Multi-commodity flow problems（MCFs） can be found in many areas, such as transportation, communication, and logistics. Therefore, such problems have been studied by a multitude of researchers, and a variety of method...Multi-commodity flow problems（MCFs） can be found in many areas, such as transportation, communication, and logistics. Therefore, such problems have been studied by a multitude of researchers, and a variety of methods have been proposed for solving it. However, most researchers only discuss the properties of different models and algorithms without taking into account the impacts of actual implementation. In fact, the true performance of a method may differ greatly across various implementations. In this paper, several popular optimization solvers for implementations of column generation and Lagrangian relaxation are discussed. In order to test scalability and optimality, three groups of networks with different structures are used as case studies. Results show that column generation outperforms Lagrangian relaxation in most instances, but the latter is better suited to networks with a large number of commodities.展开更多
Utility maximization is a major priority of prosumers participating in peer-to-peer energy trading and sharing(P2P-ETS).However,as more distributed energy resources integrate into the distribution network,the impact o...Utility maximization is a major priority of prosumers participating in peer-to-peer energy trading and sharing(P2P-ETS).However,as more distributed energy resources integrate into the distribution network,the impact of the communication link becomes significant.We present a multi-commodity formulation that allows the dual-optimization of energy and communication resources in P2P-ETS.On one hand,the proposed algorithm minimizes the cost of energy generation and communication delay.On the other hand,it also maximizes the global utility of prosumers with fair resource allocation.We evaluate the algorithm in a variety of realistic conditions including a time-varying communication network with signal delay signal loss.The results show that the convergence is achieved in a fewer number of time steps than the previously proposed algorithms.It is further observed that the entities with a higher willingness to trade the energy acquire more satisfactions than others.展开更多
The commodity transportation capacity between all origin-destination （ OD ） pairs over the multimodal multi-commodities freight transportation network （MMFTN） is determined. A multi-ob- jectives mathematical model...The commodity transportation capacity between all origin-destination （ OD ） pairs over the multimodal multi-commodities freight transportation network （MMFTN） is determined. A multi-ob- jectives mathematical model is formulated for determining the OD capacity over the MMFTN accord- ing to a transporting capacity matrix that increased from the reference matrixes. The corresponding incremental factor for estimating the capacity matrix is obtained via the maximal likelihood estima- tion method that samples data of differences between the estimated commodity volumes and carrying capacities of the critical links. The proposed formulations are tested by an experimental highway and railroad freight transportation network in an existing literature. The relevant results of OD capacities are displayed and applicability of the algorithm is certified.展开更多
A simulation approach of a smart grid by cooperative bargaining is presented in this paper. Each participant of the smart grid determines its optimal schedule to meet its power and heating demand at minimal costs empl...A simulation approach of a smart grid by cooperative bargaining is presented in this paper. Each participant of the smart grid determines its optimal schedule to meet its power and heating demand at minimal costs employing solar panels, fuel cells and batteries. This is done by solving a quadratic optimisation problem which takes the energy prices and the available devices into account. The energy prices are related to the demand and supply in the smart grid, so that a lower demand yields lower prices. The cooperative bargaining game is used to tune the participants’ optimal solution to obtain a Nash equilibrium. The computed solutions of the participants are validated against the capacities and structure of the smart grid by solving a multi-commodity flow problem. The presented model features multiple types of energy, so that they may be substituted to meet the participants’ demand. Furthermore, the participants may also act as supplier and not only as consumer, which allows decentralised generation of energy. The approach is validated in several experiments where effects like negative energy prices if generated energy exceeds the smart grid’s total demand and peak-shaving with even small-capacity batteries are exhibited.展开更多
Air transportation is often affected by disruptions,both in the form of disasters that are caused by human error or natural phenomena.Such disruptions primarily affect passengers,in the form of travel delays and fligh...Air transportation is often affected by disruptions,both in the form of disasters that are caused by human error or natural phenomena.Such disruptions primarily affect passengers,in the form of travel delays and flight cancellations.Recovering airline schedules after disruptive events is particularly challenging for airlines due to unavailability of flights and/or their reduced capacity to address the demands of the affected passengers.In this work,we propose a multimodal rescheduling approach for airline passengers whose travel is disrupted by natural phenomena,such as hurricanes and tropical storms.The objective is to identify an optimal route,which may involve a combination of air and road travel,that minimizes system-level airline costs.The multimodal approach proposed here includes a multi-commodity network flow model where different origin-destination pairs for different travelers are treated as the different commodities.We incorporate transportation network risk in the form of a family of hop/risk side constraints.We test our approach on a simulated toy network and then proceed to use publicly available data to compare different airport network structures.The results from our computational study show that certain airline passengers may experience more inconvenience in comparison to others depending on the airport network topology of a specific airline.展开更多
In this paper the definition of domination is generalized to the case that the elements of the traffic matrices may have negative values. It is proved that D3 dominates D3 ＋ λ（D2 - D1） for any λ ≥0 if D1 dominat...In this paper the definition of domination is generalized to the case that the elements of the traffic matrices may have negative values. It is proved that D3 dominates D3 ＋ λ（D2 - D1） for any λ ≥0 if D1 dominates D2. Let u（D） be the set of all the traffic matrices that are dominated by the traffic matrix D. It is shown that u （ D∞） and u （D ∈） are isomorphic. Besides, similar results are obtained on multi-commodity flow problems. Fhrthermore, the results are the generalized to integral flows.展开更多
基金supported by research funds from the National Natural Science Foundation of China (Nos. 61521091, 61650110516, 61601013)
文摘Multi-commodity flow problems（MCFs） can be found in many areas, such as transportation, communication, and logistics. Therefore, such problems have been studied by a multitude of researchers, and a variety of methods have been proposed for solving it. However, most researchers only discuss the properties of different models and algorithms without taking into account the impacts of actual implementation. In fact, the true performance of a method may differ greatly across various implementations. In this paper, several popular optimization solvers for implementations of column generation and Lagrangian relaxation are discussed. In order to test scalability and optimality, three groups of networks with different structures are used as case studies. Results show that column generation outperforms Lagrangian relaxation in most instances, but the latter is better suited to networks with a large number of commodities.
基金This work was supported in part by the Peer-to-peer Energy Trading and Sharing-3M(multi-times,multi-scales,multi-qualities)project funded by EPSRC(No.EP/N03466X/1)in part,by ENERGY-IQ,a UK-Canada Power Forward Smart Grid Demonstrator project funded by The Department for Business,Energy and Industrial Strategy(BEIS)(No.7454460).
文摘Utility maximization is a major priority of prosumers participating in peer-to-peer energy trading and sharing(P2P-ETS).However,as more distributed energy resources integrate into the distribution network,the impact of the communication link becomes significant.We present a multi-commodity formulation that allows the dual-optimization of energy and communication resources in P2P-ETS.On one hand,the proposed algorithm minimizes the cost of energy generation and communication delay.On the other hand,it also maximizes the global utility of prosumers with fair resource allocation.We evaluate the algorithm in a variety of realistic conditions including a time-varying communication network with signal delay signal loss.The results show that the convergence is achieved in a fewer number of time steps than the previously proposed algorithms.It is further observed that the entities with a higher willingness to trade the energy acquire more satisfactions than others.
文摘The commodity transportation capacity between all origin-destination （ OD ） pairs over the multimodal multi-commodities freight transportation network （MMFTN） is determined. A multi-ob- jectives mathematical model is formulated for determining the OD capacity over the MMFTN accord- ing to a transporting capacity matrix that increased from the reference matrixes. The corresponding incremental factor for estimating the capacity matrix is obtained via the maximal likelihood estima- tion method that samples data of differences between the estimated commodity volumes and carrying capacities of the critical links. The proposed formulations are tested by an experimental highway and railroad freight transportation network in an existing literature. The relevant results of OD capacities are displayed and applicability of the algorithm is certified.
文摘A simulation approach of a smart grid by cooperative bargaining is presented in this paper. Each participant of the smart grid determines its optimal schedule to meet its power and heating demand at minimal costs employing solar panels, fuel cells and batteries. This is done by solving a quadratic optimisation problem which takes the energy prices and the available devices into account. The energy prices are related to the demand and supply in the smart grid, so that a lower demand yields lower prices. The cooperative bargaining game is used to tune the participants’ optimal solution to obtain a Nash equilibrium. The computed solutions of the participants are validated against the capacities and structure of the smart grid by solving a multi-commodity flow problem. The presented model features multiple types of energy, so that they may be substituted to meet the participants’ demand. Furthermore, the participants may also act as supplier and not only as consumer, which allows decentralised generation of energy. The approach is validated in several experiments where effects like negative energy prices if generated energy exceeds the smart grid’s total demand and peak-shaving with even small-capacity batteries are exhibited.
文摘Air transportation is often affected by disruptions,both in the form of disasters that are caused by human error or natural phenomena.Such disruptions primarily affect passengers,in the form of travel delays and flight cancellations.Recovering airline schedules after disruptive events is particularly challenging for airlines due to unavailability of flights and/or their reduced capacity to address the demands of the affected passengers.In this work,we propose a multimodal rescheduling approach for airline passengers whose travel is disrupted by natural phenomena,such as hurricanes and tropical storms.The objective is to identify an optimal route,which may involve a combination of air and road travel,that minimizes system-level airline costs.The multimodal approach proposed here includes a multi-commodity network flow model where different origin-destination pairs for different travelers are treated as the different commodities.We incorporate transportation network risk in the form of a family of hop/risk side constraints.We test our approach on a simulated toy network and then proceed to use publicly available data to compare different airport network structures.The results from our computational study show that certain airline passengers may experience more inconvenience in comparison to others depending on the airport network topology of a specific airline.
基金Supported by National Natural Science Foundation of China under Grant No.(1157101511331012)the Open Project of Key Laboratory of Big Data Mining and Knowledge ManagementKnowledge Innovation Program of the Chinese Academy of Sciences under Grant No.(KGCX2-RW-329)
文摘In this paper the definition of domination is generalized to the case that the elements of the traffic matrices may have negative values. It is proved that D3 dominates D3 ＋ λ（D2 - D1） for any λ ≥0 if D1 dominates D2. Let u（D） be the set of all the traffic matrices that are dominated by the traffic matrix D. It is shown that u （ D∞） and u （D ∈） are isomorphic. Besides, similar results are obtained on multi-commodity flow problems. Fhrthermore, the results are the generalized to integral flows.
