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A multi-objective mathematical programming model for location-routing of COVID-19 healthcare waste in Tunisia

ANNALS OF OPERATIONS RESEARCH 2024年 1-22页

作者： Frikha, Hela Daami, Fedia Univ Sfax Higher Inst Ind Management OLID Res Lab Rd Tunis Km 10-5Technopole SfaxBP 1164 Sfax 3021 Tunisia

The fast transmission of the Severe Acute Respiratory Syndrome CoronaVirus 2 (SARS-CoV-2) has led to a pandemic of Coronavirus Disease 2019 (COVID-19) through the world. The spread of this virus is continuing to generate a universal health crisis that led to severe impacts on all people across the world. This disease has resulted in an enormous number of infected cases that must be hospitalized. The exponential increase in the number of tested positive patients systematically leads to an exponential generation of healthcare wastes. Indeed, healthcare waste management is a challenge task for the municipal authorities and healthcare providers since inadequate management policies can lead to serious problems for both human health and environment. In this context, in order to face the third wave pandemic pick, we propose in this paper a multi-objective mixed integer mathematical program to expend the capacity of medical waste facilities by locating temporary treatment centers as well as temporary landfills. In addition, the proposed model allows optimizing COVID-19 medical waste routing from hospitals to disposal centers. The location-routing suggested model aims at minimizing the risk of virus transmission as well as total costs and is applied on a real case study based on the COVID-19 outbreak in Tunisia.

关键词： COVID-19 outbreak Hazardous healthcare waste multi-objective mathematical programming Location-routing problem Waste treatment centers Landfills

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A Fuzzy multi-objective mathematical programming Model for Project Management Decisions Considering Quality and Contractual Reward and Penalty Costs in a Project Network

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ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING 2021年第2期46卷 1617-1629页

作者： Hashemi, S. M. Mousavi, S. M. Patoghi, A. Shahed Univ Dept Ind Engn Tehran Iran

Project management is a process that schemes and controls the project life cycle via the easiest and the best way to achieve project goals. Project managers always aim to simultaneously handle conflicting goals in the organization. In this paper, a new mathematical model is proposed that simultaneously minimizes total cost and completion time and maximizes the quality in the project management decision problem. Contractual penalty cost and contractual reward cost with a new method are the other consideration in the proposed model. In the projects, the relation between time and direct cost is a nonlinear function. Hence, a linearization technique is presented with attention to variable change and piecewise linearization, in which nonlinear function is converted to the linear programming model. On the other hand, in real conditions according to uncertainty in environmental situations and incomplete information, there can be ambiguity in parameters and variables of the problem. The uncertainty of the parameters and variables is expressed with fuzzy sets theory and fuzzy mathematical programming. The other aim of this paper is to introduce a modified version of fully fuzzy multi-objective linear programming for the problem. For analyzing a fully fuzzy time-cost-quality project management model, a practical example of the literature is provided. By examining the results of the model with conflicting objectives, two scenarios are presented to explore the interactions of conflicting objectives on the project, and the results are reported.

关键词： Project management decision multi-objective mathematical programming Quality Contractual penalty and reward cost Fully fuzzy linear programming

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multi-objective Phasor Measurement Unit Placement in Electric Power Networks: Integer Linear programming Formulation

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ELECTRIC POWER COMPONENTS AND SYSTEMS 2015年第17期43卷 1902-1911页

作者： Aghaei, Jamshid Baharvandi, Amir Akbari, Mohammad-Amin Muttaqi, Kashem M. Asban, Mohammad-Reza Heidari, Alireza Shiraz Univ Technol Dept Elect & Elect Engn Shiraz *** Iran Univ Wollongong Australian Power Qual & Reliabil Ctr Sch Elect Comp & Telecommun Engn Wollongong NSW Australia Univ New S Wales Australian Energy Res Inst Sydney NSW Australia Univ New S Wales Sch Elect Engn & Telecommun Sydney NSW Australia

A multi-objective optimal phasor measurement unit placement model using integer linear programming is presented in this article. The proposed model simultaneously optimizes two objectives, i.e., minimization of phasor measurement unit numbers and maximization of measurement redundancy. To calculate the redundancy criteria, the single-line outage and the phasor measurement unit loss are considered simultaneously. A linear formulation is presented for both objective functions. Also herein, to address conflicting attributes and identify Pareto optimal solutions of the multi-objective optimal phasor measurement unit placement problem, a new multi-objective mathematical programming method is proposed. Finally, a new index, i.e., minimum distance to utopia point, is implemented to select the most preferred solution among the available Pareto front based options on the goal to achieve judicious decision makers. Two test systems, i.e., a modified 9-bus and an IEEE 118-bus test systems, are used to illustrate the effectiveness of the proposed framework.

关键词： phasor measurement unit integer linear programming phasor measurement unit placement redundancy observability analysis multi-objective mathematical programming line outage Pareto solution optimization state estimation

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A multi-objective programming model for assessment the GHG emissions in MSW management

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WASTE MANAGEMENT 2013年第9期33卷 1934-1949页

作者： Mavrotas, George Skoulaxinou, Sotiria Gakis, Nikos Katsouros, Vassilis Georgopoulou, Elena Natl Tech Univ Athens Iroon Polytech 9 Athens 15780 Greece EPEM SA Athens 10446 Greece FACETS SA Athens 11471 Greece Athena Res & Innovat Ctr Maroussi 15125 Greece Natl Observ Athens Athens 11810 Greece

In this study a multi-objective mathematical programming model is developed for taking into account GHG emissions for Municipal Solid Waste (MSW) management. mathematical programming models are often used for structure, design and operational optimization of various systems (energy, supply chain, processes, etc.). The last twenty years they are used all the more often in Municipal Solid Waste (MSW) management in order to provide optimal solutions with the cost objective being the usual driver of the optimization. In our work we consider the GHG emissions as an additional criterion, aiming at a multi-objective approach. The Pareto front (Cost vs. GHG emissions) of the system is generated using an appropriate multi-objective method. This information is essential to the decision maker because he can explore the trade-offs in the Pareto curve and select his most preferred among the Pareto optimal solutions. In the present work a detailed multi-objective, multi-period mathematical programming model is developed in order to describe the waste management problem. Apart from the bi-objective approach, the major innovations of the model are (1) the detailed modeling considering 34 materials and 42 technologies, (2) the detailed calculation of the energy content of the various streams based on the detailed material balances, and (3) the incorporation of the IPCC guidelines for the CH4 generated in the landfills (first order decay model). The equations of the model are described in full detail. Finally, the whole approach is illustrated with a case study referring to the application of the model in a Greek region. (C) 2013 Elsevier Ltd. All rights reserved.

关键词： MSW Optimization multi-objective mathematical programming GHG emissions

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A fuzzy QFD approach to determine supply chain management strategies in the dairy industry

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JOURNAL OF INTELLIGENT MANUFACTURING 2013年第6期24卷 1111-1122页

作者： Ayag, Zeki Samanlioglu, Funda Buyukozkan, Gulcin Kadir Has Univ Fac Engn Dept Ind Engn Istanbul Turkey Galatasaray Univ Fac Engn & Technol Dept Ind Engn Istanbul Turkey

The aim of this study is to identify the crucial logistics requirements and supply chain management (SCM) strategies for the dairy industry. For product or service development, quality function deployment (QFD) is a useful approach to maximize customer satisfaction. The determination of design requirements and supply chain management strategies are important issues during QFD processes for product or service design. For this reason, a fuzzy QFD methodology is proposed in this study to determine these aspects and to improve customer satisfaction. Qualitative information is converted firstly into quantitative parameters, and then this data is combined with other quantitative data to parameterize two multi-objective mathematical programming models. In the first model, the most important logistic requirements for the company are determined based on total technical importance, total cost, total feasibility and total value increment objectives, and in the second model, based on these objectives, appropriate supply chain management strategies are determined. Finally, a case study from the Turkish dairy industry is given to illustrate the proposed approach.

关键词： Dairy customer needs Dairy logistics requirements Supply chain management strategies Fuzzy QFD multi-objective mathematical programming

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A new multi-objective solution approach to solve transmission congestion management problem of energy markets

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APPLIED ENERGY 2016年 165卷 462-471页

作者： Hosseini, Seyyed Ahmad Amjady, Nima Shafie-khah, Miadreza Catalao, Joao P. S. Semnan Univ Dept Elect Engn Semnan Iran Univ Beira Interior P-6201001 Covilha Portugal Univ Porto Fac Engn P-4200465 Oporto Portugal Univ Lisbon Inst Super Tecn INESC ID Av Rovisco Pais 1 P-1049001 Lisbon Portugal

Transmission congestion management plays a key role in deregulated energy markets. To correctly model and solve this problem, power system voltage and transient stability limits should be considered to avoid obtaining a vulnerable power system with low stability margins. Congestion management is modeled as a multi-objective optimization problem in this paper. The proposed scheme includes the cost of congestion management, voltage stability margin and transient stability margin as its multiple competing objectives. Moreover, a new effective multi-objective mathematical programming (MMP) solution approach based on normalized normal constraint (NNC) method is presented to solve the multi-objective optimization problem of the congestion management, which can generate a well-distributed and efficient Pareto frontier. The proposed congestion management model and MMP solution approach are implemented on the New-England's test system and the obtained results are compared with the results of several other congestion management methods. These comparisons verify the superiority of the proposed approach. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： Transmission congestion management Deregulated energy market multi-objective mathematical programming Voltage and transient stability

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An integrated approach for sustainable supply chain planning

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COMPUTERS & OPERATIONS RESEARCH 2015年 54卷 180-194页

作者： Boukherroub, Tasseda Ruiz, Angel Guinet, Alain Fondrevelle, Julien Interuniv Res Ctr Enterprise Networks Logist & Transportat CIRRELT Quebec City PQ Canada Univ Laval Fac Forest Geog & Geomat Quebec City PQ G1V 0A6 Canada Univ Laval Fac Sci Adm Quebec City PQ G1V 0A6 Canada Inst Natl Sci Appl Univ Lyon DISP EA4570 F-69621 Villeurbanne France

This paper proposes an integrated approach for transposing sustainable development principles to supply chain planning models. Inspired by research on performance measurement, we designed a method that links sustainability performance to supply chain decisions, and allows setting coherent performance measures. By transposing this method to a multi-objective mathematical programming, the supply chain planning is optimized while the economic, environmental and social performances are all coherently integrated into the model. To illustrate our approach, we applied it to a Canadian lumber industry case. We solved the mathematical model by using the weighted goal programming technique, which results in a set of "compromise" solutions allowing the decision maker to choose the alternative that reflects the balance he/she wishes to make regarding the three dimensions of sustainability. (C) 2014 Elsevier Ltd. All rights reserved.

关键词： Supply chain planning Sustainable development Performance measurement multi-objective mathematical programming Weighted goal programming

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multi-objective design optimization of combined cooling, heating and power system for cruise ship application

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JOURNAL OF CLEANER PRODUCTION 2019年 233卷 264-279页

作者： Yan, Yamin Zhang, Haoran Long, Yin Wang, Yufei Liang, Yongtu Song, Xuan Yu, James J. Q. China Univ Petr Beijing Key Lab Urban Oil & Gas Distribut Technol Fuxue Rd 18 Beijing 102249 Peoples R China Univ Tokyo Ctr Spatial Informat Sci 5-1-5 Kashiwanoha Kashiwa Chiba 2778563 Japan Univ Tokyo Grad Sch Frontier Sci Dept Environm Syst 5-1-5 Kashiwanoha Kashiwa Chiba 2778563 Japan China Univ Petr State Key Lab Heavy Oil Proc Fuxue Rd 18 Beijing 102249 Peoples R China Univ Hong Kong Dept Elect & Elect Engn Pokfulam Hong Kong Peoples R China

In recent years, the size (weight and volume) of cruise ships are experiencing spectacular increase, coherently with the increase in energy consumption and carbon emissions. However, the regulations about pollutant emissions imposed by the International Maritime Organization are becoming more and more strict. In order to face up to this issue, the energy system of cruise ships is constantly being modified. In this paper, the structure of the cruise ship's energy system with multiple facilities such as an internal combustion engine, gas turbine, dual fuel engine, PV panels, and the wind turbine is preestablished. Then, a multi-objective mathematical programming model is formulated to determine the selection and capacity of facilities with minimal total annual cost and size, while the emissions, energy balance and technical constraints are taken into account. By adopting the augmented epsilon-constraint method, the design and operation strategies could be obtained. As an illustrated example, the model is applied to a real cruise ship, and the Pareto frontier could provide ship designers with well-balanced solutions based on economic and size priorities, and with the increase in the proportion of size objective, the total annual cost increases and size decreases gradually. Compared with the reference energy system, the optimal energy system could reduce the total annual cost by 12.6% if only the economic objective is considered and reduce the size by 21.1% if only the size objective is considered. In multi objective condition, the CO, NOx, and SOx emissions could be reduced by 29.1%-61.3%, 42.8%-61.3%, and 42.8%-613% per year, respectively. Moreover, a sensitivity analysis is conducted, and the result shows that the size and consumption cost of Marine Gas Oil (MGO) and Liquefied Natural Gas (LNG) are more sensitive to the change of the proportion of size objective compared to Heavy fuel oil (HFO) and Marine diesel oil (MDO). (C) 2019 Elsevier Ltd. All rights reserved.

关键词： Cruise ship Energy system multi-objective mathematical programming Optimization

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A vibration damping optimization algorithm for solving a new multi-objective dynamic cell formation problem with workers training

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COMPUTERS & INDUSTRIAL ENGINEERING 2016年 101卷 35-52页

作者： Mehdizadeh, Esmaeil Niaki, Seyed Vahid Daei Rahimi, Vahid Islamic Azad Univ Qazvin Branch Fac Ind & Mech Engn Qazvin Iran

This paper presents a comprehensive multi-objective mixed integer mathematical programming model which considers cell formation and production planning problems simultaneously. This comprehensive model includes dynamic system reconfiguration, multi period production planning, operation sequence, alternative process plans for part types, machine and worker flexibility, duplicate machines, machine capacity, available time of workers and worker assignment. The aim of the proposed model is to minimize inter and intra-cell movement costs, machine and reconfiguration costs, setup costs, production planning costs (holding, backorder and subcontracting costs) and workers hiring, firing, training and salary costs, as well as minimizing summation of machines idle times as a second objective. Due to NP-hardness of the problem, a recent and efficient meta-heuristic algorithm namely multi-objective vibration damping optimization (MOVDO) is designed for finding Pareto-optimal frontier. In order to check the efficiency of the developed algorithm, it is compared with two salient multi-objective genetic algorithms named NSGAII and NRGA. Finally, by generating some test problems in small and large scales and using some multi objective comparison metrics, the algorithms are compared and analyzed statistically. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： Dynamic cell formation problem Cellular manufacturing system multi-objective mathematical programming Production planning Vibration damping optimization algorithm

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Using DEA to obtain efficient solutions for multi-objective 0-1 linear programs

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2000年第1期126卷 51-68页

作者： Liu, FHFL Huang, CC Yen, YL Natl Chiao Tung Univ Dept Ind Engn & Management Hsinchu 300 Taiwan Natl Yunlin Univ Sci & Technol Dept Ind Management Touliu 640 Taiwan

This paper concerns the problem of a service-oriented public sector entity to allocate limited resources to different activities while keeping conflicting objectives in mind. The multi-objective Resource Allocation Problem (MRAP) is to select activities to be performed. The authors formulate the problem as a multi-objective 0-1 linear problem. The authors implement Data Envelopment Analysis (DEA) with the Banker, Charnes and Cooper's (BCC) model to measure the Decision Making Unit's (DMU) efficiency. In this study, the production function is a mathematical statement relating the technological relationship between the objectives and resources of MRAP. Each DMU presents a technological relationship, i.e. DMU presents a relationship between resources and objectives. This relationship gives information about the use of resources and satisfactoriness of objectives. The inputs and outputs, respectively, outline resources and objectives. The production possibility set represents feasible solutions for MRAP. Moreover, due to the multiple objectives of problems, the method derives a solution set instead of an optimal solution in single objective ones. This solution set, a well-known efficient solutions set, forms the decision set of problems. Each DMU results from an alternative, a combination of activities, The production possibility set presents all the candidates of DMU. The set of alternatives resulting in efficient DMUs is efficient solutions of MRAP. The authors developed a two-stage algorithm to generate and evaluate DMUs. The first stage generates a DMU with the maximum of the distance function. The second stage is then used to evaluate the efficiency of the generated DMU. (C) 2000 Elsevier Science B.V. All rights reserved.

关键词： data envelopment analysis multi-objective mathematical programming 0-1 linear programming

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