Multimodal Processes Rescheduling: Cyclic Steady States Space Approach

Automated guided vehicles fleet match-up scheduling with production flow constraints

Route finding is an everyday challenge for urban residents. While many route planner applications exist, they cannot find suitable routes based on user preferences. According to user preferences, routing in a multimode urban transportation network can be considered a multiobjective optimization problem. Different objectives and modes for transportation, along with many routes as decision elements, give rise to the complexity of the problem. This study uses an elitism multiobjective evolutionary algorithm and the Pareto front concept to solve the problem. The data of a simulated multimode network consisting of 150 vertexes and 2600 edges are used to test and evaluate the proposed method. Four transport modes are considered: the metro, bus, taxi, and walking. Also, three minimization objective functions are considered: expense, discomfort, and time. The results show the competence of the algorithm in solving such a complex problem in a short run time. The optimal setting for the algorithm parameters is found by considering the algorithm run time, diversity of solutions, and convergence trend by running sensitivity analyses. A repeatability test is applied using the optimal setting of the algorithm, which shows a high level of repeatability. While NSGA-II (Non-dominated Sorting Genetic Algorithm II) may be a well-established algorithm in the literature, its application in multiobjective route finding in multimode transport networks is unique and novel. The outcomes of the proposed method are compared with existing methods in the literature, proving the better performance of the NSGA-II algorithm.

Cyclic scheduling problems arise in a variety of transportation applications and service domains. Within the class of those problems we can identify situations where there is need to make use of different modes of transportation. What is of particular interest in this paper is the design of a class of multimodal cyclic processes (MCP) for production engineering and supply chains. The paper presents a new modeling framework enabling to prototype and evaluate multimodal processes while comparing their cyclic steady states. A way in which the multimodal processes encompass the behavior of supporting them concurrently flowing cyclic processes (SCCP) is discussed in terms of constraints satisfaction problem. Possible implementations are illustrated on example of the flexible manufacturing system operation.KeywordsCyclic processesCyclic schedulingConcurrent processesMultimodal processesState spaceDeclarative modelingDispatching rules

An integrated approach of fuzzy risk assessment model and data envelopment analysis for route selection in multimodal transportation networks

Vulnerability assessment of China–Europe Railway Express multimodal transport network under cascading failures

Pareto-improving congestion pricing on multimodal transportation networks

Multimodal transportation network with cargo containerization technology: Advantages and challenges

The cyclic scheduling problem modeled in terms of Cyclic Concurrent Process Systems is considered. The problem can be seen as a kind of Diophantine problem, hence its solvability, i.e. schedulability, plays a pivotal role in many supply-chain problems. In contradiction to the traditionally offered solutions the approach proposed allows one to take into account such behavioral features as transient periods and deadlocks occurrence. So, the contribution’s aim is the modeling framework enabling an evaluation of cyclic scheduling problems solvability, i.e., the declarative approach to reachability problems regarding cyclic steady states determination as well as conditions guaranteeing assumed performance of multimodal processes executed within a concurrent cyclic processes environment.

This article intends to provide an advanced traveller information system based on open geospatial consortium (OGC) standards to perform a fuzzy bi-criteria shortest-path analysis for a multimodal transportation network. To do so, chaining of OGC web services is used to resolve interoperability problems among distributed and heterogeneous resource data. First, a web feature service is assigned to each mode of transportation to gather and convert the data to a standard format, such as geographic markup language. Then, the obtained data are combined to model and construct the multimodal transportation network. Subsequently, a web processing service is designed for performing a fuzzy bi-criteria shortest-path analysis in the multimodal transportation network. Finally, the best routes between the origin–destination pair are presented on a digital map by using a web map service. In the study, among various route-selection criteria, travel time and comfort are considered. To model these criteria, the fuzzy set theory is utilized. By using fuzzy decision tables and a Tsukamoto fuzzy inference system, the desirability of the routes is calculated. The results of comparison among the four travel routes between various origin–destination pairs indicate that the proposed system could be an applicable tool for providing pre-trip information and assisting multimodal travellers under uncertain conditions.

In the pursuit of capacity-oriented urban sustainable development (SD), this study aims to enhance the multimodal transport network by making it more accessible, efficient, and environmentally friendly. A sustainable framework combining policy mixes and second-best constraints is developed as a multimodal transportation network capacity (TNC) model with the bi-level programming (BLP) formulation. The upper-level model is to maximise the total origin-destination (OD) demand with considering second-best constraints. The lower-level model is a combined mode split and traffic assignment with elastic demand (CMSTA-ED) model which considers policy mixes. Numerical experiments are conducted to demonstrate the effectiveness of the hybrid PSO–GWO algorithm, the synergy of the method for selecting and mixing policy instruments based on the proposed assessment system, and a methodology to establish a policy mix. The findings of this research offer practical guidance for formulating well-informed and no-redundant policy mixes, contributing to the improvement of sustainable multimodal transportation network performance.

Nowadays, urban and suburban areas face increasing environmental pressures, and encouraging sustainable transportation behaviors at the household level has become crucial. This paper presents a model of a decision support system (DSS) for promoting sustainable household mobility choices in multi-modal transport networks. The system was modeled using an enhanced Petri Net approach, allowing for the dynamic representation of complex transport networks and multi-modal journey options. The model incorporated various sustainability factors. These were combined into a single environmental impact score, which was considered alongside travel time and cost in the route optimization process. Simulation results demonstrated the DSS’s capability to guide users toward more sustainable mobility choices. The model also showed potential as a tool for policymakers to assess the impact of various sustainable transportation initiatives and infrastructure investments. This paper discussed the versatile applications of the system. It also addressed the limitations of Petri Net models in transportation systems and suggested future research directions.

This paper describes a Grid-like Material Transportation Network (GMTN) in which several heterogeneous means of transportation (Automated Guided Vehicles (AGVs), hoists, lifts, etc.) interact with each other via common shared workstations to provide a variety of demand-responsive material handling operations. Different material handling transport modes provide movement of workpieces between workstations along their manufacturing routes in the GMTN and they can be seen as processes realized with synergic utilization of various local periodically acting unimodal processes. The main contribution of this research is the solution of a constraint satisfaction problem addressing AGVs fleet match-up scheduling subject to GMTN and fuzzy operation time constraints. In the presented case both production rate (production takt) and operations execution time are described by imprecise (fuzzy) data. In other words, the research’s objective concerns assessing grid-like networks of periodically acting local transportation modes from the perspective of possible mass-customized oriented requirements imposed on scheduling of multimodal flows of jobs assigned to certain technological routes passing through common shared workstations.

The advantage of multimodal transport is that it can deliver the goods to their destination in a reasonable combination of transport modes while ensuring security and punctuality. Multimodal transportation can effectively reduce logistics costs, improve logistics efficiency, and reduce environmental pollution. In the process of multimodal transportation, due to the interference of natural factors (weather, terrain, etc.) and some special human factors, it may have different degrees of impact on the transportation time and transportation safety of different transportation modes. Therefore, when choosing a transportation method, it is necessary to consider the transportation time and transportation safety under the interference. However, the current research on multimodal transport has not considered the impact of external interference on transportation time and transportation safety. Compared with other modes of transportation, external interference has a relatively small impact on railway transportation. Railways can safely deliver goods to their destinations on time. Under the background of China’s huge railway network and advanced heavy-duty technology, this paper establishes a multimodal transport route selection model for considering railway as the core, introduces time penalty cost and damage compensation cost, and takes the lowest comprehensive transportation cost as the model objective under the premise of considering transportation reliability and transportation safety. Finally, taking a multimodal transport network in China as an example, an improved ant colony algorithm is used to solve the model and the results verify the rationality of the model.

The single variety of goods transportation route optimization is the basic link of organization and implementation of multimodal transport. Transport costs, transport time, multimodal transport network carriage capacity and change trains ability are the main factors affecting the multimodal transport path selection. The multimodal transport network is described as a simple undirected graph. Contrast and analyze the network characteristics. Based on the parameters definition and borders assumption, using point-arc model, structure the multimodal transport path selection model of a single variety of goods. Further analysis found that: through transforming the network and reconstructing the objective function, it can simplify a linear constraint model about shortest path.

Ideology and Practice of Systems Engineering in Multi-Modal Transport Planning