Collaborative supply chain planning under dynamic lot sizing costs with capacity decision

Li, Hongyan; You, Tian-Hui; Luo, Xiaoyi

doi:10.3969/j.issn.1004-4132.2011.02.010

Cited by 4 publications

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A review of discrete-time optimization models for tactical production planning

Díaz‐Madroñero

Peidro

2014

International Journal of Production Research

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This paper presents a review of optimization models for tactical production planning. The objective of this research is to identify streams and future research directions in this field based on the different classification criteria proposed. The major findings indicate that: (1) the most popular production planning area is master production scheduling with a big-bucket time-type period; (2) most of the considered limited resources correspond to productive resources and, to a lesser extent, to inventory capacities; (3) the consideration of backlogs, setup times, parallel machines, overtime capacities and network-type multi-site configuration stand out in terms of extensions; (4) the most widely used modeling approach is linear/integer/mixed integer linear programming solved with exact algorithms, such as branch-and-bound, in commercial MIP solvers; (5) CPLEX, C and its variants and Lindo/Lingo are the most popular development tools among solvers, programming languages and modeling languages, respectively; (6) most works perform numerical experiments with random created instances, while a small number of works were validated by real-world data from industrial firms, of which the most popular are sawmills, wood and furniture, automobile and semiconductors and electronic devices.

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A review of discrete-time optimization models for tactical production planning

Díaz‐Madroñero

Peidro

2014

International Journal of Production Research

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An Approach for Assessing the Applicability of Collaborative Planning Concepts

Küppers¹,

Saalmann

Hellingrath

2015

2015 48th Hawaii International Conference on System Sciences

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Optimal Policy for Controlling Two-Server Queueing Systems with Jockeying

Lin

Bhatnagar

2022

J. of Syst. Eng. Electron.

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This paper studies the optimal policy for joint control of admission, routing, service, and jockeying in a queueing system consisting of two exponential servers in parallel. Jobs arrive according to a Poisson process. Upon each arrival, an admission/routing decision is made, and the accepted job is routed to one of the two servers with each being associated with a queue. After each service completion, the servers have an option of serving a job from its own queue, serving a jockeying job from another queue, or staying idle. The system performance is inclusive of the revenues from accepted jobs, the costs of holding jobs in queues, the service costs and the job jockeying costs. To maximize the total expected discounted return, we formulate a Markov decision process (MDP) model for this system. The value iteration method is employed to characterize the optimal policy as a hedging point policy. Numerical studies verify the structure of the hedging point policy which is convenient for implementing control actions in practice.

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Collaborative supply chain planning under dynamic lot sizing costs with capacity decision

Cited by 4 publications

References 0 publications

A review of discrete-time optimization models for tactical production planning

A review of discrete-time optimization models for tactical production planning

An Approach for Assessing the Applicability of Collaborative Planning Concepts

Optimal Policy for Controlling Two-Server Queueing Systems with Jockeying

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