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Design of a reverse logistics network for medical waste considering location and routing decisions

JOURNAL OF CLEANER PRODUCTION 2024年 474卷

作者： Palomino-Perez, Yulieth Rojas, Miguel Amaya-Mier, Rene Univ Norte Dept Ind Engn Barranquilla Colombia

Medical waste generated in healthcare facilities is categorized as hazardous due to its infectious, toxic, or radioactive properties, posing substantial risks to human health and the environment. This research proposes a bi-objective mixed-integer linear programming model for designing reverse logistics networks that enable both economical and safe medical waste management. Said model determines optimal quantity, depot locations, and routes for transporting waste from its generating points (hospitals) to the treatment and disposal sites (depots). This research addresses a bi-objective location routing problem, with multiple depots, time windows, capacity constraints, and variated waste types, across a multi-period horizon. It is innovative because no previous works have successfully dealt with such a combination of pragmatic features. The Location Routing Problem is an already well-known NP-Hard problem, with the additional aforementioned features further adding to its complexity. Thus, a genetic algorithm to solve large-sized realistic instances within reasonable computing times had been developed. Numerical experiments considered 20 random instances contrasting exact and approximate solution approaches. Also, a medical waste collection case study of a public hospital network in Atlantico Department, Colombia, delivering a Pareto frontier solution set, was introduced. The results demonstrated the efficacy of the proposed genetic algorithm in successfully addressing small instances of the problem, delivering outcomes comparable to the mixed-integer linear programming model. Furthermore, it yields good-quality solutions in a reduced computational time for larger instances deemed unfeasible for the mixed-integer linear programming model. This article contributes to both scientific literature and practitioners by presenting a decision-making tool designed to address the medical waste reverse logistics challenge under realistic scenarios. It approaches the

关键词： Medical hazardous waste Reverse logistics network Location-routing problem Multiobjective optimization mixed-integer linear programming model Genetic algorithm

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Mathematical modeling and a hybrid evolutionary algorithm for process planning

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JOURNAL OF INTELLIGENT MANUFACTURING 2021年第3期32卷 781-797页

作者： Liu, Qihao Li, Xinyu Gao, Liang Huazhong Univ Sci & Technol Sch Mech Sci & Engn State Key Lab Digital Mfg Equipment & Technol Wuhan 430074 Peoples R China

Process planning is an essential part of the manufacturing system linking the designing and practical manufacturing. However, the reported process planning models are too simple to describe all characteristics because of the complexity of process planning. Therefore, a new mixed-integer linear programming (MILP) mathematical model is established based on OR-node of the network graph. In the model, the linear expression of the OR-node controlling function as well as three types of changing costs are first established. Beside, considering the OR-node selection state in the encoding and decoding method, a hybrid evolutionary algorithm (HEA) is designed to combine a genetic algorithm with a simulated annealing algorithm. The tournament selection method is adopted in the proposed HEA, and the discussion on the tournament size is conducted on the open problems to make the algorithm designing more reasonable and scientific. The HEA and the new MILP model are both tested on series of numerical experiments which are carried on the existing benchmarks as well as some randomly generated cases. The behavior of both two methods can verify their effectiveness and superiority successfully.

关键词： Process planning mixed-integer linear programming model Hybrid evolutionary algorithm Benchmark

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Optimal coordinated operation of integrated energy hubs, considering regenerative braking utilization

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IET ELECTRICAL SYSTEMS IN TRANSPORTATION 2021年第4期11卷 362-376页

作者： Akbari, Saeed Fazel, Seyed Saeed Jadid, Shahram Iran Univ Sci & Technol Sch Railway Engn Tehran 16864 Iran Iran Univ Sci & Technol Sch Elect Engn Tehran Iran

This article presents a coordinated operation model for energy management of a multi-integrated energy system based on mixed-integer linear Programing (MILP). The power derived by trains from regenerative braking energy (RBE), during deceleration, is utilised to meet the interconnected energy hubs' (IEHs) demand. The recovered energy is calculated by simulating the motion of the trains in MATLAB software. The electricity and heat demand response (DR) programs are integrated into the proposed model to study their impacts on the operating cost and the carbon emission of the IEH, considering several case studies. Furthermore, the uncertainties of the RBE, photovoltaic power generation, and loads of the IEH are considered by formulating the optimisation problem stochastically through a scenario-based approach. Therefore, a scenario generation and reduction decision-making technique is employed. Finally, the GAMS optimisation software is used to assess the efficiency of the presented MILP model. The simulation results indicate that the total operating cost of the IEH reduced 2.0% and 1.4% in the case studies. Also, the CO2 emission is decreased by about 0.3% by applying the coordination scheme besides the DR programs.

关键词： carbon compounds total operating cost Matlab photovoltaic power generation reduction decision-making technique GAMS optimisation software integrated interconnected energy hubs regenerative braking utilization photovoltaic power systems DR programs carbon emission power engineering computing regenerative braking energy stochastic programming MATLAB software MILP model linear programming multiintegrated energy system RBE IEH coordination scheme integer programming energy management CO mixed-integer linear programming model energy management systems regenerative braking coordinated operation model demand side management decision making

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Development of an intelligent evolution algorithm for open pit mines' long-term production scheduling using the concept of block aggregation

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MINING TECHNOLOGY-TRANSACTIONS OF THE INSTITUTIONS OF MINING AND METALLURGY 2024年第3期133卷 257-275页

作者： Azadi, Nooshin Mirzaei-Nasirabad, Hossein Sahand Univ Technol Fac Min Engn Tabriz Iran

The method described for production scheduling in this study is a simultaneous use of a clustering algorithm with a genetic algorithm (GA). The aggregating algorithm presented in this study aims to control the concentration of operations and the cluster size, which is evaluated using the Silhouette criterion. The fitness function and the chromosome length in the GA have differences from the usual one. The results showed the number of binary variables in a mixed-integer linear programming model was reduced by 78.5% based on the created clusters. Although the aggregated model's net present value (NPV) is decreased by 7%, the solution time significantly dropped from 3 h to 43.1 s. Also, compared to the non-clustering block model, the aggregated block model's NPV, obtained by GA, was improved.

关键词： The Silhouette criterion open-pit mine block aggregation mixed-integer linear programming model genetic algorithm long-term production scheduling

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A deterministic bounding procedure for the global optimization of a bi-level mixed-integer problem

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2021年第1期291卷 52-66页

作者： Soares, Ines Alves, Maria Joao Antunes, Carlos Henggeler INESC Coimbra DEEC Rua Silvio LimaPolo 2 P-3030290 Coimbra Portugal Univ Coimbra CeBER Av Dias da Silva 165 P-3004512 Coimbra Portugal Univ Coimbra Fac Econ Av Dias da Silva 165 P-3004512 Coimbra Portugal Univ Coimbra Dept Elect & Comp Engn Rua Silvio LimaPolo 2 P-3030290 Coimbra Portugal

In this paper, a deterministic bounding procedure for the global optimization of a mixed-integer bi-level programming problem is proposed. The aim has been to develop an efficient algorithm to deal with a case study in the electricity retail market. In this problem, an electricity retailer wants to define a time-of-use tariff structure to maximize profits, but he has to take into account the consumers' reaction by means of re-scheduling appliance operation to minimize costs. The problem has been formulated as a bi-level mixed-integer programming model. The algorithm we propose uses optimal-value-function reformulations based on similar principles as the ones that have been used by other authors, which are adapted to the characteristics of this type of (pricing optimization) problems where no upper (lower) level variables appear in the lower (upper) level constraints. The overall strategy consists of generating a series of convergent upper bounds and lower bounds for the upper-level objective function until the difference between these bounds is below a given threshold. Computational results are presented as well as a comparison with a hybrid approach combining a particle swarm optimization algorithm to deal with the upper-level problem and an exact solver to tackle the lower-level problem, which we have previously developed to address a similar case study. When the lower-level model is difficult, a significant relative MIP gap is unavoidable when solving the algorithm's subproblems. Novel reformulations of those subproblems using "elastic" variables are proposed trying to obtain meaningful lower/upper bounds within an acceptable computational time. (C) 2020 Elsevier B.V. All rights reserved.

关键词： Global optimization Bi-level optimization mixed-integer linear programming model Pricing problem Dynamic tariffs Electricity retail market Demand response

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Meta-heuristic algorithm for aircraft pre-tactical conflict resolution with altitude and heading angle change maneuvers

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TOP 2021年第3期29卷 629-647页

作者： Cecen, Ramazan Kursat Sarac, Tugba Cetek, Cem Eskisehir Osmangazi Univ Eskisehir Turkey Eskisehir Tech Univ Eskisehir Turkey

Aircraft conflict resolution is of great importance for the safe and efficient management of air traffic. This study proposes a two-step optimization approach for the aircraft conflict resolution problems within the pre-tactical time window in generic free route airspace. Safe separation between aircraft pairs is maintained using either altitude or heading angle change maneuvers in a pre-defined buffer zone within the boundaries of the airspace. The first step of the model aims to minimize the total number of conflicting aircraft and the total fuel consumption together using altitude change maneuvers. A mixed-integer linear programming model is proposed for the first step but, due to the high computational time, a metaheuristic algorithm (simulated annealing) was developed. If the altitude change does not resolve all conflicts in the first step, the proposed model implements heading angle change maneuvers with minimum extra fuel burn in the second step. A nonlinear programming model is presented for the second step. Numerical results show that the proposed approach can resolve all conflicts in less than 4 min for the highest traffic flow rate.

关键词： Aircraft conflict resolution Air traffic management Meta-heuristic algorithm Non-linear programming model mixed-integer linear programming model Free route airspace

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A mathematical programming approach for equitable COVID-19 vaccine distribution in developing countries

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ANNALS OF OPERATIONS RESEARCH 2021年 1-34页

作者： Tavana, Madjid Govindan, Kannan Nasr, Arash Khalili Heidary, Mohammad Saeed Mina, Hassan La Salle Univ Business Syst & Analyt Dept Distinguished Chair Business Analyt Philadelphia PA 19141 USA Univ Paderborn Fac Business Adm & Econ Business Informat Syst Dept D-33098 Paderborn Germany Univ Southern Denmark Dept Technol & Innovat Odense Denmark Sharif Univ Technol Grad Sch Management & Econ Tehran Iran Allameh Tabatabai Univ Fac Management & Accounting Tehran Iran Univ Tehran Coll Engn Sch Ind Engn Tehran Iran

Developing countries scramble to contain and mitigate the spread of coronavirus disease 2019 (COVID-19), and world leaders demand equitable distribution of vaccines to trigger economic recovery. Although numerous strategies, including education, quarantine, and immunization, have been used to control COVID-19, the best method to curb this disease is vaccination. Due to the high demand for COVID 19 vaccine, developing countries must carefully identify and prioritize vulnerable populations and rationalize the vaccine allocation process. This study presents a mixed-integer linear programming model for equitable COVID-19 vaccine distribution in developing countries. Vaccines are grouped into cold, very cold, and ultra-cold categories where specific refrigeration is required for their storage and distribution. The possibility of storage for future periods, facing a shortage, budgetary considerations, manufacturer selection, order allocation, time-dependent capacities, and grouping of the heterogeneous population are among the practical assumptions in the proposed approach. Real-world data is used to demonstrate the efficiency and effectiveness of the mathematical programming approach proposed in this study.

关键词： Vaccine supply chain Coronavirus vaccine Equitable distribution Location-inventory problem mixed-integer linear programming model COVID-19

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Integrated deployment of dedicated lane and roadside unit considering uncertain road capacity under the mixed-autonomy traffic environment

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TRANSPORTATION RESEARCH PART B-METHODOLOGICAL 2023年第1期174卷

作者： Zhang, Fang Lu, Jian Hu, Xiaojian Meng, Qiang Southeast Univ Jiangsu Key Lab Urban ITS Southeast Univ Rd 2 Nanjing 211189 Peoples R China Southeast Univ Jiangsu Prov Collaborat Innovat Ctr Modern Urban T Southeast Univ Rd 2 Nanjing 211189 Peoples R China Southeast Univ Sch Transportat Southeast Univ Rd 2 Nanjing 211189 Peoples R China Natl Univ Singapore Dept Civil & Environm Engn Singapore 117576 Singapore

The rapid development of automated vehicle (AV) technologies enables us to explore how to update the urban road infrastructure to cater for the upcoming mixed-autonomy traffic with both AVs and human-driven vehicles (HVs). In this study, we aim to seek an optimal solution to integrate the deployment of AV-dedicated lane and roadside unit assisting automated driving subject to a limited budget by considering the route choice behaviors of AVs and HVs. An AV-dedicated lane segregates AVs from the mixed traffic to create a fully automated driving envi-ronment and eliminate disturbances from HVs. The deployment of roadside units assisting automated driving could overcome the connectivity gap for AVs and lower their headway when they follow an HV. We seek to develop a robust and optimal integrated deployment solution that accommodates the uncertain road capacity caused by the stochastic mixed AV and HV fleet sequence. We first establish the stochastic network equilibrium conditions for the mixed traffic, and formulate the integrated deployment problem as a mathematical program with comple-mentarity constraints (MPCC). The MPCC is approximated by a mixed-integer linear programing (MILP) model, which allows existing algorithms for its global optimum. We further develop two interesting strategies, including domain reduction and breakpoint selection, to enhance the effectiveness of the MILP model. Numerical experiments are finally carried out to evaluate the feasibility of research methodology proposed in this study and find some valuable insights.

关键词： Automated vehicles Dedicated lanes Roadside units Uncertain road capacity linearization mixed-integer linear programming model

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Optimization of carbon emission in an integrated machine-piece scheduling and vehicle routing problem and its solution using MOPSO and NSGAII metaheuristic algorithms

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SCIENTIFIC REPORTS 2024年第1期14卷 1-30页

作者： Heidari, Ali Sheikh-Azadi, Amir-Hosein Hasan-Zadeh, Atefeh Kazemzadeh, Yousef Univ Tehran Coll Engn Sch Ind Engn Tehran Iran Univ Tehran Coll Engn Fouman Fac Engn POB *** Fouman Iran Persian Gulf Univ PGU Dept Petr Engn Bushehr Iran

The growth of the global economy is accompanied by significant energy consumption, and greenhouse gas emissions create various problems such as global warming and environmental degradation. To protect the environment, governments are seeking to reduce carbon emissions. Production systems that operate solely based on economic factors in the workshop only consider problems such as production speed, cost, and processing time. Two aspects can be effective in saving energy and reducing emissions at the production planning level: using routing to find the shortest path for collecting workpieces to the workshop, and turning off machines with long idle times and restarting them at the appropriate time. If the workshop production problem is combined with vehicle routing, a new problem arises. According to the research conducted so far, an integrated mathematical model for production routing has not been designed in a situation where the routing is before the production workshop. In this research, this bi-objective model is introduced, and it is solved using the augmented epsilon-constraint (AEC) method. The proposed mixed-integer linear programming model of this research includes three dimensions: environmental, social (customer satisfaction), and economic simultaneously. Given the high complexity of the mathematical model, MATLAB software and MOPSO and NSGA-II algorithms were used to solve it at higher dimensions. Seven evaluation criteria were used to compare the two proposed algorithms, and the results show that the MOPSO algorithm performs better. The findings suggest that minimizing pollution may involve sacrificing on-time delivery to customers. Consequently, decision-makers must carefully weigh the trade-off between reducing environmental impact and maintaining satisfactory delivery performance, ultimately deciding on an acceptable pollution level.

关键词： Optimization Vehicle Routing Carbon and Energy mixed-integer linear programming model Metaheuristic Algorithms

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Sustainable supply chain of distributed multi-product gas fields based on skid-mounted equipment to dynamically respond to upstream and market fluctuations

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ENERGY 2024年 292卷

作者： Hong, Bingyuan Du, Zhaonan Qiao, Dan Liu, Daiwei Li, Yu Sun, Xiaoqing Gong, Jing Zhang, Hongyu Li, Xiaoping Zhejiang Ocean Univ Natl & Local Joint Engn Res Ctr Harbor Oil & Gas S Sch Petrochem Engn & Environm Zhejiang Key Lab Petrochem Environm Pollut Control Zhoushan 316022 Peoples R China PipeChina Oil & Gas Control Ctr Dongtucheng Rd Beijing 100013 Peoples R China PipeChina West East Pipeline Co Shanghai 200120 Peoples R China China Natl Oil & Gas Explorat & Dev Corp Beijing 100034 Peoples R China China Univ Petr Natl Engn Lab Pipeline Safety MOE Key Lab Petr Engn Beijing Key Lab Urban Oil & Gas Distribut Technol Fuxue Rd 18 Beijing 102249 Peoples R China

Efficient operation of the gas field supply chain is an important guarantee for oil and gas energy security, and it needs to dynamically adapt to upstream and market fluctuations. This paper proposes an innovative design and operation optimization mixed integer nonlinear programming (MILP) method for distributed supply chain based on skid equipment. Unlike the traditional methods, the proposed MILP method can simultaneously obtain upstream production planning, midstream modular equipment and processing capacity allocation, and downstream transportation allocation schemes for various natural gas products such as liquefied natural gas (LNG), compressed natural gas (CNG) and pipeline natural gas (PNG) of each time periods by making the maximum net present value (NPV) of the full development cycle as the target. In order to prove the superiority and usability of the proposed method, four operation scheduling modes are compared through two comprehensive case analysis. Additionally, the effects of gas well productivity, market demand and product price are investigated through sensitivity analysis. The results show that comparing with the traditional method, the proposed method can effectively improve the loading rate of the processing equipment, increase the overall revenue of gas field development, integrate the operation in the upstream, midstream and downstream of the supply chain, dynamically adapt to the gas production and marketing fluctuations. This study provides a creative way to obtain better profit, reduce energy utilization and promote cleaner production for sustainable supplies management in gas industry.

关键词： Gas field supply chain mixed-integer linear programming model Production planning Modular infrastructure Operation optimization

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