Integrating production scheduling and vehicle routing decisions at the operational decision level: A review and discussion

Moons, Stef; Ramaekers, Katrien; Caris, An; Arda, Yasemin

doi:10.1016/j.cie.2016.12.010

Cited by 156 publications

(72 citation statements)

References 63 publications

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“…Recently, the integration of a production scheduling problem and a VRP at the operational decision level has received more attention in the scientific literature, see e.g., Farahani et al (2012), Amorim et al (2013) and Li et al (2016) among others. A review on and classification of integrated PS-VRPs can be found in Chen (2010) and Moons et al (2017).…”

Section: Introductionmentioning

confidence: 99%

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%

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

et al. 2017

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“…Due to the increasing demand for planning that integrates production and distribution, several optimization models and solution techniques have been proposed to assist in the decision making process at the different hierarchical levels (for example, strategic, tactical and operational). Studies of solution models and methods are available in the literature, e.g., the work by Mula et al (2010) considering strategic and tactical levels; Chen (2010) and Moons et al (2017) at the operational level and Adulyasak et al (2015) at the tactical-operational level.…”

Section: Theorical Referencementioning

confidence: 99%

“…In this sense, the key decisions are to assign customer orders to features, determine the start and end times of each customer order, assign customer orders to delivery vehicles, and define delivery routes and delivery times for each customer order. Therefore, the result is a detailed production and distribution schedule with the exact moment each customer order is executed (MOONS et al, 2017).…”

Section: Theorical Referencementioning

confidence: 99%

Simulation model of a stop production line: the relationship between financial return and productivity

Santos

Garlet

Klein

et al. 2019

Ind. Jour. Manag. & Prod.

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Making innovations to become competitive is not always an easy task, and in the industrial sphere, this thinking becomes even more complex. In this sense, proper use in raw material transformation processes becomes very challenging for managers, since improving processes is a condition where more can be done with less. Thus, many organizations seek to develop improvements through existing activities using a variety of techniques that are addressed in the literature, such as value flow mapping, lean production, simulations, among others. Therefore, this article aims to study and apply the computational simulation, through the use of Tecnomatix Plant Simulation © software, to obtain the best relation between financial return [http://creativecommons.org/licenses/by/3.0/us/] Licensed under a Creative Commons Attribution 3.0 United States Licenseand productivity of a upholstery production line. In the methodology of this work was carried out the structural proposition of five scenarios. For the construction of these, a current scenario of the production line was carried out and for each new scenario, operators were added with new tasks to be performed. Although the final results show a better financial return for scenario three, the results obtained in scenario five are significant in terms of productivity indicators, although the cost with extra operators is much higher than in the other scenarios. Thus, it was clear the relevance of applying simulation in the production line, since the model assisted the managers in the decision making.

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“…A review and discussion on the papers that deal with integrating production scheduling and vehicle routing decisions can be found in Moons et al. ().…”

Section: Related Workmentioning

confidence: 99%

Variable neighborhood search based approaches to a vehicle scheduling problem in agriculture

Anokić

Stanimirović

Davidović

et al. 2017

Int Trans Operational Res

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A vehicle scheduling problem (VSP) that arises from sugar beet transportation within minimum working time under the set of constraints reflecting a real‐life situation is considered. A mixed integer quadratically constrained programming (MIQCP) model of the considered VSP and reformulation to a mixed integer linear program (MILP) are proposed and used within the framework of Lingo 17 solver, producing optimal solutions only for small‐sized problem instances. Two variants of the variable neighborhood search (VNS) metaheuristic—basic VNS (BVNS) and skewed VNS (SVNS) are designed to efficiently deal with large‐sized problem instances. The proposed VNS approaches are evaluated and compared against Lingo 17 and each other on the set of real‐life and generated problem instances. Computational results show that both BVNS and SVNS reach all known optimal solutions on small‐sized instances and are comparable on medium‐ and large‐sized instances. In general, SVNS significantly outperforms BVNS in terms of running times.

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Integrating production scheduling and vehicle routing decisions at the operational decision level: A review and discussion

Cited by 156 publications

References 63 publications

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

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

Simulation model of a stop production line: the relationship between financial return and productivity

Variable neighborhood search based approaches to a vehicle scheduling problem in agriculture

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