Modeling the supply chain configuration problem with resource constraints

Li, Haitao; Womer, Keith

doi:10.1016/j.ijproman.2007.08.004

Cited by 40 publications

(19 citation statements)

References 12 publications

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“…Li and Womer [121] employ the mode concept to take quality considerations into account. Each mode m of an activity j is associated with a quality γ jm .…”

Section: Multiple Modesmentioning

confidence: 99%

A survey of variants and extensions of the resource-constrained project scheduling problem

Hartmann

Briskorn

2010

European Journal of Operational Research

738

356

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“…Li and Womer [121] employ the mode concept to take quality considerations into account. Each mode m of an activity j is associated with a quality γ jm .…”

Section: Multiple Modesmentioning

confidence: 99%

A survey of variants and extensions of the resource-constrained project scheduling problem

Hartmann

Briskorn

2010

European Journal of Operational Research

738

356

View full text Add to dashboard Cite

“…Also, Li and Womer [35] employed the mode concept to take quality considerations into account and whose goal is to find the reliability of a node in the supply chain. Tiwari et al [36] proposed a model in which an activity may be started in a mode that does not allow completing the activity at a required quality level.…”

Section: Multi-mode Resource Constrained Project Scheduling Problemmentioning

confidence: 99%

An Entropy-Based Upper Bound Methodology for Robust Predictive Multi-Mode RCPSP Schedules

Chen¹,

Liang

Padilla

2014

Entropy

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Abstract:Projects are an important part of our activities and regardless of their magnitude, scheduling is at the very core of every project. In an ideal world makespan minimization, which is the most commonly sought objective, would give us an advantage. However, every time we execute a project we have to deal with uncertainty; part of it coming from known sources and part remaining unknown until it affects us. For this reason, it is much more practical to focus on making our schedules robust, capable of handling uncertainty, and even to determine a range in which the project could be completed. In this paper we focus on an approach to determine such a range for the Multi-mode Resource Constrained Project Scheduling Problem (MRCPSP), a widely researched, NP-complete problem, but without adding any subjective considerations to its estimation. We do this by using a concept well known in the domain of thermodynamics, entropy and a three-stage approach. First we use Artificial Bee Colony (ABC)-an effective and powerful meta-heuristic-to determine a schedule with minimized makespan which serves as a lower bound. The second stage defines buffer times and creates an upper bound makespan using an entropy function, with the advantage over other methods that it only considers elements which are inherent to the schedule itself and does not introduce any subjectivity to the buffer time generation. In the last stage, we use the ABC algorithm with an objective function that seeks to maximize robustness while staying within the makespan boundaries defined OPEN ACCESSEntropy 2014, 16 5033 previously and in some cases even below the lower boundary. We evaluate our approach with two different benchmarks sets: when using the PSPLIB for the MRCPSP benchmark set, the computational results indicate that it is possible to generate robust schedules which generally result in an increase of less than 10% of the best known solutions while increasing the robustness in at least 20% for practically every benchmark set. And, in an attempt to solve larger instances with 50 or 100 activities, we also used the MRCPSP/max benchmark sets, where the increase of the makespan is approximately 35% with respect to the best known solutions at the same time as with a 20% increase in robustness.

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“…The objective of their model was to obtain the optimal options and inventory policy for each stage by minimising the total cost and maximising the fulfilment of target service levels. Li and Womer (2008) extended the model of Graves and Willems by taking the level of quality and resource constraints into consideration and its target was to minimise the cycle time of the development of a new product. They used a constraint programming (CP) approach to model and solve the supply chain configuration problem under resource constraints.…”

Section: Literature Reviewmentioning

confidence: 99%

Partner selection model for design chain collaboration

Chen

Chiang

Guo

2013

International Journal of Production Research

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Due to increasing global competition and shorter new product life cycles, brand owners collaborate more often with design chain partners to bring a new product to market. This paper proposes a design partner selection model to minimise the overall design chain cost, taking into account communication cost, time-tomarket, and quality. The model can be formulated as a stagecoach problem. Next, a dynamic programming algorithm is developed for this model to select the optimal partners through the design chain. Finally, a numerical example and a sensitivity analysis are presented. The results also reveal that design quality and manufacturing quality positively influence the total cost, and when brand owners need to speed up timeto-market to keep up with a competitor, the design quality will become less important.

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Modeling the supply chain configuration problem with resource constraints

Cited by 40 publications

References 12 publications

A survey of variants and extensions of the resource-constrained project scheduling problem

A survey of variants and extensions of the resource-constrained project scheduling problem

An Entropy-Based Upper Bound Methodology for Robust Predictive Multi-Mode RCPSP Schedules

Partner selection model for design chain collaboration

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