1,027 research outputs found
An economic order quantity stochastic dynamic optimization model in a logistic 4.0 environment
This paper proposes a stock dynamic sizing optimization under the Logistic 4.0 environment. The safety stock is conceived to fill up the demand variability, providing continuous stock availability. Logistic 4.0 and the smart factory topics are considered. It focuses on vertical integration to implement flexible and reconfigurable smart production systems using the information system integration in order to optimize material flow in a 4.0 full-service approach. The proposed methodology aims to reduce the occurring stock-out events through a link among the wear-out items rate and the downstream logistic demand. The failure rate items trend is obtained through life-cycle state detection by a curve fitting technique. Therefore, the optimal safety stock size is calculated and then validated by an auto-tuning iterative modified algorithm. In this study, the reorder time has been optimized. The case study refers to the material management of a very high-speed train
A New Optimal Stepsize For Approximate Dynamic Programming
Approximate dynamic programming (ADP) has proven itself in a wide range of
applications spanning large-scale transportation problems, health care, revenue
management, and energy systems. The design of effective ADP algorithms has many
dimensions, but one crucial factor is the stepsize rule used to update a value
function approximation. Many operations research applications are
computationally intensive, and it is important to obtain good results quickly.
Furthermore, the most popular stepsize formulas use tunable parameters and can
produce very poor results if tuned improperly. We derive a new stepsize rule
that optimizes the prediction error in order to improve the short-term
performance of an ADP algorithm. With only one, relatively insensitive tunable
parameter, the new rule adapts to the level of noise in the problem and
produces faster convergence in numerical experiments.Comment: Matlab files are included with the paper sourc
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Theory and Practice of Supply Chain Synchronization
In this dissertation, we develop strategies to synchronize component procurement in assemble-to-order (ATO) production and overhaul operations. We focus on the high-tech and mass customization industries which are not only considered to be very important to create or keep U.S. manufacturing jobs, but also suffer most from component inventory burden.
In the second chapter, we address the deterministic joint replenishment inventory problem with batch size constraints (JRPB). We characterize system regeneration points, derive a closed-form expression of the average product inventory, and formulate the problem of finding the optimal joint reorder interval to minimize inventory and ordering costs per unit of time. Thereafter, we discuss exact solution approaches and the case of variable reorder intervals. Computational examples demonstrate the power of our methodology.
In the third chapter, we incorporate stochastic demand to the JRPB. We propose a joint part replenishment policy that balances inventory and ordering costs while providing a desired service level. A case study and guided computational experiments show the magnitudes of savings that are possible using our methodology.
In the fourth chapter, we show how lack of synchronization in assembly systems with long and highly variable component supply lead times can rapidly deteriorate system performance. We develop a full synchronization strategy through time buffering of component orders, which not only guarantees meeting planned production dates but also drastically reduces inventory holding costs. A case study has been carried out to prove the practical relevance, assess potential risks, and evaluate phased implementation policies.
The fifth chapter explores the use of condition information from a large number of distributed working units in the field to improve the management of the inventory of spare parts required to maintain those units. Synchronization is again paramount here since spare part inventory needs to adapt to the condition of the engine fleet. All needed parts must be available to complete the overhaul of a unit. We develop a complex simulation environment to assess the performance of different inventory policies and the value of health monitoring.
The sixth chapter concludes this dissertation and outlines future research plans as well as opportunities
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