Coordination of production scheduling and delivery problems with heterogeneous fleet

Low, Chinyao; Chang, Chia Ling; Li, Rong-Kwei; Huang, Chia Ling

doi:10.1016/j.ijpe.2014.02.014

Cited by 50 publications

(36 citation statements)

References 29 publications

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Section: Introductionmentioning

confidence: 99%

“…The most related studies to our work are Low et al (2013Low et al ( , 2014) and Zhang et al (2016). Low et al (2013Low et al ( , 2014 consider an integration of a practical scheduling problem in a DC with a VRP. However, in our paper, an integrated mathematical model is formulated using the terminology of warehousing instead of production related terminology used in the studies of Low et al (2013Low et al ( , 2014).…”

Section: Introductionmentioning

confidence: 99%

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Integration of order picking and vehicle routing in a B2C e-commerce context

et al. 2017

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E-commerce sales are increasing every year and customers who buy goods on the Internet have high service level expectations. In order to meet these expectations, a company's logistics operations need to be performed carefully. Optimizing only internal warehouse processes will often lead to suboptimal solutions. The interrelationship between the order picking process and the delivery process should not be ignored. Therefore, in this study, an order picking problem and a vehicle routing problem with time windows and release dates are solved simultaneously using a single optimization framework. To the best of our knowledge, it is the first time that an order picking problem and a vehicle routing problem are integrated. A mixed integer linear programming formulation for this integrated order picking-vehicle routing problem (OP-VRP) is provided. The integrated OP-VRP is solved for small instances and the results are compared to these of an uncoordinated approach. Computational experiments show that integration can lead to cost savings of 14% on average. Furthermore, higher service levels can be offered by allowing customers to request their orders later and still get delivered within the same time windows.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Integration of order picking and vehicle routing in a B2C e-commerce context

et al. 2017

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“…The works on this problem include a tabu search algorithm by Gendreau, Laporte, Musaraganyi, and Taillard (1999), a new meta-heuristic known as BATA (back-tracking adaptive threshold accepting) by Tarantilis, Kiranoudis, and Vassiliadis (2004), another tabu search (Brandão, 2011), a multistart adaptive memory programming (MAMP) approach and a path re-linking approach (Li, Tian, & Aneja, 2010), a novel Adaptive Memory Programming (AMP) solution approach (Repoussis & Tarantilis, 2010), and a nonlinear mathematical model and two adaptive genetic algorithms (AGAs) (Low, Chang, Li, & Huang, 2014).…”

Section: Literature Reviewmentioning

confidence: 99%

A heuristic approach and a tabu search for the heterogeneous multi-type fleet vehicle routing problem with time windows and an incompatible loading constraint

Wang

Liu

2015

Computers & Industrial Engineering

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“…Nasiri et al (2014) developed a Lagrangian Relaxation approach which was further solved by GA for a three-echelon multi-site production-distribution planning with stochastic demands. In recent year, GA approaches with different features were proposed for integrated production-distribution scheduling problems with heterogeneous fleet consideration (Ullrich, 2013;Low et al, 2014;Hajiaghaei-Keshteli and Aminnayeri, 2014). Other heuristic approaches were also utilized for production-distribution scheduling or planning problems.…”

Section: Literature Reviewmentioning

confidence: 99%