Two-stage robust power cost minimization in a natural gas compressor station

Optimal operation of a compressor station is important since it accounts for 25%to 50%of a company’s total operating budget.In short-term management of a compressor station,handling demand uncertainty is important yet challenging.Previous studies either require precise information about the distribution of uncertain parameters or greatly simplify the compressor model.We build a two-stage robust optimization framework of power cost minimization in a natural gas compressor station with nonidentical compressors.In the first stage,decision variables are the ON/OFF state of each compressor and discharge pressure.The worst-case cost of the second stage is incorporated in the first stage.Firststage decision variables feasibility is discussed and proper feasibility cuts are also proposed for the first stage.We employ a piece-wise approximation and propose accelerate methods.Our numerical results highlight two advantages of robust approach when managing uncertainty in practical settings:(1)the feasibility of first-stage decision can be increased by up to 45%,and(2)the worst-case cost can be reduced by up to 25%compared with stochastic programming models.Furthermore,our numerical experiments show that the designed accelerate algorithm has time improvements of 1518.9%on average(3785.9%at maximum).

A systematic review of a digital twin city: A new pattern of urban governance toward smart cities

Many countries and governments consider smart cities a solution to global warming,population growth,and resource depletion.Numerous challenges arise while creating a smart city.Digital twins,along with the Internet of Things,fifth-generation wireless systems,blockchain,collaborative computing,simulation,and artificial intelligence technologies,offer great potential in the transformation of the current urban governance paradigm toward smart cities.In this paper,the concept of a digital twin city(DTC)is proposed.The characteristics,key technologies,and application scenarios of a DTC are elaborated upon.Further,we discuss the theories,research directions,and framework regarding DTCs.

DEMAND ESTIMATION AND ASSORTMENT PLANNING IN WIRELESS COMMUNICATIONS

This paper provides an efficient and useful approach for demand estimation and assortment planning of cell phone cards in wireless communication industry. We use maximum likelihood estimation to estimate the primary demand and substitution probability of each cell phone card based on historical sales data. This estimation model is nonlinear, so we transform it to a mixed integer linear programming model by logarithmic transformations and piecewise＇linear approximation. On the basis of the estimation results, we can make assortment planning. Considering the resource of cell phone cards is limited, we jointly optimize the assortment and quantity planning of cell phone cards. In numerical study, we apply our approach to a large mobile service provider in China and frod our approach can increase the revenue of this mobile service provider by 23.69%. Sensitivity analysis shows the mobile service provider should provide more assortments to increase revenue when the types of cell phone cards that can be assigned to each store are limited.

Digital twin-driven smart supply chain

Today’s supply chain is becoming complex and fragile.Hence,supply chain managers need to create and unlock the value of the smart supply chain.A smart supply chain requires connectivity,visibility,and agility,and it needs be integrated and intelligent.The digital twin(DT)concept satisfies these requirements.Therefore,we propose creating a DT-driven supply chain(DTSC)as an innovative and integrated solution for the smart supply chain.We provide background information to explain the DT concept and to demonstrate the method for building a DTSC by using the DT concept.We discuss three research opportunities in building a DTSC,including supply chain modeling,real-time supply chain optimization,and data usage in supply chain collaboration.Finally,we highlight a motivating case from JD.COM,China’s largest retailer by revenue,in applying the DTSC platform to address supply chain network reconfiguration challenges during the COVID-19 pandemic.