A Survey of League Championship Algorithm: Prospects and Challenges <s> University Timetable <s> In subway systems, the energy put into accelerating trains can be reconverted into electric energy by using the motors as generators during the braking phase. In general, except for a small part that is used for onboard purposes, most of the recovery energy is transmitted backward along the conversion chain and fed back into the overhead contact line. To improve the utilization of recovery energy, this paper proposes a cooperative scheduling approach to optimize the timetable so that the recovery energy that is generated by the braking train can directly be used by the accelerating train. The recovery that is generated by the braking train is less than the required energy for the accelerating train; therefore, only the synchronization between successive trains is considered. First, we propose the cooperative scheduling rules and define the overlapping time between the accelerating and braking trains for a peak-hours scenario and an off-peak-hours scenario, respectively. Second, we formulate an integer programming model to maximize the overlapping time with the headway time and dwell time control. Furthermore, we design a genetic algorithm with binary encoding to solve the optimal timetable. Last, we present six numerical examples based on the operation data from the Beijing Yizhuang subway line in China. The results illustrate that the proposed model can significantly improve the overlapping time by 22.06% at peak hours and 15.19% at off-peak hours. <s> BIB001 </s> A Survey of League Championship Algorithm: Prospects and Challenges <s> University Timetable <s> Railway timetable scheduling is a fundamental operational problem in the railway industry and has significant influence on the quality of service provided by the transport system. This paper explores the periodic railway timetable scheduling (PRTS) problem, with the objective to minimize the average waiting time of the transfer passengers. Unlike traditional PRTS models that only involve service lines with fixed cycles, this paper presents a more flexible model by allowing the cycle of service lines and the number of transfer passengers to vary with the time period. An enhanced differential evolution (DE) algorithm with dual populations, termed “dual-population DE” (DP-DE), was developed to solve the PRTS problem, yielding high-quality solutions. In the DP-DE, two populations cooperate during the evolution; the first focuses on global search by adopting parameter settings and operators that help maintain population diversity, while the second one focuses on speeding up convergence by adopting parameter settings and operators that are good for local fine tuning. A novel bidirectional migration operator is proposed to share the search experience between the two populations. The proposed DP-DE has been applied to optimize the timetable of the Guangzhou Metro system in Mainland China and six artificial periodic railway systems. Two conventional deterministic algorithms and seven highly regarded evolutionary algorithms are used for comparison. The comparison results reveal that the performance of DP-PE is very promising. <s> BIB002 </s> A Survey of League Championship Algorithm: Prospects and Challenges <s> University Timetable <s> Leader election is one of the important problems in distributed systems. This problem deals with selecting a node in distributed systems as a leader. In the election of nodes problems such as node failure and discrete parts of the network should also be examined. Investigation of this problem in wireless networks especially Adhoc, that do not have special structure and topology changes are frequently and inevitable, is much more complex than wired networks. This paper examines different algorithms for leader election. Some algorithms are designed for just one leader and some of them are designed for N leader. Some of them also create hierarchical structure in resulted graph of wireless networks. These algorithms are used in places that have been pre-clustered or clustering of them is possible. In this paper, in addition to various algorithms classification based on the used assumptions and methods, we deal with. <s> BIB003
Resources allocation BIB001 and scheduling BIB002 BIB003 .