scholarly journals Multidimensional Dynamic Programming Algorithm forN-Level Batching with Hierarchical Clustering Structure

2017 ◽  
Vol 2017 ◽  
pp. 1-12
Author(s):  
Seung-Kil Lim ◽  
June-Young Bang ◽  
Jae-Gon Kim
Keyword(s):  
Dynamic Programming ◽  
Hierarchical Clustering ◽  
Programming Model ◽  
Dynamic Programming Algorithm ◽  
Nonlinear Integer Programming ◽  
Batch Size ◽  
Programming Algorithm ◽  
Processing Cost ◽  
Level 1 ◽  
Item Types

This study focuses on theN-level batching problem with a hierarchical clustering structure. Clustering is the task of grouping a set of item types in such a way that item types in the same cluster are more similar (in some sense or another) to each other than to those in other clusters. In hierarchical clustering structure, more and more different item types are clustered together as the level of the hierarchy increases.N-level batching is the process by which items with different types are grouped into several batches passed from level 1 to levelNsequentially for given hierarchical clustering structure such that batches in each level should satisfy the maximum and minimum batch size requirements of the level. We consider two types of processing costs of the batches: unit processing cost and batch processing cost. We formulate theN-level batching problem with a hierarchical clustering structure as a nonlinear integer programming model with the objective of minimizing the total processing cost. To solve the problem optimally, we propose a multidimensional dynamic programming algorithm with an example.

scholarly journals A Hybrid Dynamic Programming for Solving Fixed Cost Transportation with Discounted Mechanism

2016 ◽  
Vol 2016 ◽  
pp. 1-9
Author(s):  
Farhad Ghassemi Tari
Keyword(s):  
Dynamic Programming ◽  
Programming Model ◽  
Transportation Network ◽  
Dynamic Programming Algorithm ◽  
Optimal Solution ◽  
Transportation Cost ◽  
Solution Algorithm ◽  
Transportation Costs ◽  
Programming Algorithm ◽  
Fixed Cost

The problem of allocating different types of vehicles for transporting a set of products from a manufacturer to its depots/cross docks, in an existing transportation network, to minimize the total transportation costs, is considered. The distribution network involves a heterogeneous fleet of vehicles, with a variable transportation cost and a fixed cost in which a discount mechanism is applied on the fixed part of the transportation costs. It is assumed that the number of available vehicles is limited for some types. A mathematical programming model in the form of the discrete nonlinear optimization model is proposed. A hybrid dynamic programming algorithm is developed for finding the optimal solution. To increase the computational efficiency of the solution algorithm, several concepts and routines, such as the imbedded state routine, surrogate constraint concept, and bounding schemes, are incorporated in the dynamic programming algorithm. A real world case problem is selected and solved by the proposed solution algorithm, and the optimal solution is obtained.

scholarly journals The dynamic programming approach to long term production planning in agriculture

2011 ◽  
Vol 59 (2) ◽  
pp. 129-136 ◽  
Author(s):  
Jitka Janová
Keyword(s):  
Dynamic Programming ◽  
Production Planning ◽  
Programming Model ◽  
Dynamic Programming Algorithm ◽  
Optimal Solution ◽  
Goal Function ◽  
Programming Algorithm ◽  
Programming Approach ◽  
Model Case ◽  
Local Character

The production planning in agriculture is one of the most important decision problems of the farmer. Although some decision support tools based mainly on linear programming and addressed to agriculture authorities were presented, their direct application by a farmer is not possible. This is mainly due to the local character of the models developed for particular agricultural conditions and also due to the complexness of underlying mathematical programming models.This paper aims to develop dynamic programming model for the long run crop plan optimization covering the typical conditions of Czech farms, which could serve as a platform for further enlargements and changes according to needs and conditions of particular farm. The dynamic programming algorithm is developed in detail for model case of four areas to be planted by four crops each year. The possibility of covering different constraints by generating the state space is discussed, and the generating procedure for crop rotation rules is shown. The goal function reflects the farmers objective of profit maximization and it is defined with respect to harvests’ randomness. The case study is solved for the data from South Moravian agriculture cooperative and the optimal solution is presented and discussed.

Optimization in Trajectory Planning of Multi-Jointed Fingers in Dextrous Hand Designs

1991 ◽  
Author(s):  
A. Meghdari ◽  
H. Sayyaadi
Keyword(s):  
Dynamic Programming ◽  
Motion Control ◽  
Trajectory Planning ◽  
Degrees Of Freedom ◽  
Optimization Technique ◽  
Dynamic Programming Algorithm ◽  
Programming Algorithm ◽  
Kinematics And Dynamics ◽  
Feasible Solutions ◽  
Dextrous Hand

Abstract An optimization technique based on the well known Dynamic Programming Algorithm is applied to the motion control trajectories and path planning of multi-jointed fingers in dextrous hand designs. A three fingered hand with each finger containing four degrees of freedom is considered for analysis. After generating the kinematics and dynamics equations of such a hand, optimum values of the joints torques and velocities are computed such that the finger-tips of the hand are moved through their prescribed trajectories with the least time or/and energy to reach the object being grasped. Finally, optimal as well as feasible solutions for the multi-jointed fingers are identified and the results are presented.

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