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Optimization reverse logistics for waste plastic recycling in India: a genetic algorithm approach

INNOVATIVE INFRASTRUCTURE SOLUTIONS 2025年第5期10卷 1-13页

作者： Kumar, Sachin Sinha, Sanjeev Ranjan, Rajesh Saurav, Samir Natl Inst Technol Civil Engn Dept Patna India

The increasing environmental and economic impacts of plastic waste necessitate efficient recycling strategies. Despite advancements in reverse logistics for materials like metals and construction waste, plastic waste recycling remains underexplored, especially in urban contexts. This study fills this gap by developing a genetic algorithm (GA) and mixed-integer linear programming (MILP) model to optimize the reverse logistics network for plastic garbage in Patna, India. The approach incorporates 23 optimally located recycling facilities, resulting in an estimated 16.3% reduction in overall costs and 19.7% improvement in transportation efficiency. By integrating collection centers, the model effectively addresses low-density and contamination challenges, leading to a 22.5% increase in material recovery rates. Sensitivity evaluations on GA parameters and transportation costs confirm the model's robustness, producing stable and convergent solutions across different scenarios. Future research might compare GA performance with other optimization methods like Ant Colony or Grey Wolf Optimization and investigate stochastic frameworks to account for uncertainty in waste generation. This study provides a scalable, cost-effective, and data-driven framework for improving urban plastic waste management. The findings offer valuable insights for policymakers, urban planners, and waste management industries, helping them design more sustainable and economically viable recycling systems.

关键词： Plastic waste recycling Reverse logistics optimization Waste management efficiency Genetic algorithm mixed-integer linear programming model

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A distributed trajectory control strategy for the connected automated vehicle in an isolated roundabout

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IET INTELLIGENT TRANSPORT SYSTEMS 2022年第2期16卷 232-251页

作者： Wu, Ruiyi Jia, Hongfei Yang, Lili Miao, Hongzhi Lin, Yu Zhang, Yikun Jilin Univ Transportat Coll Changchun 130022 Peoples R China Dalian Maritime Univ Coll Transportat Engn Dalian 116026 Peoples R China Minist Publ Secur Traff Management Res Inst Wuxi 214151 Jiangsu Peoples R China

This paper develops a distributed cooperative control strategy (DCCS) to plan and optimize the collision-free trajectory for the connected automated vehicle (CAV) at an isolated roundabout. The representation of the trajectories of CAVs is defined within a roundabout. The central angle and lane radius are used to indicate the location of vehicles, and the corresponding angular velocity is used to describe the vehicle's speed through the roundabout. This trajectory definition method simplifies the proposed problem into two parts: the trajectory optimization of each vehicle in a specific lane and the lane change coordination of CAVs in the roundabout. To solve the trajectory optimization problem, a mixed-integer linear programming (MILP) model is formulated at the vehicle level to minimize the travel time and make the trajectory as smooth as possible. A model predictive control (MPC) framework is designed to coordinate lane-change conflicts and push CAVs' trajectories toward global optimization. The proposed framework integrates the vehicles' trajectory optimization results so that all CAVs reach a consensus. Numerical experiments test the effect of the strategy in terms of traffic efficiency and mobility performance under different demand pattern scenarios. The results show that the proposed RA-DCCS (Roundabout-DCCS) can make all CAVs smooth and conflict-free trajectories and enable vehicles to execute reasonable lane change decisions.

关键词： conflict-free trajectories global optimization trajectory optimization problem linear programming mixed-integer linear programming model CAV road vehicles specific lane trajectory control Roundabout-DCCS integer programming optimisation corresponding angular velocity isolated roundabout distributed cooperative control strategy predictive control road traffic trajectory definition method road safety vehicle level lane-change conflicts reasonable lane change decisions trajectory optimisation (aerospace) lane change coordination central angle model predictive control framework vehicles collision avoidance distributed trajectory control strategy push CAVs' trajectories lane radius traffic engineering computing collision-free trajectory connected automated vehicle

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Distributionally robust co-optimization of the demand-side resources and soft open points allocation for the high penetration of renewable energy

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IET RENEWABLE POWER GENERATION 2022年第4期16卷 713-725页

作者： Liu, Hong Li, Junkai Zhang, Shida Ge, Shaoyun Yang, Baijie Wang, Chengshan Tianjin Univ Minist Educ Key Lab Smart Grid Tianjin 300072 Peoples R China

The new technologies, such as soft open points (SOPs) and demand response (DR), offer original approaches to stabilize the system operation and accommodate the high penetration of distributed generators (DGs). However, the applied effects of these technologies are closely affected by the uncertainties of the consumer's willingness and the outputs of DGs. To solve the problems caused by the uncertainty of the resources in active distribution system, this paper proposes a distributionally robust co-optimization model for the demand side resources and SOPs, which realizes the combination of investment economy and operation robustness. Next, using equivalent substitution and polyhedron linearization technique, this paper proposes the mathematical method which transforms the original non-linear programming model into a mixed-integer linear programming model, and obtains the solution to the distributionally robust model with column and constraint generation (CCG) algorithm. Finally, the effectiveness of the proposed model is verified with the sample from a power distribution system in northern China. The result demonstrates that the co-optimization model can realize complementary advantages of the demand side resources and SOPs, which can not only guarantee the economy of scheme, but also improve the accommodation of DGs.

关键词： investment distributed generators power distribution system linear programming distributed power generation equivalent substitution nonlinear programming model mixed-integer linear programming model distributionally robust co-optimization model consumer nonlinear programming integer programming optimisation active distribution system SOPs demand response renewable energy investment economy soft open points allocation applied effects polyhedron linearization technique system operation distributionally robust model original approaches operation robustness

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Daily operation of multi-energy systems based on stochastic optimization considering prediction of renewable energy generation

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IET RENEWABLE POWER GENERATION 2022年第2期16卷 245-260页

作者： Azizi, Ali Karimi, Hamid Jadid, Shahram Iran Univ Sci & Technol Ctr Excellence Power Syst Automat & Operat Dept Elect Engn Tehran *** Iran

Nowadays, the energy crisis is one of the most critical challenges facing countries. To deal with this crisis, instead of independently optimizing each of the energy carriers (electricity, gas, heat etc.), all carriers are considered simultaneously by a concept called multi-energy system, which not only leads to economic benefits but also has environmental benefits. Here, a mixed-integer linear programming model is proposed to minimize the total daily cost of a local multi-energy system including the cost of energy exchange with the main grid, the cost of natural gas, and carbon emission costs. A polynomial neural network model is used to forecast the hourly wind speed and radiation of the next day. Also, a probabilistic scenario-generation and scenario reduction method is utilized to generate the possible scenarios from the probability density function. The simulation results show that the proposed model using neural network prediction and stochastic optimization increases the total cost of the multi-energy system by 12% in the worst-case. Sensitivity analysis of loads, electricity prices, and gas prices have been used to investigate the behaviour of variables on energy hub operating costs.

关键词： integer programming power generation economics local multienergy system sensitivity analysis energy crisis energy hub operating costs stochastic optimization considering prediction renewable energy generation power engineering computing linear programming total daily cost renewable energy sources mixed-integer linear programming model energy exchange carbon emission costs probability energy carriers natural gas

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A bi-level approach to load restoration strategy considering variant length of time steps

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IET GENERATION TRANSMISSION & DISTRIBUTION 2022年第2期16卷 319-332页

作者： Sun, Lei Yang, Zhichao Li, Mingming Ding, Ming Liang, Bomiao Hefei Univ Technol Sch Elect Engn & Automat Hefei Peoples R China Anhui Prov Key Lab Renewable Energy Utilizat & En Hefei Peoples R China Zhejiang Univ Sci & Technol Sch Automat & Elect Engn Hangzhou Peoples R China

A bi-level load restoration optimisation strategy is proposed for the transmission system with wind farm-energy storage combined systems (WESs), taking the variant length of time steps into account. The upper level model is proposed to maximise weighted restored loads, and formulated as a mixed-integer linear programming model. After solving the upper model, the optimal load pickup and transmission line restoration scheme can be obtained and delivered to the lower level model. The lower level model adopts a non-linear model to minimise the length of the current time step, which is delivered to the upper lever model. By iteratively solving the upper and lower level models, the optimal load pickup and transmission line restoration scheme as well as the optimal length of current time step can be obtained. To minimise the gap between the scheduled generation of the WES and its actual power generation, a real-time energy storage (ES) dispatch strategy is proposed taking maximum charging-discharging cycles of the ES into account. The entire load restoration strategy can be obtained by iteratively solving the proposed model with updated operational conditions of power systems. Finally, two test systems are employed to verify the validity and correctness of the proposed model.

关键词： transmission line restoration scheme power transmission lines dispatch strategy wind farm-energy storage combined systems power system restoration power generation dispatch wind power plants bi-level load restoration optimisation strategy integer programming current time step mixed-integer linear programming model iterative method charging-discharging cycles transmission system nonlinear model actual power generation WES iterative methods

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Optimal replication strategy for mitigating burst traffic in information-centric satellite networks: a focus on remote sensing image transmission

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Frontiers of Information Technology & Electronic Engineering 2024年第6期25卷 791-808页

作者： Ziyang XING Xiaoqiang DI Hui QI Jing CHEN Jinhui CAO Jinyao LIU Xusheng LI Zichu ZHANG Yuchen ZHU Lei CHEN Kai HUANG Xinghan HUO Jilin Key Laboratory of Network and Information Security Changchun 130022China School of Computer Science and Technology Changchun University of Science and TechnologyChangchun 130022China Information Center Changchun University of Science and TechnologyChangchun 130022China

Information-centric satellite networks play a crucial role in remote sensing applications,particularly in the transmission of remote sensing ***,the occurrence of burst traffic poses significant challenges in meeting the increased bandwidth *** content delivery networks are ill-equipped to handle such bursts due to their pre-deployed *** this paper,we propose an optimal replication strategy for mitigating burst traffic in information-centric satellite networks,specifically focusing on the transmission of remote sensing *** strategy involves selecting the most optimal replication delivery satellite node when multiple users subscribe to the same remote sensing content within a short time,effectively reducing network transmission data and preventing throughput degradation caused by burst traffic *** formulate the content delivery process as a multi-objective optimization problem and apply Markov decision processes to determine the optimal value for burst traffic *** address these challenges,we leverage federated reinforcement learning ***,we use bloom filters with subdivision and data identification methods to enable rapid retrieval and encoding of remote sensing *** software-based simulations using a low Earth orbit satellite constellation,we validate the effectiveness of our proposed strategy,achieving a significant 17%reduction in the average delivery *** paper offers valuable insights into efficient content delivery in satellite networks,specifically targeting the transmission of remote sensing images,and presents a promising approach to mitigate burst traffic challenges in information-centric environments.

关键词： Information-centric satellite network Burst traffic Content delivery Federated reinforcement learning mixed-integer linear programming model Bloom filter Dynamic network

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Vehicle routing problem under safe separation distance for multiple unmanned aerial vehicle operation

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OPERATIONAL RESEARCH 2022年第5期22卷 5107-5136页

作者： Uhm, Hyun Seop Lee, Young Hoon Yonsei Univ Dept Ind Engn 50 Yonsei Ro Seoul 03722 South Korea

In this work, we present a variant of the vehicle routing problem for multiple unmanned aerial vehicle operation. The problem was described as a multi-depot vehicle routing problem with separation distance constraints, and two mathematical models were developed to find the best routes under capacity, maximum traveling time, and intervehicle separation constraints. In the first model, the separation distance constraint was proposed using a discrete time window based on previous studies, while the second model restricts the relative difference of departure time between every two arcs within the safety distance. Although the second model was designed using the mixed-integer linear programming model, finding acceptable solutions within a limited computation time was a challenge. Therefore, a decomposition heuristic, which divides the second model into a routing step followed by a scheduling step, and a hybrid tabu search algorithm with constructive initial solution generation were suggested. The performance of the suggested algorithms was evaluated for randomly generated graphs in two-dimensional space, and computational experiments showed that the proposed algorithms can be applied to practical cases with enhanced computational efficiency.

关键词： Multi-depot vehicle routing problem Intervehicle separation distance Departure time scheduling mixed-integer linear programming model Decomposition heuristic Hybrid initial solution generation Tabu search heuristic

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modeling and solution methods for hybrid flow shop scheduling problem with job rejection

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OPERATIONAL RESEARCH 2022年第3期22卷 2721-2765页

作者： Dabiri, Mohamadreza Yazdani, Mehdi Naderi, Bahman Haleh, Hassan Islamic Azad Univ Dept Ind Engn Fac Ind & Mech Engn Qazvin Branch Qazvin Iran Univ Windsor Dept Mech Automot & Mat Engn Fac Engn Windsor ON Canada Golpayegan Univ Technol Dept Ind Engn Golpayegan Iran

This paper addresses the hybrid flow shop scheduling problem by considering job rejection to minimize the sum of the total tardiness cost of the scheduled jobs and total cost of the rejected jobs as a single-objective problem. A mixed-integer linear programming model is proposed to solve small-sized problems within an acceptable computational time. Also, this paper exhibits two innovative heuristic algorithms, which are presented to discover fast solutions for the problem along with five meta-heuristics are adapted to solve large-sized problems in the model. Another contribution of this paper is to illustrate the different encoding and decoding methods adapted to algorithms, which are capable of obtaining a feasible schedule and furthermore, to guarantee the efficiency of the solutions based on the schedule. The results obtained from the computational study demonstrate the mathematical model and proposed algorithms effectiveness. Additionally, this paper studies the efficacy of job rejection noting the scheduling for a real-world hybrid flow shop in the tile industry production system. As well as, in this paper, the problem is viewed from a bi-objective problem perspective, so that the tardiness costs of the scheduled jobs and rejection costs of rejected jobs as two objectives are minimized simultaneously to obtain the Pareto solutions. We analyze relationship between the results of the single-objective and bi-objective approaches on small and large-sized problems.

关键词： Scheduling Hybrid flow shop mixed-integer linear programming model Meta-heuristic algorithm Heuristic algorithm

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modeling and optimization algorithm for energy-efficient distributed assembly hybrid flowshop scheduling problem considering worker resources

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JOURNAL OF INDUSTRIAL INFORMATION INTEGRATION 2024年 40卷

作者： Yu, Fei Lu, Chao Yin, Lvjiang Zhou, Jiajun China Univ Geosci Sch Comp Sci Wuhan 430074 Peoples R China Hubei Univ Automot Technol Sch Econ & Management Shiyan 442002 Peoples R China 388 Lumo Rd Wuhan Peoples R China

Considering increasingly serious environmental issues, sustainable development and green manufacturing have received much attention. Meanwhile, with the development of economic globalization and requirement of customization production, distributed hybrid flowshop scheduling problem (DHFSP) and assembly shop problem (ASP) have widely existed in realistic manufacturing systems. In addition to machine resources, worker resources are a key element affecting production efficiency. However, previous studies have not considered the integration mode of DHFSP, ASP, and worker resources in green manufacturing systems. Therefore, this paper focuses on an energy -efficient distributed assembly hybrid flowshop scheduling problem considering worker resources (EDAHFSPW) for the first time. To solve this problem, a mixed -integer linear programming (MILP) model and a multi -objective memetic algorithm (MOMA) are proposed with minimization the total tardiness ( TT D ) and total energy consumption ( TEC ) objectives. In MOMA, a speed -related decoding method is developed to improve the quality of solutions. To generate excellent initial solutions, an initialization strategy is proposed based on problem characteristics. A local search strategy is presented to improve the exploitation capability. An energy -saving strategy is designed to further optimize TEC . Additionally, to validate the proposed MILP model, we implement CPLEX to solve it on 12 small -sized instances. To verify the effectiveness of the proposed MOMA, extensive experiments are conducted to compare with other 5 comparison algorithms on 90 large -sized instances. Experimental results illustrate that MOMA is superior to its competitors.

关键词： Distributed hybrid flowshop scheduling problem Assembly shop problem Worker resources Energy-efficient mixed-integer linear programming model

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Multi-purpose reverse logistics network design for medical waste management in a megacity: Istanbul, Turkey

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Environment Systems and Decisions 2022年第3期42卷 372-387页

作者： Balci, Esin Balci, Sezin Sofuoglu, Aysun Department of Environmental Engineering Izmir Institute of Technology Urla Turkey Cizgi Technology Electronic Design and Manufacturing Inc. Sancaktepe Turkey Department of Chemical Engineering Izmir Institute of Technology Urla Turkey

In the study, a multi-purpose reverse logistics network has been designed to create effectual management of medical waste (MW) generated in 39 districts of Istanbul, a heavily populated city, during the COVID-19 pandemic as well as that to be generated in the next decade. With the model, the medical waste management system in Istanbul is analyzed during the pandemic and for the next 10 years. The model attempts to integrate economic, environmental, and social objectives within the sustainable development goals. It aims to maximize the number of personnel and government earnings for the estimated MW of a megacity while minimizing the total fixed cost and the cost of carbon emissions and transportation. The results indicated that the existing facilities are sufficient for the treatment and disposal of MW generated even under pandemic conditions. However, the capacity of the sterilization facility could be insufficient to treat the estimated amount of MW in the next decade. Opening a sterilization facility near the sanitary landfill in Komurcuoda with a total management cost of 62,450,332 €/year would be an optimum solution for Istanbul MW. In comparison to the single-purpose model results, the multi-purpose model resulted in approximately 42,000 € more in total cost. Sensitivity analyses show that the amount of MW has the most significant effect on the total cost. This simple model created an effective MW management proposal for Istanbul, which can be a model for megacities. © 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

关键词： COVID-19 Medical waste Medical waste management mixed-integer linear programming model Reverse logistics

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