this paper considers a two-stage assembly flow shop problem (tafsp) where m machines are in the first stage and an assembly machine is in the second stage. the objective is to minimize a weighted sum of earliness and tardiness time for n available jobs. jit seeks to identify and eliminate waste components including over production, waiting time, transportation, inventory, movement and defective...

The nested partitions method is a flexible and effective framework of optimizing large-scale problems with combinatorial structure. In this paper we consider the nested partitions method for simulation optimization and propose a new variant that uses inheritance to speed convergence. The new nested partitions method with inheritance algorithm performs well for when applied to test problems but ...

Markovian models and their analysis techniques accomplish an important function in evaluating reliability/ availability in complex engineering systems. Markovian modeling is essentially associated with constant rate of transition from one state to another state of the system and is strictly applicable to exponential distributions. When a more general form for the distribution of a system compon...

A two-stage method for the computational prediction of the structure of protein-ligand complexes is proposed. Given an experimentally determined structure of the protein, in the first stage a large number of plausible ligand conformations is generated using the fast docking algorithm FlexX. In the second stage these conformations are minimized and reranked using a method based on a classical fo...

There are a large number of methods for solving under-determined linear inverse problem. Many of them have very high time complexity for large datasets. We propose a new method called Two-Stage Sparse Representation (TSSR) to tackle this problem. We decompose the representing space of signals into two parts, the measurement dictionary and the sparsifying basis. The dictionary is designed to app...