Multi-objective analysis of an integrated supply chain scheduling problem

Cakici, Eray; Mason, Scott J.; Kurz, Mary E.

doi:10.1080/00207543.2011.578162

Cited by 50 publications

(19 citation statements)

References 33 publications

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“…In a more recent work on deterministic approaches, Cakici et al [13] proposed a MIP approach for multi-objective scheduling of customer orders in an integrated production and distribution system. The problem objective was to optimize the trade-off between total weighted tardiness as a service level measure and total distribution costs.…”

Section: Literature Reviewmentioning

confidence: 99%

Integrated supply, production and distribution scheduling under disruption risks

Sawik

2016

Omega

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Section: Literature Reviewmentioning

confidence: 99%

Integrated supply, production and distribution scheduling under disruption risks

Sawik

2016

Omega

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“…The jobs are processed in batches, and the total size of the jobs in a batch cannot exceed the capacity of the machine [5]. Cakici et al [2] studied the problem of minimizing the total weighted tardiness and total distribution costs in an integrated production and distribution system, and introduced a genetic algorithm [2]. Li et al [22] provided a SA for the problem of integrated production and delivery with one manufacturer and one distributer.…”

Section: Introductionmentioning

confidence: 99%

Minimizing sum of the due date assignment costs, maximum tardiness and distribution costs in a supply chain scheduling problem

Assarzadegan

Rasti−Barzoki

2016

Applied Soft Computing

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“…Recently, a few articles have considered the routing decisions in the integrated problem. Cakici, Mason, and Kurz (2012), Ullrich (2013) and Low, Li, and Chang (2013) consider delivery time windows and take the related time optimization as the objective. Adulyasak, Cordeau, and Jans (2012) and Jha and Shanker (2013) take the total cost as the objective and consider inventory cost in the integrated problem.…”

Section: Introductionmentioning

confidence: 99%

A capacitated vehicle routing problem with order available time in e-commerce industry

Liu

2016

Engineering Optimization

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In this article, a variant of the well-known capacitated vehicle routing problem (CVRP) called the capacitated vehicle routing problem with order available time (CVRPOAT) is considered, which is observed in the operations of the current e-commerce industry. In this problem, the orders are not available for delivery at the beginning of the planning period. CVRPOAT takes all the assumptions of CVRP, except the order available time, which is determined by the precedent order picking and packing stage in the warehouse of the online grocer. The objective is to minimize the sum of vehicle completion times. An efficient tabu search algorithm is presented to tackle the problem. Moreover, a Lagrangian relaxation algorithm is developed to obtain the lower bounds of reasonably sized problems. Based on the test instances derived from benchmark data, the proposed tabu search algorithm is compared with a published related genetic algorithm, as well as the derived lower bounds. Also, the tabu search algorithm is compared with the current operation strategy of the online grocer. Computational results indicate that the gap between the lower bounds and the results of the tabu search algorithm is small and the tabu search algorithm is superior to the genetic algorithm. Moreover, the CVRPOAT formulation together with the tabu search algorithm performs much better than the current operation strategy of the online grocer. ARTICLE HISTORY

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Multi-objective analysis of an integrated supply chain scheduling problem

Cited by 50 publications

References 33 publications

Integrated supply, production and distribution scheduling under disruption risks

Integrated supply, production and distribution scheduling under disruption risks

Minimizing sum of the due date assignment costs, maximum tardiness and distribution costs in a supply chain scheduling problem

A capacitated vehicle routing problem with order available time in e-commerce industry

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