A novel two-echelon hierarchical location-allocation-routing optimization for green energy-efficient logistics systems

Tirkolaee, Erfan Babaee; Goli, Alireza; Mardani, Abbas

doi:10.1007/s10479-021-04363-y

Cited by 42 publications

(17 citation statements)

References 58 publications

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“…Real-coded memetic algorithms have also been presented to solve optimisation problems with continuous variables [36,39]. Like a location routing problem that combines strategic level facility location problem [20,21] and tactical level routing problem [62], an ambulance location-allocation problem combines strategic and tactical level decisions. The problem presented in this work involves a combination of decisions, including station location, demand allocation and ambulance allocation.…”

Section: Solution Methodologymentioning

confidence: 99%

Ambulance location under temporal variation in demand using a mixed coded memetic algorithm

2022

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Emergency medical services (EMS) are among the most important services in any society due to their role in saving people's lives and reducing morbidities. The location of ambulance stations and the allocation of ambulances to the stations is an important planning problem for any EMS system to ensure adequate coverage while minimising the response time. This study considers a mixed-integer programming model that determines the ambulance locations by considering the time of day variations in demand. The presented model also considers heterogeneous performance measures based on survival function and coverage for different patient types with varying levels of urgency. A memetic algorithm based-approach that applies a mixed chromosome representation for solutions is proposed to solve the problem. Our computational results indicate that neglecting time-dependent variation of demand can underestimate the number of ambulances required by up to 15% during peak demand. We also demonstrate the effectiveness of the proposed solution approach in providing good quality solutions within a reasonable time.

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Section: Solution Methodologymentioning

confidence: 99%

Ambulance location under temporal variation in demand using a mixed coded memetic algorithm

2022

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“…In the MCME-LRP-RLN, the negative social utility objective is as importance as the cost objective, but the interpretability is less than the cost objective. Previous studies used carbon emissions, pollution treatment costs, regional development, and negative utility of residents as negative social utility objectives, and the objective functions are more subjective and simpler in form, mostly multiplying or dividing transport distance and transport volume (Ding et al, 2014;Tirkolaee et al, 2021;Pourmohammadi et al, 2021). However, various types of panel data disclosed by business operations offer the possibility of fitting an objective scientific negative utility function.…”

Section: Locationrouting Problemmentioning

confidence: 99%

“…Previous studies used carbon emissions, pollution treatment costs, regional development, and negative utility of residents as negative social utility objectives, and the objective functions are more subjective and simpler in form, mostly multiplying or dividing transport distance and transport volume (Ding et al. , 2014; Tirkolaee et al. , 2021; Pourmohammadi et al.…”

Section: Literature Reviewmentioning

confidence: 99%

A multi-cycle and multi-echelon location-routing problem for integrated reverse logistics

Xiang

Liu

Jiang

et al. 2022

IMDS

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PurposeThe rapid development of smart cities and green logistics has stimulated a lot of research on reverse logistics, and the diversified data also provide the possibility of innovative research on location-routing problem (LRP) under reverse logistics. The purpose of this paper is to use panel data to assist in the study of multi-cycle and multi-echelon LRP in reverse logistics network (MCME-LRP-RLN), and thus reduce the cost of enterprise facility location.Design/methodology/approachFirst, a negative utility objective function is generated based on panel data and incorporated into a multi-cycle and multi-echelon location-routing model integrating reverse logistics. After that, an improved algorithm named particle swarm optimization-multi-objective immune genetic algorithm (PSO-MOIGA) is proposed to solve the model.FindingsThere is a paradox between the total cost of the enterprise and the negative social utility, which means that it costs a certain amount of money to reduce the negative social utility. Firms can first design an open-loop logistics system to reduce cost, and at the same time, reduce negative social utility by leasing facilities.Practical implicationsThis study provides firms with more flexible location-routing options by dividing them into multiple cycles, so they can choose the right option according to their development goals.Originality/valueThis research is a pioneering study of MCME-LRP-RLN problem and incorporates data analysis techniques into operations research modeling. Later, the PSO algorithm was incorporated into the crossover of MOIGA in order to solve the multi-objective large-scale problems, which improved the convergence speed and performance of the algorithm. Finally, the results of the study provide some valuable management recommendations for logistics planning.

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“…Mashud et al [28] developed a sustainable retailer inventory model by investing in PT and green technology (GT) to control the deterioration rate and greenhouse gases emissions, respectively. A two-echelon location routing problem for green energy efficiency logistics systems was investigated by Tirkolaee et al [53]. However, the impact of the present COVID-19 pandemic on deterioration rate has not been considered in their model.…”

Section: Introductionmentioning

confidence: 99%

Impacts of green and preservation technology investments on a sustainable EPQ model during COVID-19 pandemic

Barman

Pervin²,

Roy

2022

RAIRO-Oper. Res.

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Carbon and Sulfur dioxides emissions are the key issues of global warming that affects on human health. Emissions cap- and -trade policy is a key mechanism implemented in several countries to reduce the emissions. Nowadays, public gathering is restricted due to the pandemic situation caused by COVID-19. As a result, people are facing huge problems in their regular activities and lifestyle. During the lockdown periods, demands for few merchandises decrease and the deterioration rate increases. Moreover, because of the unavailability of raw materials and labours during the lockdown, shortages occur at the manufacturing company. Keeping these problems in mind, a multi-objective sustainable economic production quantity model is proposed with partially back-ordering shortages, in which the effects of sustainability are investigated. To handle the demand fluctuation throughout the current pandemic, emergency level dependent demand rate is assumed. To reduce greenhouse gases emissions and deterioration rate, investments in green technology and preservation technology efforts are used. The objectives of this study are to maximize the manufacturer’s profit and minimize the greenhouse gases emissions for producing green products. The multi-objective model is solved by utilizing the fuzzy goal programming approach. The mathematical model is illustrated by four numerical examples. The main finding of the work is that under both green and preservation technologies investments, a sustainable model with partially back-ordering shortages and lockdown level dependent demand rate decreases justifiable greenhouse gases emissions and increases the product’s greening level. The results indicate that the system profit is increased by 16.1% by investing in both preservation and green technology. Furthermore, a sensitivity analysis is performed along with some managerial insights for practitioners. Finally, the paper is ended with conclusions and future research tips.

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A novel two-echelon hierarchical location-allocation-routing optimization for green energy-efficient logistics systems

Cited by 42 publications

References 58 publications

Ambulance location under temporal variation in demand using a mixed coded memetic algorithm

Ambulance location under temporal variation in demand using a mixed coded memetic algorithm

A multi-cycle and multi-echelon location-routing problem for integrated reverse logistics

Impacts of green and preservation technology investments on a sustainable EPQ model during COVID-19 pandemic

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