An ant colony optimization heuristic for an integrated production and distribution scheduling problem

Chang, Yung-Chia; Li, Vincent C.; Chiang, Chia Ju

doi:10.1080/0305215x.2013.786062

Cited by 56 publications

(30 citation statements)

References 33 publications

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“…Historically, production and distribution subproblems are solved sequentially which often leads to suboptimal solutions, as proved by Chen and Vairaktarakis (2005), Park and Hong (2009), and Chang et al (2014). These studies indicate that integration can lead to a solution improvement between 5% and 20% compared to an uncoordinated approach.…”

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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“…Other heuristic approaches were also utilized for production-distribution scheduling or planning problems. Chang et al (2014) used an ant colony optimization heuristic to solve a joint production-distribution schedule with parallel machines and capacitated vehicles by make-to-order strategy. Toptal et al (2013) proposed a tabu search heuristic for a joint production and transportation planning problem in which two vehicle types for outbound shipment were considered.…”

Section: Literature Reviewmentioning

confidence: 99%

Integrated scheduling of a multi-product multi-factory manufacturing system with maritime transport limits

Sun

Chung

Chan

2015

Transportation Research Part E: Logistics and Transportation Re

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“…To our best knowledge, Chen (2010) is the only comprehensive review on integrated production and outbound distribution scheduling problems within a single time period. There have been considerable studies conducted in production-transportation integration with emphasis on the road transportation and vehicle routing problem (Chang and Lee, 2004;Chang et al, 2014;Chen et al, 2009;Hunter and Van Buer, 1996;Lee and Chen, 2001;Li et al, 2005a;Tang and Liu, 2009;Van Buer et al, 1999;Xuan, 2011;Zhong et al, 2007). Hunter and Van Buer (1996) are among the pioneers who studied integrated production and distribution problem (IPDP) on serving multiple products to multiple customers.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Li et al (2008) addressed a coordinated scheduling problem of parallel machine assembly manufacturing and multi-destination transportation in the make-to-order consumer electronics supply chain. Chang et al (2014) considered an integrated production and distribution scheduling problem in which jobs are first processed by one of the unrelated parallel machines and then distributed to corresponding customers by capacitated vehicles without intermediate inventory. The objective is to find a joint production and distribution schedule so that the weighted sum of total weighted job delivery time and the total distribution cost is minimized.…”

Section: Literature Reviewmentioning

confidence: 99%

Batch delivery scheduling of trucks integrated with parallel machine schedule of job orders from multi-customers

Joo

Kim

2018

JAMDSM

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This article considers an integration of two-echelon supply chain management (SCM) problem between a manufacturing site and customers. In the first echelon, jobs ordered by a number of customers are arranged and manufactured by one of a number of identical parallel machines. In the second, jobs are grouped by customer in batches and then delivered via trucks with a limited capacity. The problem is to determine batch delivery schedule of identical trucks. The batch delivery schedule is integrated with a parallel machine schedule of job orders from multi-customers. So, the objective of the problem is to simultaneously determine machine scheduling, batching and truck delivery scheduling to the corresponding customer to minimize the delivery completion time of whole the batched jobs. To solve the problem, two approaches are addressed in this article. The first approach uses a mathematical model (mixed integer programming model) to obtain the optimal solution. Since the problem is NP-hard, three kinds of genetic algorithm-based heuristics are proposed to increase solution efficiency for the second approach. The performances of the algorithms are compared using computational experiments with randomly generated examples. The computational experiments illustrate that the one of the proposed algorithms is capable of near-optimal solutions within a reasonable computing time.

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An ant colony optimization heuristic for an integrated production and distribution scheduling problem

Cited by 56 publications

References 33 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

Integrated scheduling of a multi-product multi-factory manufacturing system with maritime transport limits

Batch delivery scheduling of trucks integrated with parallel machine schedule of job orders from multi-customers

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