A review of applications of genetic algorithms in operations management
CKH Lee - Engineering Applications of Artificial Intelligence, 2018 - Elsevier
Many decisions in operations management (OM) belong to the class of Non-deterministic
Polynomial hard problems and thus heuristic search methods have been applied to improve …
Polynomial hard problems and thus heuristic search methods have been applied to improve …
A survey on metaheuristics for stochastic combinatorial optimization
Metaheuristics are general algorithmic frameworks, often nature-inspired, designed to solve
complex optimization problems, and they are a growing research area since a few decades …
complex optimization problems, and they are a growing research area since a few decades …
Smart semiconductor manufacturing for pricing, demand planning, capacity portfolio and cost for sustainable supply chain management
Leading nations have re-emphasised the importance of semiconductor manufacturing to
supply chain safety and resilience. Limitations of the existing studies can be traced in part to …
supply chain safety and resilience. Limitations of the existing studies can be traced in part to …
Forecasting agricultural output with an improved grey forecasting model based on the genetic algorithm
SL Ou - Computers and electronics in agriculture, 2012 - Elsevier
Agriculture is the foundation of the national economy. Thus, an appropriate tool for
forecasting agricultural output is very important for policy making. In this study, both modified …
forecasting agricultural output is very important for policy making. In this study, both modified …
A swarm intelligence based sample average approximation algorithm for the capacitated reliable facility location problem
We present a novel hybrid method, swarm intelligence based sample average
approximation (SIBSAA), for solving the capacitated reliable facility location problem …
approximation (SIBSAA), for solving the capacitated reliable facility location problem …
Stochastic programming based capacity planning for semiconductor wafer fab with uncertain demand and capacity
Capacity planning is a challenging problem in semiconductor manufacturing industry due to
high uncertainties both in market and manufacturing systems, short product life cycle, and …
high uncertainties both in market and manufacturing systems, short product life cycle, and …
A review of scenario generation methods
S Mitra, ND Domenica - International Journal of Computing …, 2010 - inderscienceonline.com
Stochastic programming models provide a powerful paradigm for decision making under
uncertainty. In these models the uncertainties are captured by scenario generation and so …
uncertainty. In these models the uncertainties are captured by scenario generation and so …
Collaborative capacity sharing among manufacturers on the same supply network horizontal layer for sustainable and balanced returns
To deal with volatile demand and rapidly changing manufacturing technologies for
sustainable returns, as a solution, collaborative capacity sharing (CCS) among …
sustainable returns, as a solution, collaborative capacity sharing (CCS) among …
Capacity planning with technology replacement by stochastic dynamic programming
Technology replacement is capital intensive and highly risky in fast-paced high-tech
industries along lumpy demand. This article proposes a solution to decision-making related …
industries along lumpy demand. This article proposes a solution to decision-making related …
A novel bi-vector encoding genetic algorithm for the simultaneous multiple resources scheduling problem
To improve capital effectiveness in light of demand fluctuation, it is increasingly important for
high-tech companies to develop effective solutions for managing multiple resources …
high-tech companies to develop effective solutions for managing multiple resources …