PDP2024 – An Innovative Control Approach for Cyber-Physical Transportation Systems: The Case of Monte-Carlo Workflow Computations
Title
An Innovative Control Approach for Cyber-Physical Transportation Systems: The Case of Monte-Carlo Workflow Computations
Abstract
Contemporarily, in light of the intelligent transportation systems (ITS) sector, the tendency can be observed that the solution of the multi-objective cyber-physical optimization problems with imperfect information takes an increasingly weighted role. In the present scientific work, the authors want to take these developments into account by introducing an innovative cyber-physical architectural design and corresponding the two-stage heuristic computing approach. It is utilized in synergy with the MCSA (Multi-tier Cyber-physical System Architecture) and DCEx architectural principles for the workflow scheduling of Monte-Carlo simulation, which is based on the intelligent and sustainable route-order dispatching process model. Factors such as emissions, transport costs, risks, and the individual weighting of orders are reflected in the model. In particular, the authors define a stochastic ILP-based (Integer Linear Programming) monte-carlo workflow model. They further propose two-stage scheduling heuristic with Delta-HEFT DAG relaxation as first stage and apply state-of-the-art techniques as a part of SCIP framework to solve 2nd 1–0 ILP-based stage; evaluate the performance of the scheduling approach. The authors obtain preliminary results of the second stage behavior using a realistic heterogeneous computing scenario and corresponding constraint structures within MACS simulator engine (Modular Architecture for Complex Computing Systems Analysis). The results from the experiments illustrate moderate complexity of the approach. Scalability of the model looks promising for the applicability in various industry-related scenarios and corresponding computing environments.
This work has been supported by FFG Project Grant Agreement No. 911465.
Further Information
PDP ’24: 32nd Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP) – April 2023 – Pages 153-160 – DOI: https://doi.org/10.1109/PDP62718.2024
GoodIT 2023 – Intelligent and Sustainable Transportation through Multi-Objective Model for the Logistic Route-Order Dispatching System
Title
Intelligent and Sustainable Transportation through Multi-Objective Model for the Logistic Route-Order Dispatching System
Abstract
Solution of multi-objective optimization in the logistics sector have become an integral important part of the Intelligent Transportation System (ITS). In this work we focus on the intelligent and sustainable transportation processes through the design of the multi-objective model for the logistic route-order dispatching system. We consider transportation costs, emissions, order importance and risks for failures, for the logistic route-order dispatching system. We present an Integer Linear Programming (ILP) optimization model and apply state-of-the-art techniques as a part of SCIP framework to solve pilot problem instances and evaluate the performance of the model. We obtain results of solving the model on a single monolithic Google Cloud Compute (GCP) to estimate the time complexity of the solving process in relation to the various problem sizes. The results from the experiments show low complexity of the problems of various sizes. Therefore scalability of the model looks promising for the applicability in various industry-related scenarios and computing environments. In particular, using hybrid-cloud systems and state-of-the-art optimization frameworks such as IBM CPLEX or Gurobi.
This work has been supported by FFG Project Grant Agreement No. 899648. We acknowledge ARCOS Research Group for provisioning of TUCAN HPC cluster for data analysis and computations. This work was partially supported by the Spanish Ministry of Science and Innovation Project “New Data Intensive Computing Methods for High-End and Edge Computing Platforms (DECIDE)” Ref. PID2019-107858GB-I00.
Further Information
GoodIT ’23: Proceedings of the 2023 ACM Conference on Information Technology for Social Good – September 2023 – Pages 530–536 – DOI: https://doi.org/10.1145/3582515.3609578