indirect interplant heat exchanges. The benefit allocation schemes are then determined according to core and Shapley values in the second stage. The feasibility and effectiveness of proposed methodology are demonstrated in detail with a three-plant example. It is also plain to observe from the corresponding results that the applicability of the aforementioned design strategy is practicable in realistic environment. (c) 2021 Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved.

关键词： Indirect interplant heat integration Retrofit design mathematical programming model Cooperative game Core Shapley value

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Consistency- and Consensus-Based Group Decision-Making Method With Incomplete Probabilistic Linguistic Preference Relations

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IEEE TRANSACTIONS ON FUZZY SYSTEMS 2021年第9期29卷 2565-2579页

作者： Liu, Peide Wang, Peng Pedrycz, Witold Shandong Univ Finance & Econ Sch Management Sci & Engn Jinan 250014 Peoples R China Univ Alberta Dept Elect & Comp Engn Edmonton AB T6G 2R3 Canada

The use of incomplete probabilistic linguistic term sets (InPLTSs) can enrich the flexibility of qualitative decision-making information expression, especially in decision-making situations with high time pressure and insufficient knowledge. In this article, we develop a method for group decision-making (GDM) with incomplete probabilistic linguistic preference relations (InPLPRs), considering consistency and consensus simultaneously. First, to fully explore the ability of InPLTSs to express uncertain information, InPLTSs are specifically classified. Then, an expected multiplicative consistency of InPLPRs is introduced, which is conducive to estimating the missing information more accurately and effectively. Subsequently, considering the consensus of GDM problems, a consensus index, which considers the principle of majority and minority, is developed to measure the agreement degree among multiple individuals. Because individual InPLPRs may not all meet acceptable consistency after reaching consensus, a consistency- and consensus-improving mathematical programming model considering information distortion is presented. Then, to aggregate all individual preference relations into a collective one, a reliability-induced ordered weighted geometric operator is introduced, whose induced variable reliability is determined by the confidence degree and consistency index of individual preference relations. Furthermore, a multiphase algorithm with InPLPRs is developed to solve GDM problems. Finally, a numerical example of fire emergency decisions is presented to illustrate the applicability of the proposed method, and a detailed validity test and comparative analysis are conducted to highlight the advantages of the proposed method.

关键词： Linguistics Decision making Probabilistic logic Reliability mathematical model Optimization Indexes Consensus expected multiplicative consistency group decision-making (GDM) incomplete probabilistic linguistic preference relation (InPLPRs) induced ordered weighted geometric operator mathematical programming model

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Parallel machine scheduling with multiple processing alternatives and sequence-dependent setup times

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INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 2021年第18期59卷 5438-5453页

作者： Kim, Jun Kim, Hyun-Jung Korea Inst Ind Technol Proc Platform Res Div Ansan South Korea Korea Adv Inst Sci & Technol Dept Ind & Syst Engn 291 Daehak Ro Daejeon 34141 South Korea

This paper examines a parallel machine scheduling problem in which jobs can be processed either in multiple parts or in a complete form and the number of possible job splitting alternatives of jobs is more than one. There are sequence-dependent setup times between different jobs (or parts), and the objective is to minimise makespan by choosing an appropriate processing alternative for each job, assigning parts (or jobs) to machines, and determining the sequence of parts on the machines. This work is motivated from a 3D printer-based manufacturing system that produces customised products for individuals or start-up companies. When 3D printers are used as processing machines, a product can be printed in diverse forms composed of different parts. To address the problem, we first propose a mixed integer programming model and then develop a hybrid genetic algorithm which is combined with a travelling salesman problem-based heuristic algorithm. The experimental results show that the average gap between a solution from the proposed algorithm and an optimal one solved with CPLEX or a lower bound is very small. The paired t-test shows that there is a significant improvement for processing jobs with multiple alternatives.

关键词： 3D printing scheduling minimisation of makespan mathematical programming model sequence-dependent setup time hybrid genetic algorithm

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