Iterative dynamic programming

Chudoung, Jerawan

doi:10.1016/s0005-1098(03)00079-7

Cited by 3 publications

(1 citation statement)

References 1 publication

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“…Conventional APP problem assumes market demand is crisp value [20], difficulty estimating crisp demand is overcome by using fuzzy demand which also increases estimation flexibility and results in better production plans that increase profits [13], [21]. www.ijacsa.thesai.org Dynamic programming (DP) is a powerful optimization tool for dealing with complex problems involving sequential or multi-stage decision making in many fields [22].…”

Section: Introductionmentioning

confidence: 99%

Dynamic Programming Approach in Aggregate Production Planning Model under Uncertainty

Marfuah¹,

Mutmainah²,

Panudju³

et al. 2023

IJACSA

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In order to achieve a competitive edge in the market, one of the most essential components of effective operations management is aggregate production planning, abbreviated as APP. The sources of uncertainty discussed in the APP model include uncertainty in demand, uncertainty of production costs, and uncertainty of storage costs. The problem of APP usually involves many imprecise, conflicting and incommensurable objective functions. The application of APP in real conditions is often inaccurate, because some information is incomplete or cannot be obtained. The aim of this study is to develop APP model under uncertainty with a dynamic programming (DP) approach to meet consumer demand and minimize total costs during the planning period. The APP model includes several parameters including market demand, production costs, inventory costs, production levels and production capacity. After describing the problem, the optimal APP model is formulated using artificial neural network (ANN) techniques in the demand forecasting process and fuzzy logic (FL) in the DP framework. The ANN technique is used to forecast the input demand for APP and minimize the total cost during the planning period using the FL technique in the DP framework to accommodate uncertainties. The model input is historical data obtained through interviews. A case study was conducted on the the need for aluminum plates for the automotive industry. The results show that the ANN technique proposed for demand projection has a low error value in forecasting demand and FL in the DP framework is able to find minimal production costs in the APP model.

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Section: Introductionmentioning

confidence: 99%

Dynamic Programming Approach in Aggregate Production Planning Model under Uncertainty

Marfuah¹,

Mutmainah²,

Panudju³

et al. 2023

IJACSA

View full text Add to dashboard Cite

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Design of solar-powered forced ventilation system and energy-efficient thermal comfort operation of greenhouse

Revathi

Sivakumaran

Radhakrishnan

2021

Materials Today: Proceedings

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Trajectory optimization of flexible link manipulators in point-to-point motion

2008

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The aim of this paper is to determine the optimal trajectory and maximum payload of flexible link manipulators in point-to-point motion. The method starts with deriving the dynamic equations of flexible manipulators using combined Euler-Lagrange formulation and assumed modes method. Then the trajectory planning problem is defined as a general form of optimal control problem. The computational methods to solve this problem are classified as indirect and direct techniques. This work is based on the indirect solution of open-loop optimal control problem. Because of the offline nature of the method, many difficulties like system nonlinearities and all types of constraints can be catered for and implemented easily. By using the Pontryagin's minimum principle, the obtained optimality conditions lead to a standard form of a two-point boundary value problem solved by the available command in MATLAB R . In order to determine the optimal trajectory a computational algorithm is presented for a known payload and the other one is then developed to find the maximum payload trajectory. The optimal trajectory and corresponding input control obtained from this method can be used as a reference signal and feedforward command in control structure of flexible manipulators. In order to clarify the method, derivation of the equations for a planar two-link manipulator is presented in detail. A number of simulation tests are performed and optimal paths with minimum effort, minimum effort-speed, maximum payload, and minimum vibration are obtained. The obtained results illustrate the power and efficiency of the method to solve the different path planning problems and overcome the high nonlinearity nature of the problems.

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Iterative dynamic programming

Cited by 3 publications

References 1 publication

Dynamic Programming Approach in Aggregate Production Planning Model under Uncertainty

Dynamic Programming Approach in Aggregate Production Planning Model under Uncertainty

Design of solar-powered forced ventilation system and energy-efficient thermal comfort operation of greenhouse

Trajectory optimization of flexible link manipulators in point-to-point motion

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