Multi-objective optimization of closed-loop supply chains to achieve sustainable development goals in uncertain environments

Engineering Applications of Artificial Intelligence, Год журнала: 2024, Номер 133, С. 108052 - 108052

Опубликована: Фев. 15, 2024

Язык: Английский

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Challenges and opportunities in green hydrogen supply chain through metaheuristic optimization

Journal of Computational Design and Engineering, Год журнала: 2023, Номер 10(3), С. 1143 - 1157

Опубликована: Апрель 29, 2023

Abstract A comprehensive analysis of the green hydrogen supply chain is presented in this paper, encompassing production, storage, transportation, and consumption, with a focus on application metaheuristic optimization. The challenges associated each stage are highlighted, potential optimization methods to address these discussed. primary method water electrolysis through renewable energy, outlined along importance its Various storage methods, such as compressed gas, liquid hydrogen, material-based covered an emphasis need for improve safety, capacity, performance. Different transportation options, including pipelines, trucks, ships, explored, factors influencing choice different regions identified. consumption their challenges, fuel cell performance optimization, hydrogen-based heating systems design, energy conversion technology choice, also paper further investigates multi-objective approaches problems domain. significant techniques highlighted key addressing improving overall efficiency sustainability respect future trends rapidly advancing area.

Язык: Английский

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Berth allocation and scheduling at marine container terminals: A state-of-the-art review of solution approaches and relevant scheduling attributes

Journal of Computational Design and Engineering, Год журнала: 2023, Номер 10(4), С. 1707 - 1735

Опубликована: Июль 4, 2023

Abstract Marine container terminals play a significant role for international trade networks and global market. To cope with the rapid steady growth of seaborne market, marine terminal operators must address operational challenges appropriate analytical methods to meet needs The berth allocation scheduling problem is one important decisions faced by during operations planning. optimization schedule strongly associated spatial temporal resources. An optimal robust remarkably improves productivity competitiveness seaport. A number studies have been conducted over last years. Thus, there an existing need comprehensive critical literature survey analyze state-of-the-art research progress, developing tendencies, current shortcomings, potential future directions. Therefore, this study thoroughly selected scientific manuscripts dedicated problem. identified were categorized based on attributes, including discrete, continuous, hybrid problems. detailed review was performed categories. representative mathematical formulation each category presented along summary various considerations characteristics every study. specific emphasis given solution adopted. shortcomings outlined state-of-the-art. This expectation assisting community relevant stakeholders scheduling.

Язык: Английский

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Hybrid machine learning-metaheuristic model for sustainable agri-food production and supply chain planning under water scarcity

Resources Environment and Sustainability, Год журнала: 2023, Номер 14, С. 100133 - 100133

Опубликована: Авг. 4, 2023

Agriculture is of great importance in all societies, serving as the fundamental basis for producing food and ensuring survival human populations. The process agricultural production associated logistical elements face numerous difficulties, which are further intensified by worldwide water scarcity resulting from climate change. Nevertheless, existing body literature has not sufficiently addressed consequences on agri-food supply chains. To bridge this research gap contribute to mitigating global crisis induced change, study proposes a hybrid model that combines optimized neural networks based meta-heuristic algorithms mathematical optimization sustainable chain. proposed integrates particle swarm (PSO) feature selection convolutional network (CNN)-gated recurrent unit (GRU) with genetic algorithm (GA) structure predict consumption. Leveraging model's results, multi-objective agriculture chain developed optimize profitability while simultaneously addressing environmental pollutants, waste, usage, manufacturing costs time. evaluate effectiveness approach, real case Iran employed, providing both theoretical practical insights into design incorporates sustainability factors effectively tackles growing challenge scarcity. findings hold implications managers policymakers countries where growing. By integrating advanced techniques predictive models, offers novel framework enhancing chains pressing issues

Язык: Английский

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Optimising post-disaster waste collection by a deep learning-enhanced differential evolution approach

Engineering Applications of Artificial Intelligence, Год журнала: 2024, Номер 132, С. 107932 - 107932

Опубликована: Янв. 31, 2024

In the aftermath of natural disasters, efficient waste collection becomes a crucial challenge, owing to dynamic and unpredictable nature generation, coupled with resource constraints. This paper presents an innovative hybrid methodology that synergizes Long Short-Term Memory (LSTM) machine learning Differential Evolution (DE) optimisation augment efforts post-disaster. The approach leverages real-time data forecast generation high accuracy, facilitating development adaptable strategies. Our is designed dynamically update plans in response evolving scenarios, ensuring timely effective decision-making. Field tests conducted earthquake-prone city have demonstrated superior performance this method managing under fluctuating conditions. Moreover, in-depth sensitivity analysis helps identifying key areas for improvement. Significantly outperforming traditional models, offers substantial time savings equips disaster teams robust tool addressing challenges collection.

Язык: Английский

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An integrated queueing-inventory-routing problem in a green dual-channel supply chain considering pricing and delivery period: a case study of construction material supplier

Journal of Computational Design and Engineering, Год журнала: 2022, Номер 9(5), С. 1917 - 1951

Опубликована: Авг. 30, 2022

Abstract The current paper presented a stochastic integrated queueing-inventory-routing problem into green dual-channel supply chain considering an online retailer with vehicle-routing (VRP) and traditional retailing channel M/M/C queueing system. A mixed-integer non-linear programming model (MINLP) is to address the VRP suggested makes decisions about optimal routing, delivery time interval customers, number of servers in retailers, inventory replenishment policies, retailers’ price. For first time, this considers two channels simultaneously under different uncertainty, including demand, lead service customers. also follows continuous-time Markov chain. small-scale test problems are solved using GAMS software. Since NP-hard, study conducts comprehensive comparative analysis performance 13 metaheuristics. ant lion optimiser, dragonfly algorithm, grasshopper optimisation Harris-hawks optimisation, moth-flame multi-verse optimizer, sine cosine salp-swarm whale grey-wolf genetic differential evolution, particle swarm optimization algorithms that were chosen for study. Comprehensive statistical tests conducted evaluate these methods. Furthermore, executed construction material producers as case Finally, sensitivity analyses on crucial parameters; managerial insights recommended.

Язык: Английский

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Designing a New Location-Allocation and Routing Model with Simultaneous Pick-Up and Delivery in a Closed-Loop Supply Chain Network under Uncertainty

Logistics, Год журнала: 2023, Номер 7(1), С. 3 - 3

Опубликована: Янв. 10, 2023

Background: In this paper, a new closed-loop supply chain (CLSC) network model, including economic, social and environmental goals, is designed. This paper’s primary purpose to meet customers’ uncertain demands in different scenarios where the robust-fuzzy-probabilistic method has been used estimate exact demand. Furthermore, strategic tactical decisions, such as vehicle routing, facility location optimal flow allocation CLSC network, are considered, features queuing system product distribution time window delivery considered. Methods: To solve problem, NSGA II MOPSO have used. Results: The results of solving numerical examples larger sizes show that effects decrease increase, design costs total (SCN) increase. Moreover, more efficient than problem-solving achieving comparison indicators. Conclusions: sensitivity analysis with increasing uncertainty rate, SCN, amount greenhouse gas emissions maximum traffic

Язык: Английский

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An integrated decision model for managing hospital evacuation in response to an extreme flood event: A case study of the Hawkesbury‐Nepean River, NSW, Australia

Safety Science, Год журнала: 2022, Номер 155, С. 105867 - 105867

Опубликована: Июль 5, 2022

Язык: Английский

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Vehicle and UAV Collaborative Delivery Path Optimization Model

Mathematics, Год журнала: 2022, Номер 10(20), С. 3744 - 3744

Опубликована: Окт. 12, 2022

In the context of frequent public emergencies, emergency logistics distribution is particularly critical, and because unique advantages unmanned aerial vehicles (UAVs), model coordinated delivery UAVs gradually becoming an essential form distribution. However, omission start-up costs prevents cost UAV battery replacement sorting, assembly verification packages from being factored into total cost. Furthermore, most existing models focus on route optimization cost, which cannot fully reflect customer’s desire for service satisfaction under conditions. It necessary to convert unsatisfactory degree time window a penalty rather than constraint. Additionally, there lack analysis mutual waiting between when one them performing tasks. Considering effects window, customer demand, maximum load capacity, duration benefits, we propose collaborative path minimize A genetic algorithm used obtain solution constraints subloops, order, take-off landing nodes. To assess efficacy vehicle model, this paper employs county-level district in Xi’an city as pilot area delivery. Compared with vehicle-alone UAV-alone vehicle-UAV can significantly reduce utilization while also lowering Thus, effectively improve timeliness satisfaction. The 39.2% less that 16.5% model. Although its slightly higher reduction decrease overall by 11.8%. This suggests cut all sizes conserve half resources vehicles, employing preferable. Moreover, integrating etc., more express requirements

Язык: Английский

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Evaluating the Role of Urban Drainage Flaws in Triggering Cascading Effects on Critical Infrastructure, Affecting Urban Resilience

Infrastructures, Год журнала: 2022, Номер 7(11), С. 153 - 153

Опубликована: Ноя. 11, 2022

The urban drainage system plays an important role in the infrastructure resilience discussion. Its functional failures can trigger cascading effects on other systems and critical infrastructures. main aim of this work is to investigate quantify flood resilience, offering integrated methodological approach. In process, flooding consequences were quantified by hydrodynamic simulations, using a case study exploratory research method. A set indicators was proposed map generated floods consequent quantification resilience. Two simulation scenarios validate assessment framework work. first scenario represented current situation showed negative city resulting from disordered growth. second considered improvement behavior, considering sustainable approach supported concept blue-green with open spaces system. comprehensive over time conducted analyzing evolution System Integrity Index both scenarios. results that water dynamics play ordering land use preserving efficiently respond developing threats, dealing earlier development moment, proving importance as preliminary structuring driver for supporting planning, ordered according environmental constraints defined dynamics.

Язык: Английский

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