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A mix integer programming model and solution approach to determine the optimum machine number in the unrelated parallel machine scheduling problem

JOURNAL OF THE FACULTY OF ENGINEERING AND ARCHITECTURE OF GA...

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JOURNAL OF THE FACULTY OF ENGINEERING AND ARCHITECTURE OF GAZI UNIVERSITY 2022年第1期37卷 329-345页

作者： Sarac, Tugba Tutumlu, Busra Eskisehir Osmangazi Univ Ind Engn Dept TR-26480 Eskisehir Turkey Kutahya Dumlupinar Univ Ind Engn Dept TR-43100 Kutahya Turkey

It is assumed that all machines will be used in studies dealing with parallel machine scheduling problems. However, for some businesses having special processes, where large furnaces with very intense energy consumption are used during commissioning, it can be very critical to complete jobs using the least number of furnaces. In addition, for many businesses, doing their jobs with fewer machines creates opportunities for unused machines to be rented to another company or to accept additional jobs as much as the capacity of idle machines. For this reason, in this study, the assumption that all machines will be used has been removed and a mathematical model has been proposed that will decide both which machines will be used and which jobs will be produced in which order on these machines, for the unrelated parallel machine scheduling problem with sequence and machine dependent setup times and machine eligibility restriction. The objectives of the considered problem are minimizing the number of machines to be used and the completion time of the last job. The objective functions of the proposed multi-objective mathematical model are scalarized using the weighted sum method. In order to show the solution performance of the mathematical model, randomly generated test problems were solved with GAMS / CPLEX. To solve the large problems, a local search algorithm and a genetic algorithm have been proposed due to the lack of feasible solutions with GAMS / CPLEX. In the large-scale problem, when all weight pairs are taken into account, genetic algorithm is more successful than local search algorithm an average of 25.64% in terms of solution quality and 50.31% in terms of time.

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Optimisation models for project selection in asset management: an application to the water sector

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INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH 2024年第5期31卷 2956-2987页

作者： Vilarinho, Hermilio Barbosa, Flavia Novoa, Henriqueta Silva, Jaime Gabriel Yamada, Luciana Camanho, Ana S. Univ Porto Fac Engn R Dr Roberto Frias P-4200465 Porto Portugal Inst Engn Sistemas & Comp Tecnol & Ciencia INESC T R Dr Roberto Frias Porto Portugal Aguas Douro & Paiva Rua Vilar 235 5 Andar P-4050626 Porto Portugal Inst Politecn Porto IPP Inst Super Engn Porto ISEP R Dr Antonio Bernardino Almeida 431 Porto Portugal

A significant challenge in asset management is the selection of investment projects for infrastructures, which often relies on subjective judgement and lacks structured decision support methods. This challenge is particularly complex in water systems due to the diverse and heterogeneous nature of the components requiring investment. While the infrastructure value index (IVI) is widely used to characterise assets and support investment decisions in the water sector, its application in optimisation models for generating efficient project portfolios remains unexplored. To address this research gap, this study introduces optimisation models for generating investment portfolio plans in water systems' asset management. The proposed approach includes two mixed-integer linear programming (MILP) models that determine optimal solutions and an evolutionary algorithm that offers sub-optimal alternative investment selection plans to provide decision-makers with additional choices for balancing optimal outcomes. The primary contribution of this research is the combined utilisation of MILP and evolutionary algorithms, integrating the IVI into the decision-making process. These tools provide decision-makers with structured methods for defining investment plans and minimising the subjective elements typically associated with such processes. To illustrate the effectiveness of the models, a case study is presented involving a pumping station of a Portuguese water company. The results demonstrate the practical application and benefits of the proposed approach in optimising investment decisions. This research contributes to advancing asset management practices by integrating quantitative optimisation techniques and leveraging the IVI, thereby enhancing the objectivity and efficiency of investment planning in water systems' asset management.

关键词： asset management capital investment planning project selection performance indicator mixed-integer linear programming multi-objective programming

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A multi-stage quantitative resilience analysis and optimization framework considering dynamic decisions for urban infrastructure systems

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RELIABILITY ENGINEERING & SYSTEM SAFETY 2024年 243卷

作者： Wang, Feng Tian, Jin Shi, Chenli Ling, Jiamu Chen, Zian Xu, Zhengguo Zhejiang Univ State Key Lab Ind Control Technol Hangzhou 310027 Peoples R China Zhejiang Univ Coll Control Sci & Engn Hangzhou 310027 Peoples R China Huzhou Univ Inst Microbiol & Immunol Huzhou 313000 Zhejiang Peoples R China Beihang Univ Sch Reliabil & Syst Engn Beijing Peoples R China

In urban infrastructure systems, resilience is crucial for maintaining functionality, minimizing losses, and expediting recovery during disruptive incidents. Effective allocating resources across various phases of emerging disturbances can generally enhance the system's capacity to cope with disasters. However, it is imperative to recognize that distinct resource allocation strategies may lead to divergent outcomes in terms of resilience performance. Therefore, this study develops a framework for optimizing resource allocation based on multiple resilience objectives by understanding the interplay between resilience performance and dynamic decisionmaking. The resilience processes are first formalized into distinct stages, considering the technical and organizational resilience of the infrastructure system in the event of disruption. Building upon this foundation, five decision scenarios are proposed, contingent on the allocation or non-allocation of resources to each resilience stage. A multi-resilience-objective mixed-integer linear programming (MROMILP) model is formulated to optimize the resource allocation scheme for each resilience stage within the constraints of internal resources. Finally, the model and framework are tested using a power system as a tangible example. The integrated multi-stage quantitative resilience assessment and optimization method proposed in this study can assist decision-makers in making dynamic and continuous trade-offs between resources and resilience targets.

关键词： Infrastructure systems Resilience optimization multi-objective programming Resource allocation

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multi-criteria decision making approach for supplier selection and order allocation in a digital supply chain resilience

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ANNALS OF OPERATIONS RESEARCH 2024年 1-37页

作者： Fang, Jiaqi Zhou, Wenli Xiong, Lihui Wenzhou Univ Sch Business Wenzhou 325035 Zhejiang Peoples R China

The emergence of strong strategic sourcing and globalization has increased the sensitivity of supply chains to disruption, especially for technology companies. Supplier selection and order Allocation (SS-OA) has become a key strategic decision in high-quality supply chain planning and management. This paper builds a data-driven framework and, through a systematic literature review and interviews with management, establishes an evaluation system that integrates economic, resilience, and digital criteria. The adaptability and performance of suppliers were evaluated by AHP and TOPSIS. On this basis, a dual-objective order optimization model is established to optimize the value of flexible digital procurement and reduce related costs. Integrating the supplier selection criteria of the enterprise, the non-dominant sorting genetic algorithm in the meta-heuristic algorithm is used to solve the Pareto optimal solution set. This method provides decision support for supplier selection and order allocation in the supply chain, and promotes the sustainable development of enterprises.

关键词： Supply chain resilience multi-objective programming Supplier selection AHP TOPSIS NSGA-II

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Carbon emission reduction by forming liner alliances under maritime emission trading system

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TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT 2025年 144卷

作者： Sun, Yulong Zheng, Jianfeng Cui, Di Liu, Huayu Dalian Maritime Univ Transportat Engn Coll Dalian Peoples R China China Waterborne Transportat Res Inst Safety & Emergency Div Beijing Peoples R China Dalian Maritime Univ Marine Engn Coll Dalian Peoples R China

The maritime emission trading system (METS) is adopted to reduce ship CO2 emissions. This paper utilizes the forming of liner alliances under the METS to further reduce ship CO2 emissions. To investigate the effectiveness of forming liner alliances on ship CO2 emission reduction, we propose a liner ship operation planning problem for a liner alliance, which determines fleet deployment, slot co-chartering and emission permit trading. A multi-objective programming model is adopted to deal with the proposed problem. By considering three liner carriers, numerical results show that, i) the total ship CO2 emission reduction rate for these three liner carriers can be up to 13.5 %, by forming the liner alliance;ii) for any of these three liner carriers, the ship CO2 emission reduction rate can be up to 10 %similar to 15 %, by forming the liner alliance;iii) high fuel prices help liner alliances balance the trade-off between the operational cost and ship CO2 emissions.

关键词： Ship emissions Maritime emission trading system Liner alliance multi-objective programming

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Matrix-based network data envelopment analysis: A common set of weights approach

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SOCIO-ECONOMIC PLANNING SCIENCES 2024年 95卷

作者： Peykani, Pejman Esmaeili, Fatemeh Sadat Seyed Pishvaee, Mir Saman Rostamy-Malkhalifeh, Mohsen Lotfi, Farhad Hosseinzadeh Khatam Univ Fac Engn Dept Ind Engn Tehran Iran Iran Univ Sci & Technol Sch Ind Engn Tehran Iran Islamic Azad Univ Dept Math Sci & Res Branch Tehran Iran Istinye Univ Res Ctr Performance & Prod Anal Istanbul Turkiye

Performance measurement of decision-making units (DMUs) with network structure is one of the main challenges in data envelopment analysis (DEA) field. The main purpose of this paper is to propose a novel network data envelopment analysis (NDEA) approach based on matrix of efficiency, common set of weights (CSW), multiobjective programming (MOP), and goal programming (GP) technique for performance measurement of peer DMUs in two-stage network structure. The advantages of the proposed NDEA approach can be summarized as follows: comparing all DMUs and sub-DMUs on the same base, considering all internal structures and relations and capability to extending this for all network structures, linearity of the proposed models, unique efficiency decomposing without any need to consider multiplicative, additive or leader-follower relations between overall and stages efficiency. To illustrate the usefulness and applicability of the proposed approach we applied it to a real application of non-life insurance companies in Taiwan.

关键词： Network data envelopment analysis Common set of weights Efficiency matrix General two-stage structure multi-objective programming Insurance industry

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A New Mean-Variance-Skewness Model for Portfolio Optimization Using Three-Part Zigzag Uncertain Variable

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PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES INDIA SECTION A-PHYSICAL SCIENCES 2025年第1期95卷 55-70页

作者： Chhatri, Sanjoy Bhattacharya, Debasish Natl Inst Technol Agartala Dept Math Agartala 799046 Tripura India

A multi-objective portfolio selection problem involving newly introduced stocks has been studied here, and an innovative solution procedure for the same with a numerical illustration is also provided. The returns of these stocks are represented by a new uncertainty distribution, called the three-part zigzag uncertainty distribution, introduced in this paper. This newly defined uncertainty distribution function is regular and closer to an S-shaped curve than linear and zigzag uncertainty distribution functions. The properties of the three-part zigzag uncertainty distribution are studied, and the expression for the general order central moment of the distribution has been obtained. Using the expected value and the second, third order central moments, two maximizing objectives and one minimizing objective for the said optimization purpose are formed. Finally, using the "fmincon" function in Matlab 2018a, the constructed problem is solved. The solution obtained has been interpreted. The fact that it yields an efficient or Pareto optimal solution has also been *** Statement A three-objective portfolio selection problem in an uncertain situation has been constructed using a newly defined uncertainty distribution. An innovative solution procedure that elicits efficient solutions is suggested to solve the problem. The work done can be applied to solve real-life portfolio selection problems with better accuracy.

关键词： Portfolio optimization Uncertain variable Efficient solution multi-objective programming 74PXX 90-XX

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Effects of Price Range Variation on Optimal Sizing and Energy Management Performance of a Hybrid Fuel Cell Vehicle

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IEEE TRANSACTIONS ON ENERGY CONVERSION 2023年第3期38卷 1626-1638页

作者： Fernandez, Alvaro Macias Kandidayeni, Mohsen Boulon, Loic Trovao, Joao P. Univ Quebec Trois Rivieres Hydrogen Res Inst Dept Elect & Comp Engn Trois Rivieres PQ G8Z 4M3 Canada Univ Sherbrooke Dept Elect Engn & Comp Engn Sherbrooke PQ J1K 2R1 Canada Polytech Coimbra P-3045093 Coimbra Portugal INESC Coimbra P-3030290 Coimbra Portugal

The usage of multi-objective cost functions (MOCFs) in sizing and energy management strategy (EMS) of fuel cell hybrid electric vehicles (FCHEVs) has expanded due to the participation of multiple technological and economic disciplines. To better understand the impact of price fluctuation on the component size and EMS of an FCHEV, this article proposed a sensitivity analysis methodology. First, a two-step optimization approach that considers hydrogen consumption, system degradation, and trip cost is used to minimize a MOCF of the Can-Am Spyder electric motorcycle simulator. Then, an effect analysis is carried out for the cost-optimal results under two driving profiles to understand the link between cost variation and system performance. These simulations indicate that each might result in different system sizes and EMS compromise. After that, an online optimization EMS based on sequential quadratic programming is used on a reduced-scale hardware-in-the-loop configuration to evaluate the simulation results with varied weights. Experimental results indicate that when an adequate size is used for each pair of weights, the EMS results in a 6% decrease in the trip cost.

关键词： Electric vehicles fuel cells genetic algorithms multi-objective programming optimal control

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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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Research on optimal train operation control strategy based on dynamic programming algorithm 3

Research on optimal train operation control strategy based o...

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2023 IEEE 3rd International Conference on Data Science and Computer Application, ICDSCA 2023

作者： Zhou, Luyao Shen, Zhijie Liu, Haoran Zhang, Qingyang Gao, Zehua Liu, Jiawang Wenzhou University of Technology Wenzhou China Dongguan University of Technology Dongguan China Jiangsu University Zhenjiang China Nanjing Institute of Technology Nanjing China Hebei University Baoding China Jishou University Jishou China

ISBN: (纸本)9798350341546

Energy-saving train operation is an important means to reduce the energy consumption of rail transit system. This paper mainly aims at the problem that different driving strategies will produce different energy and time consumption during train operation, and establishes a mathematical model to study the optimal train driving strategies in different running processes. Firstly, the train dynamics model is established, and the running parameters of the train under different road conditions are obtained by Euler method. Then, optimization models of single objective programming and multi-objective programming are constructed according to different road conditions, and then dynamic programming algorithm is used to solve the models, and the optimal train control strategy under different objectives and different road conditions is obtained, and the relevant parameter sequence curves are obtained. © 2023 IEEE.

关键词： Dynamic programming algorithm Eulerian method multi-objective programming Nonlinear programming Single objective programming

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