A facility system can be modeled by a connected graph in which the vertices represent entities such as suppliers, distribution centers or customers and the edges represent facilities such as the paths of goods or info...A facility system can be modeled by a connected graph in which the vertices represent entities such as suppliers, distribution centers or customers and the edges represent facilities such as the paths of goods or information. The efficiency, and hence the reliability, of a facility system is to a large degree adversely affected by the edge failures in the network. Such failures may be caused by various natural disasters or terrorist attacks. In this paper, we consider facility systems’ reliability analysis based on the classical uncapacitated fixed-charge location problem when subject to edge failures. For an existing facility system, we formulate two models based on deterministic case and stochastic case to measure the loss in efficiency due to edge failures and give computational results and reliability envelopes for a specific example.展开更多
The reliability of facility location problem has aroused wide concern recently. Many researchers focus on reliable and robust facility systems design under component failures and have obtained promising performance. H...The reliability of facility location problem has aroused wide concern recently. Many researchers focus on reliable and robust facility systems design under component failures and have obtained promising performance. However, the target and reliability of a facility system are to a large degree adversely affected by the edge failures in the network, which remains a deep study. In this paper, we focus on facility systems’ reliability subject to edge failures. For a facility location system, we formulate two models based on classical uncapacitated fixed-charge location problem under deterministic and stochastic cases. For a specific example, location decisions and the comparison of reliability under different location models are given. Extensive experiments verify that significant improvements in reliability can be attained simply by increasing the amount of operating cost.展开更多
无容量设施选址问题(Uncapacitated Facility Location Problem,UFLP)是组合优化中经典的NP-Hard问题之一。针对UFLP的变形问题之一,即带惩罚的无容量设施选址问题(Uncapacitated Facility Location Problem With Penalties,UFLPWP),研...无容量设施选址问题(Uncapacitated Facility Location Problem,UFLP)是组合优化中经典的NP-Hard问题之一。针对UFLP的变形问题之一,即带惩罚的无容量设施选址问题(Uncapacitated Facility Location Problem With Penalties,UFLPWP),研究了UFLPWP的数学性质,其中包括可以批量确定某些设施一定关闭的性质,并进行了数学证明,利用这些数学性质可以对问题进行降阶,进而缩小问题的规模。在此基础上设计了基于上、下界的回溯算法来求解UFLPWP。通过一个示例分析,进一步阐述该算法的原理。展开更多
The reliability of facility location problems has been received wide attention for several decades. Researchers formulate varied models to optimize the reliability of location decisions. But the most of such studies a...The reliability of facility location problems has been received wide attention for several decades. Researchers formulate varied models to optimize the reliability of location decisions. But the most of such studies are not practical since the models are too ideal. In this paper, based on the classical uncapacitated fixed-charge location problem (UFLP) and some supply constraints from the reality, we distinguish deterministic facility failure and stochastic facility failure cases to formulate models to measure the reliability of a system. The computational results and reliability envelopes for a specific example are also given.展开更多
The artificial bee colony(ABC)algorithm is an evolutionary optimization algorithm based on swarm intelligence and inspired by the honey bees’food search behavior.Since the ABC algorithm has been developed to achieve ...The artificial bee colony(ABC)algorithm is an evolutionary optimization algorithm based on swarm intelligence and inspired by the honey bees’food search behavior.Since the ABC algorithm has been developed to achieve optimal solutions by searching in the continuous search space,modification is required to apply it to binary optimization problems.In this study,we modify the ABC algorithm to solve binary optimization problems and name it the improved binary ABC(IbinABC).The proposed method consists of an update mechanism based on fitness values and the selection of different decision variables.Therefore,we aim to prevent the ABC algorithm from getting stuck in a local minimum by increasing its exploration ability.We compare the IbinABC algorithm with three variants of the ABC and other meta-heuristic algorithms in the literature.For comparison,we use the well-known OR-Library dataset containing 15 problem instances prepared for the uncapacitated facility location problem.Computational results show that the proposed algorithm is superior to the others in terms of convergence speed and robustness.The source code of the algorithm is available at https://github.com/rafetdurgut/ibinABC.展开更多
文摘A facility system can be modeled by a connected graph in which the vertices represent entities such as suppliers, distribution centers or customers and the edges represent facilities such as the paths of goods or information. The efficiency, and hence the reliability, of a facility system is to a large degree adversely affected by the edge failures in the network. Such failures may be caused by various natural disasters or terrorist attacks. In this paper, we consider facility systems’ reliability analysis based on the classical uncapacitated fixed-charge location problem when subject to edge failures. For an existing facility system, we formulate two models based on deterministic case and stochastic case to measure the loss in efficiency due to edge failures and give computational results and reliability envelopes for a specific example.
文摘The reliability of facility location problem has aroused wide concern recently. Many researchers focus on reliable and robust facility systems design under component failures and have obtained promising performance. However, the target and reliability of a facility system are to a large degree adversely affected by the edge failures in the network, which remains a deep study. In this paper, we focus on facility systems’ reliability subject to edge failures. For a facility location system, we formulate two models based on classical uncapacitated fixed-charge location problem under deterministic and stochastic cases. For a specific example, location decisions and the comparison of reliability under different location models are given. Extensive experiments verify that significant improvements in reliability can be attained simply by increasing the amount of operating cost.
文摘无容量设施选址问题(Uncapacitated Facility Location Problem,UFLP)是组合优化中经典的NP-Hard问题之一。针对UFLP的变形问题之一,即带惩罚的无容量设施选址问题(Uncapacitated Facility Location Problem With Penalties,UFLPWP),研究了UFLPWP的数学性质,其中包括可以批量确定某些设施一定关闭的性质,并进行了数学证明,利用这些数学性质可以对问题进行降阶,进而缩小问题的规模。在此基础上设计了基于上、下界的回溯算法来求解UFLPWP。通过一个示例分析,进一步阐述该算法的原理。
文摘The reliability of facility location problems has been received wide attention for several decades. Researchers formulate varied models to optimize the reliability of location decisions. But the most of such studies are not practical since the models are too ideal. In this paper, based on the classical uncapacitated fixed-charge location problem (UFLP) and some supply constraints from the reality, we distinguish deterministic facility failure and stochastic facility failure cases to formulate models to measure the reliability of a system. The computational results and reliability envelopes for a specific example are also given.
文摘The artificial bee colony(ABC)algorithm is an evolutionary optimization algorithm based on swarm intelligence and inspired by the honey bees’food search behavior.Since the ABC algorithm has been developed to achieve optimal solutions by searching in the continuous search space,modification is required to apply it to binary optimization problems.In this study,we modify the ABC algorithm to solve binary optimization problems and name it the improved binary ABC(IbinABC).The proposed method consists of an update mechanism based on fitness values and the selection of different decision variables.Therefore,we aim to prevent the ABC algorithm from getting stuck in a local minimum by increasing its exploration ability.We compare the IbinABC algorithm with three variants of the ABC and other meta-heuristic algorithms in the literature.For comparison,we use the well-known OR-Library dataset containing 15 problem instances prepared for the uncapacitated facility location problem.Computational results show that the proposed algorithm is superior to the others in terms of convergence speed and robustness.The source code of the algorithm is available at https://github.com/rafetdurgut/ibinABC.
