This paper addresses the optimization of scheduling for workers at a
logistics depot using a combination of genetic algorithm and simulated
annealing algorithm. The efficient scheduling of permanent and temporary
workers is crucial for optimizing the efficiency of the logistics depot while
minimizing labor usage. The study begins by establishing a 0-1 integer linear
programming model, with decision variables determining the scheduling of
permanent and temporary workers for each time slot on a given day. The
objective function aims to minimize person-days, while constraints ensure
fulfillment of hourly labor requirements, limit workers to one time slot per
day, cap consecutive working days for permanent workers, and maintain
non-negativity and integer constraints. The model is then solved using genetic
algorithms and simulated annealing. Results indicate that, for this problem,
genetic algorithms outperform simulated annealing in terms of solution quality.
The optimal solution reveals a minimum of 29857 person-days.

本研究通过综合应用遗传算法和模拟退火算法，解决了物流中心工人排班的优化问题。该优化问题涉及到永久性和临时性工人的合理排班，以提高物流中心的效率并最小化劳动力使用。研究通过建立一个 0-1 整数线性规划模型，使用遗传算法和模拟退火算法解决模型，并发现遗传算法在解决问题时的质量优于模拟退火算法。最优解揭示了 29857 个人天的最小工时需求。

运用遗传算法和模拟退火优化物流配送中心的工人排班

Optimization of Worker Scheduling at Logistics Depots Using Genetic  Algorithms and Simulated Annealing

The emergence of intelligent applications and recent advances in the fields
of computing and networks are driving the development of computing and networks
convergence (CNC) system. However, existing researches failed to achieve
comprehensive scheduling optimization of computing and network resources. This
shortfall results in some requirements of computing requests unable to be
guaranteed in an end-to-end service pattern, negatively impacting the
development of CNC systems. In this article, we propose a distributed
cooperative routing framework for the CNC system to ensure the deadline
requirements and minimize the computation cost of requests. The framework
includes trading plane, management plane, control plane and forwarding plane.
The cross-plane cooperative end-to-end routing schemes consider both
computation efficiency of heterogeneous servers and the network congestion
degrees while making routing plan, thereby determining where to execute
requests and corresponding routing paths. Simulations results substantiates the
performance of our routing schemes in scheduling computing requests in the CNC
system.

智能应用和计算与网络融合的最新进展推动了计算和网络融合系统的发展。然而，现有研究未能实现对计算和网络资源的全面调度优化，从而导致一些计算请求的要求无法在端到端服务模式中得到保证，对计算和网络融合系统的发展产生负面影响。本文提出了一种分布式协作路由框架，用于计算和网络融合系统，以确保截止日期要求并最小化请求的计算成本。该框架包括交易平面、管理平面、控制平面和转发平面。交叉平面协作端到端路由方案在制定路由计划时考虑了异构服务器的计算效率和网络拥塞程度，从而确定在哪里执行请求和对应的路由路径。仿真结果证实了我们的路由方案在计算和网络融合系统中调度计算请求的性能。