An Efficient Modified Red Deer Algorithm to Solve a Truck Scheduling Problem Considering Time Windows and Deadline for Trucks' Departure

Fathollahi-Fard, Amir M.; Ahmadi, Abbas; Sajadieh, Mohsen S.

doi:10.1002/9781119574293.ch6

Cited by 13 publications

(5 citation statements)

References 44 publications

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“…These products are transferred to the outbound dock in order to be loaded into shipping trucks (Fathollahi-Fard et al. 2020 ). Long-term storage is not permitted in cross-docking (Zuluaga et al.…”

Section: Applications Of Rd Algorithmsmentioning

confidence: 99%

“…Modified Red Deer Algorithm was proposed to Solve a Truck Scheduling Problem Considering Time Windows and Deadline for Trucks’ Departure (Fathollahi-Fard et al. 2020 ). The main feature of MRDA is fewer controlling parameters needed, and therefore a better designation is achieved of search phases to find the global solution.…”

Section: Applications Of Rd Algorithmsmentioning

confidence: 99%

“…In Fazli et al (2019) The cross-docking system is for the purpose of product distribution from manufacturers to markets (Berghman et al 2015). These products are transferred to the outbound dock in order to be loaded into shipping trucks (Fathollahi-Fard et al 2020). Long-term storage is not permitted in crossdocking (Zuluaga et al 2017).…”

Section: Applications Of Rd Algorithmsmentioning

confidence: 99%

“…Therefore, an efficient cross-docking will lead to better distribution systems which result in the satisfaction of customers (Boysen and Fliedner 2010). Modified Red Deer Algorithm was proposed to Solve a Truck Scheduling Problem Considering Time Windows and Deadline for Trucks' Departure (Fathollahi-Fard et al 2020). The main feature of MRDA is fewer controlling parameters needed, and therefore a better designation is achieved of search phases to find the global solution.…”

Section: Applications Of Rd Algorithmsmentioning

confidence: 99%

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Review and analysis for the Red Deer Algorithm

Zitar

Abualigah

Al-Dmour

2021

J Ambient Intell Human Comput

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Section: Applications Of Rd Algorithmsmentioning

confidence: 99%

Section: Applications Of Rd Algorithmsmentioning

confidence: 99%

Section: Applications Of Rd Algorithmsmentioning

confidence: 99%

Section: Applications Of Rd Algorithmsmentioning

confidence: 99%

See 2 more Smart Citations

Review and analysis for the Red Deer Algorithm

Zitar

Abualigah

Al-Dmour

2021

J Ambient Intell Human Comput

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“…The fighting between the commanders and stags is considered to improve the exploitation properties for the algorithm. This fighting is controlled by the number of commanders and stags [50]. In this operator, two new solutions are generated as following equations:…”

Section: Encoding Planmentioning

confidence: 99%

Metaheuristics for a bi-objective green vendor managed inventory problem in a two-echelon supply chain network

et al. 2020

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Generally, finding an alternative solution for reducing fossil fuel consumption and green emissions of supply chain networks can shift the Vendor Managed Inventory (VMI) to the Green VMI (GVMI). Our literature search also confirms that the issue of environmental pollution and green emissions, is still scarce and required to be explored. This motivates our attempt to offer the issue of green backorder for the VMI in a two-echelon supply chain network among the first studies. To this end, a bi-objective non-linear optimization model with the goal of maximizing the profit of inventory and minimizing the carbon emissions of transportation, simultaneously, is developed. Another contribution of this work is to propose three capable metaheuristics to solve it optimality in large-scale samples. In this regard, the Nondominated Sorting Genetic Algorithm (NSGA-II) as a well-known method as well as Multi-Objective of Keshtel Algorithm (MOKA) and Multi-Objective of Red Deer Algorithm (MORDA) as two recent nature-inspired algorithms are firstly applied. The outputs confirm that the allowed shortage situation along with the lack of cost reduction shows a greater amount of shipping and orders based on sensitivities. With regards to the comparison among algorithms, the performance of MORDA is highly better than MOKA and NSGA-II.

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