RETRACTED ARTICLE: Two-echelon electric vehicle routing problem with a developed moth-flame meta-heuristic algorithm

Goli, Alireza; Golmohammadi, Amir-Mohammad; Verdegay, J. L.

doi:10.1007/s12063-022-00298-0

Cited by 54 publications

(27 citation statements)

References 20 publications

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“…Determining the optimal size of the production batch in such a way that the total costs are minimized has always been one of the main topics of scientifc and industrial research [21][22][23]. In addition, nowadays, in industrial units, due to the competitiveness of production and the need to reduce costs and deliver goods on time, equipment availability and the prevention of unexpected stops are of particular importance.…”

Section: Discussionmentioning

confidence: 99%

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A New Mathematical Model for Economic Ordering with Preventive Maintenance and Reworking in a Supply Chain

Ding

Kaliyaperumal

Wang

2023

Discrete Dynamics in Nature and Society

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Cost reduction in production systems is one of the main concerns of most manufacturing industries. Achieving this goal requires the effective use of resources. Nowadays, due to the competitiveness of production and the need to reduce costs and deliver goods on time, equipment availability and prevention of unexpected stops are particularly important in industrial units. In recent years, equipment, machinery, and human resources have been the foundations of any organization. On the other hand, to increase the productivity and efficiency of providing services and achieve global standards, special attention should be paid to increase the efficiency of machinery and reducing downtime costs. This research conducted a mathematical formulation to find the best possible solution for the economic production quantity and inventory ordering by considering preventive maintenance. In this model, the success of organizations in providing services and increasing the quality depends on various reasons, such as maintenance and repair systems. In the proposed model, the defective items are considered, and the goal is to achieve an optimal amount of production in such a way that the costs of the entire system, including production cost, setup, maintenance, inspection, and rework costs, are minimized during a period per unit of time. The numerical results show that increasing the preventive maintenance periods leads to an upward trend in the total cost of the supply chain. Moreover, the sensitivity analysis shows that the longer the preventive maintenance on the machine, the higher reliability of the system as well as total costs will be achieved.

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Section: Discussionmentioning

confidence: 99%

“…PM Const and Repairs per Unit of Time. Te cost of performing preventive maintenance and repairs on the machine during a period per unit of time is equal to equation (23).…”

Section: Production Cost Per Unit Of Timementioning

confidence: 99%

A New Mathematical Model for Economic Ordering with Preventive Maintenance and Reworking in a Supply Chain

Ding

Kaliyaperumal

Wang

2023

Discrete Dynamics in Nature and Society

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“…The essential products were transported from a central storage to satellite stations at the first level. These products were provided to various clients at the second level (Goli et al, 2022b). Likewise, the study investigated the impact of climate change and energy policies on the Australia's future energy system.…”

Section: Literature Reviewmentioning

confidence: 99%

Predicting energy consumption through the LEAP model based on LMDI technique along with economic analysis: A case study

Abbas,

Waqas,

Lun

et al. 2023

Energy Exploration & Exploitation

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This research reports the implementation of logarithmic mean Divisia index (LMDI) and categorizes the growth of total energy usage in three different industrial sectors for the years of 2010 to 2021. Furthermore, it classifies and evaluates the factors influencing on energy consumption in Punjab province thru a sustainable way. The growth consumption is classified into scale influence, structure influence, and efficiency influence. Likewise, the long-term energy alternatives planning-Punjab model is executed with the energy consumption, scale impact, structure impact, and efficiency impact. Besides, comprehensive adjustment scenarios are also introduced to examine the impact of three different factors on overall energy usage. The results from the qualitative decomposition of LMDI indicate that the high scale can lead to high-energy consumption in Punjab Province. However, it can be reduced by high-efficiency reinforcement. The total energy consumption in 2024, 2036, and 2044 under reference scenario is 304.12, 460.01, and 590.04 million tons compared to structure influence analysis for slow terminology (SIAS) and comprehensive scenario. For that reason, it can predict and provide earlier energy management planning for the province. Conversely, the structure factor does not display obvious effect on the energy use. Equally, the quantitative results of the long-term energy alternative planning (LEAP) model are relatively consistent with those of LMDI model, whose advantageous impact on the structure influence is reasonably extrapolated. This phenomenon indicates that the structure influence and efficiency influence will maintain the disruptive impact on increasing overall energy use for the future perspectives. Consequently, the LEAP model predicts the energy consumption of Punjab Province among the years of 2020 to 2040 under medium-term development framework.

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“…Moreover, utilizing a discrete-events simulation analysis, they evaluated the assembly line behavior based on the dynamic model, using a stochastic approach. The focus of the research in this area has been on proposing metaheuristic methods and competitive algorithms like evolution strategies and ANNs, grouping evolution strategies, particle swarm optimization, honey bee optimization, genetic algorithms, beam search algorithm, differential evolution approach, ant colony algorithm, and local search algorithm, in the recent decade [ 10 , [22] , [23] , [24] , [25] , [26] , [27] , [28] , [29] , [30] , [31] ]. In addition to the mentioned literature, several exact methods like the branch & bound [ 32 ], linear programming [ 33 ], dynamic programming [ 34 ], integer programming [ 35 ], and mixed-integer programming [ 36 ], were proposed to solve different types of ALBPs.…”

Section: Introductionmentioning

confidence: 99%

A novel competitive exact approach to solve assembly line balancing problems based on lexicographic order of vectors

Shavarani

Nejad

et al. 2023

Heliyon

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RETRACTED ARTICLE: Two-echelon electric vehicle routing problem with a developed moth-flame meta-heuristic algorithm

Cited by 54 publications

References 20 publications

A New Mathematical Model for Economic Ordering with Preventive Maintenance and Reworking in a Supply Chain

A New Mathematical Model for Economic Ordering with Preventive Maintenance and Reworking in a Supply Chain

Predicting energy consumption through the LEAP model based on LMDI technique along with economic analysis: A case study

A novel competitive exact approach to solve assembly line balancing problems based on lexicographic order of vectors

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