Fuzzy Optimization of Storage Space Allocation in a Container Terminal

A fuzzy optimization model of storage space allocation is proposed,and a rolling-planning method is derived. The model takes the uncertainty of departure time of import containers and arrival time of export containers into account. For each planning horizon,the problem is decomposed into two levels: the first level minimizes the unbalanced workloads among blocks using hybrid intelligence algorithm;based on block workloads allocated in the above level,the second level minimizes the number of blocks to which the same group of import containers are split. Numerical results show that the model reduces workload imbalance,and speeds up the vessel loading and discharging process.

Designing user-centric transport strategies for urban road space redistribution

Cities worldwide are geared to promote economic growth,improve accessibility,address environmental issues,and enhance the quality of life.However,the processes that lead to the design of urban roads,particularly the space distribution,reflect the inequalities existing in the fabric of our society.Motorists often have shorter travel time and more space than passengers of other modes.Furthermore,the existing transport appraisal and planning tools that frame sustainable transport policies fall short of considering the dimension of social justice.Therefore,our urban transport systems are essential areas for advancing sustainability through a transport justice-based approach to planning that can pivot the distribution of infrastructure investments over different social groups and transport modes.This study proposes such an approach by which such suitable urban transport strategies can be identified,co-created with users and appraised while considering the commuters’needs.Specifically,the interaction between the multidimensional characteristics of sustainability and the principles of transport justice are investigated.The proposed approach is applied to London and Birmingham.The results show that a transparent and holistic approach to integrating users within transport planning is an effective way to reflect diverse needs and local circumstances and thereby ensure a just transition to sustainable urban transport policies.The results from the case studies highlight a strong rationale for the centrality of justice in any urban transport planning and policy making efforts,particularly in the allocation of road space.

Two security transmission realization schemes for MIMO Gaussian wiretap channel with one helper

This paper presents noncooperative and cooperative security transmission schemes for multiple-input multiple-output（MIMO） Gaussian wiretap channel with one helper for antenna configuration with arbitrary number. In these two schemes, the transmitter performs beamforming based on generalized singular value decomposition（GSVD）, where an appropriate power allocation algorithm is utilized. Meanwhile, the helper sends artificial noise for higher secrecy rate. However, the transmission strategies for the artificial noise are different in the two schemes. In the first scheme, the helper adopts GSVD-based beamforming. Nevertheless, in this scheme, the impact of the artificial noise on the information signal at the receiver is not considered. To solve the problem, the helper performs space projection（SP）-based beamforming in the second scheme. In this scheme, suboptimal weighting factors are introduced to reduce the computational complexity, which can be adapted to the change of the channel quality. Theoretical analysis for the performance of the two proposed schemes is then given. Furthermore, simulation results indicate that the two presented schemes perform better than the existed schemes without helper. They also show that in the second scheme the suboptimal parameter setting is better than equal parameter setting and quite close to optimal parameter setting.