  This article addresses the dynamic multi-skill workforce scheduling and
routing problem with time windows and synchronization constraints (DWSRP-TW-SC)
inherent in the on-demand home services sector. In this problem, new service
requests (tasks) emerge in real-time, necessitating a constant reevaluation of
service team task plans. This reevaluation involves maintaining a portion of
the plan unaltered, ensuring team-task compatibility, addressing task
priorities, and managing synchronization when task demands exceed a team's
capabilities. To address the problem, we introduce a real-time optimization
framework triggered upon the arrival of new tasks or the elapse of a set time.
This framework redesigns the routes of teams with the goal of minimizing the
cumulative weighted throughput time for all tasks. For the route redesign phase
of this framework, we develop both a mathematical model and an Adaptive Large
Neighborhood Search (ALNS) algorithm. We conduct a comprehensive computational
study to assess the performance of our proposed ALNS-based reoptimization
framework and to examine the impact of reoptimization strategies, frozen period
lengths, and varying degrees of dynamism. Our contributions provide practical
insights and solutions for effective dynamic workforce management in on-demand
home services.
