Online Network Flow Optimization for Multi-Grade Service Chains

2020 ◽  
Author(s):  
Victor Valls ◽  
George Iosifidis ◽  
Geeth de Mel ◽  
Leandros Tassiulas
Keyword(s):  
Network Flow ◽  
Flow Optimization ◽  
Network Flow Optimization

scholarly journals Cut Redistribution and Insertion for Advanced 1-D Layout Design via Network Flow Optimization

2018 ◽  
Vol 26 (9) ◽  
pp. 1613-1626
Author(s):  
Ye Zhang ◽  
Wenlong Lyu ◽  
Wai-Shing Luk ◽  
Fan Yang ◽  
Hai Zhou ◽  
...  
Keyword(s):  
Network Flow ◽  
Layout Design ◽  
Flow Optimization ◽  
Network Flow Optimization

DISTRIBUTION-BASED OPTION PRICING ON LATTICE ASSET DYNAMICS MODELS

2002 ◽  
Vol 05 (06) ◽  
pp. 599-618 ◽  
Author(s):  
YUJI YAMADA ◽  
JAMES A. PRIMBS
Keyword(s):  
Dynamic Programming ◽  
Option Pricing ◽  
Network Flow ◽  
Stock Price ◽  
Implied Volatility ◽  
Market Model ◽  
Flow Optimization ◽  
Optimal Hedging ◽  
Hedging Problem ◽  
Network Flow Optimization

In this paper, we propose a numerical option pricing method based on an arbitrarily given stock distribution. We first formulate a European call option pricing problem as an optimal hedging problem by using a lattice based incomplete market model. A dynamic programming technique is then applied to solve the mean square optimal hedging problem for the discrete time multi-period case by assigning suitable probabilities on the lattice, where the underlying stock price distribution is derived directly from empirical stock price data which may possess "heavy tails". We show that these probabilities are obtained from a network flow optimization which can be solved efficiently by quadratic programming. A computational complexity analysis demonstrates that the number of iterations for dynamic programming and the number of parameters in the network flow optimization are both of square order with respect to the number of periods. Numerical experiments illustrate that our methodology generates the implied volatility smile.

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