Proactive and Reactive Multi-Project Scheduling in Uncertain Environment

Abstract

In this paper, a proactive and reactive multi-project scheduling problem is addressed. This problem is related to the influences of uncertain factors, which leads to a deviation between actual scheduling and baseline scheduling, and a recovery strategy is established in order to generate a baseline scheduling scheme. This paper introduces a proactive multi-project scheduling sub-model. When the activity is interrupted, the proactive scheduling scheme is used as the baseline scheduling scheme, which is embedded in the reactive scheduling, and then, the reactive scheduling sub-model is established. The proposed model can be used to generate alternative schedules, and to meet this need, a genetic simulated annealing algorithm is proposed. A buffer change operator (SC) and a crossover operator are designed in a genetic simulated annealing algorithm so that in the early stages of the algorithm, an optimum individual is produced and protected. The performance comparison shows that the genetic simulated annealing algorithm significantly outperforms the previous algorithms.INDEX TERMS Multi-project scheduling, proactive and reactive scheduling, genetic simulated annealing algorithm, optimization model.

A Path-Based Selection Solution Approach for the Low Carbon Vehicle Routing Problem with a Time-Window Constraint

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“…Minmize (22) In order to obtain the travel solution with the shortest time, the following function was designed in this paper: (23) In order to obtain the travel solution with the least fuel consumption and the minimum cost, we employed Equations (6) and 7as the objective functions. Different models use the same constraint conditions, i.e., Constraints (18)-(21).…”

“…Based on the analysis above, it can be concluded that the former research on vehicle routing problems with time windows (VRPTW) and PEP focused on the factors of traffic congestion, vehicle composition and vehicle load, etc., rather than multi-path vehicle routing problems [21][22][23]. Therefore, a multi-path mixed-integer mathematical programming model with a time window was established, which aimed to optimize fuel cost, driver cost, vehicle depreciation and time-window penalty cost and determine the exact solution using CPLEX in Java.…”

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“…The optimization of traditional project schedule control management methods and the exploration of new methods of schedule management had always been one of the issues that scholars at home and abroad pay close attention to. A large number of scholars at home and abroad have conducted a lot of elaboration and research from different levels and angles [5] [6] [7][8] [9] . The project schedule is an activity to determine the process content and sequence relationship of the project implementation process, allocate various resources used in the implementation process and make specific time arrangement so that the project can be completed within the specified time, to control costs and save time.…”