A generalized interval fuzzy mixed integer programming model for a multimodal transportation problem under uncertainty

The real world conditions of transportation pose new challenges for development of intelligent assistive systems for effective decision making. The ignorance of relationships among various attributes and parameters is one of the major causes of uncertainty in existing models of transportation problems. Fuzzy sets have been explored by various investigators to address the uncertainty issues due to relationships among various attributes. However fuzzy sets are not fully capable of dealing all kinds of uncertainty to provide intelligent solutions of transportation problems. A soft set is explored in this paper to model the uncertainty arising from the relationships of attributes with the parameters in a multimodal and multi objective transportation problem. The three modes of transportation incorporated in this model are road, rail and air. The real data set is prepared using the tariff, distance and time duration of transport available on websites of transport service agencies. The objectives are to minimize the cost and time duration of transportation. The proposed model evaluates multiple criteria using various combinations of different modes of transport to optimize the objectives of the problem. The model has been illustrated using the real data set using existing methods of solution. The soft set approach is found to be quite effective in dealing with the relationships of attributes with the parameters arising due to multi criteria decision making and leads to intelligent optimal solutions. The proposed model can be used as intelligent assistive system for decision making of multi objective and multimodal transportation problems.

PurposeSome essential issues about modeling of reverse logistics (RL) systems and product recovery networks include consideration of the qualities of the returned products, taking into account uncertainty and integrating the forward and reverse flows. The purpose of this paper is to develop the integrated RL model, which focuses on the control of inventory and production planning problems in a case of uncertainty in demand, quantities and qualities of returns.Design/methodology/approachThe model involves a forward production route, three alternative recovery routes and a disposal route. Various levels of qualities are considered for returned products. A fuzzy mixed integer programming model (FMIP) is developed to provide a solution for the problems of production planning and inventory control. After maximizing the satisfaction degree, different solutions can have the same maximum. Moreover, policies that use all recovery routes and reduce the overall uncertainty have no chance to be chosen. To tackle these problems, a two-phase approach method is applied.FindingsAccording to the results of the numerical example, using different and appropriate recovery options based on the quality of returns can significantly decrease the recovery costs. Similarly, it is shown that the two-phase approach can be an effective and efficient method to reach a satisfactory solution for such problems.Originality/valueIn this study, after maximizing the FMIP model, a two-phase approach ‒ as a novel optimization technique in this research ‒ is employed to achieve a desirable solution.

Nowadays, there has been a growing interest in reverse logistics, recycling, remanufacturing and reusing due to the environmental, economical issues and legal obligations. Due to this fact, compani...

This article introduces a new approach called multi-objective firework algorithm (MFWA). The proposed approach allows for solving the multimodal transportation network problem (MTNP). The main goal is to develop a decision system that optimizes and determines the planning network of the multimodal transportation (PNMT) problem. The optimization involves reaching the efficient transport mode and multimodal path, in order to move from one country to another while satisfying the set of objectives. Moreover, the firework algorithm has distinct advantages in solving complex optimization problems and in obtaining a solution by a distributed and oriented research system. This approach presents a search way, which is different from the swarm intelligence-based stochastic search technique. For each firework, the process starts by exploding a firework in the sky. The search space is filled with a shower of sparks to get diversity solutions. This new approach proves their efficacy in solving the multi-objective problem, which is shown by the experimental results.

The role of information and communication technologies (ICTs) in freight transport as key enabler is well recognised. However the uptake of recent ICT advances for multimodal freight transport provisions in the UK and Europe has been slow. The aim of our paper is to explore the potential reasons for such a slow adoption and assess how recent technological advances such as cloud computing and Internet of Things might have changed the landscape and thus help to overcome these barriers. Via an extensive review of 33 EU framework programme projects, we are able to consolidate and present current major efforts in ICT developments in the freight multimodal transport setting at European level. We further discuss barriers inhibiting quick take-up of ICT applications in multimodal transport. Resolutions were then explored by reviewing four key ICT development trends recently emerging and evaluating their potential impact in reducing such barriers for deployment. Our contribution is two-fold: it advances current knowledge by presenting an up-to-date overview of existing and emerging ICT applications in the field of multimodal transport and barriers to e-enabled multimodal transport. It also captures some of the best practices in industry and aims to provoke a debate among practitioners and academics via the analysis of how innovative use of recent technological developments could potentially lower the barriers to multimodal ICT adoption and lead to a more integrated freight transport network. Therefore it lays the foundation for further research.

The problem of route optimization of large volume and long distance material distribution is carried out from the rear strategic logistics center to the front line distribution center, researched by turning into multimodal transport problems, and a single-path multimodal transport path optimization model is established. Decision variables about stage safety probability are introduced; the nonlinear model is simplified into a second-order programming model, by changing the probability of task safety and simplified the model to a linear programming model by using the monotonicity of logarithmic functions. An example is presented to solve the simulation with LINGO software, made a reference plan under different constraints, the correctness of the model is verified.

Multimodal transportation has become increasingly important and dominating in the freight transportation industry. Sustainability concerns and availability of eco-friendly transportation modes, such as high-speed rail, have called for an investigation on environmental impacts of multimodal operations. Motivated by a real-life business case, this research studies multimodal transportation problems with operational constraints and environmental considerations. Specifically, a mathematical model is developed, and a heuristic algorithm is proposed to solve the problem effectively and efficiently. Environmental and financial impacts are further studied for several model configurations. First, we study an operations scheduling problem in a multimodal transportation network, subject to shipping capacity limits, resource availability, transshipment delays, customer service requirements, and environmental concerns. The objective is to minimize the total shipping costs and penalty costs due to delivery delays. To this end, we model the problem as a mixed integer linear program (MILP), which determines the routing of customer orders, the transportation mode to use on each route segment, and the corresponding departure time of the selected mode. Second, in view of the problem’s large scale and computational complexity, we propose a Lagrangian relaxation model, and decompose the original MILP model into smaller-size subproblems. These subproblems are independent to each other, and hence can be solved in parallel to significantly speed up the computation. A sub-gradient heuristic is developed to solve the Lagrangian model by effectively searching for bounds and feasible solutions. We tested the proposed heuristic on 28 different problem settings, each with 30 randomly generated test cases. The results show that the proposed heuristic is effective in finding near-optimal solutions for small to medium sized problems benchmarked by the Gurobi MILP solver, and for large-scale problems, the heuristic outperforms Gurobi in both solution time and quality. Finally, based on the aforementioned model and its variants, we perform simulation analysis and quantify the financial and environmental impacts of four scenarios. (1) We quantify the environmental benefits of multimodal transportation, compared to truck-only transportation. (2) We quantify the impacts on carbon emissions by varying usage of high-speed rail. (3) We investigate the financial and environmental impacts on logistics companies by imposing carbon emissions quota as an operational constraint. (4) For shipping capacities, the logistics company may use a pay-per-use scheme or a fixed-volume subscription. We compare two models and their resulting impacts on firm’s operational costs and carbon emissions. Based on the numerical results of these analysis, we provide insights and suggestions on economic and environmental considerations for the future of multimodal transportation.

Background. The article provides an overview of the current state of the railway container transportation market. Statistical data on the container transportation market is presented and analyzed. The article provides an overview of the work aimed at improving the organization of container transportation by rail. A generalized scheme of container delivery using rail transport is developed. The key objectives aimed at ensuring the reliability of container delivery are identified, and the main factors affecting the speed of container delivery are systematized. A mathematical expression of the delivery time of a container for the conditions of a direct option of transshipment from one mode of transport to another and taking into account the processing and storage of cargo at the terminal. Formulated the problem of optimizing the delivery scheme of containers in multimodal transportation in the conditions of the presence of several options of container terminals, their location. At the same time, according to the conditions of the formulated task, one processing of containers at the terminal is provided. A decision support system for changing the method of transportation of container products in multimodal transportation is proposed. Conclusions are drawn about the prospects of using the proposed system by transport and logistics companies. The purpose is to identify options for ensuring the flow and uninterrupted movement of container flows during multimodal transportation. Methodology. The article used an analysis of the current situation in the field of container transportation, mathematical modeling of container delivery time, optimization of the container delivery scheme based on the decision to overload the container at each terminal, and formulated a decision support system for delivery management. Results. The state of container transportation involving rail transport is determined, the analysis of studies in the field of container transportation using rail transport is performed, the directions of ensuring the reliability of container delivery are identified. A decision support system for multimodal container transportation is proposed. Practical implications. The results obtained can be used in the railway container transportation system, as well as by freight forwarding, operator, and transport and logistics companies.

The paper considers a multicriteria multimodal transport problem, which contains three types of transport and two objective functions. The article investigates the possibility of transforming a multi-criteria multimodal transport problem into a classical transport problem by constructing a system of linear matrix equations and inequalities. It is shown that measurements for the corresponding system of linear matrix equations and inequalities are directly dependent on the number of objective functions of the considered problem. The paper proposes the algorithm for finding the problem reference plans, which is based on finding the reference plans for different types of vehicles. The multicriteria problem is solved using the method of weighted coefficients and the method of sequential concessions according to the relevant criteria. Tools of the computer mathematics system Mathcad were used for the numerical experiment on solving demonstration problems by the methods proposed in the work and for comparing the obtained results. The application of the proposed methods in this paper for solving multicriteria multimodal transport problems allows to reduce the number of iterations in the numerical solution of these problems and to overcome the different measurement problem of the objective functions in their superposition.

With international trade developing, international logistics is attached to more and more importance. Advanced way of international cargo transport gradually becomes to perfection, and multimodal transport especially predominates. But international cargo transport means high risk, uncertain requirements, information not be really shared, general insufficient or short collaboration among enterprises for lack of trust each other etc., and these factors restrict the development of multimodal transport. So this paper compares operation mode of multimodal transport with that of virtual enterprise, points out the feasibility that resolve multimodal transport problems by constructing virtual enterprise. Meanwhile, the paper indicates the problems existing in constructing virtual enterprise based multimodal transport and puts forward solutions. Toward this promotes the sound progress of international multimodal transport and the rationalization of international logistics.

In 2021, economic losses due to supply chain disruptions in the Eurozone amounted to €112.7 billion Euro: Natural catastrophes (e.g., hurricanes, earthquakes, floods, and wildfires) multiply in the wake of climate change. The risks of pandemics, trade restrictions, cyber-attacks, and geopolitical conflicts are omnipresent. Hence, the threat of disruptive events to the European transport network grows ever greater. Additionally, GHG emissions can drastically increase by up to 50% if disruptions are not treated efficiently. Here, the project “Resilient multimodal freight transport network” (ReMuNet) comes into play: ReMuNet will enable the multimodal freight network to react and respond 20% more quickly to disruptive events and help to reduce European inland transport emissions on the main run by over 50% by 2026. As a trailblazer for the Physical Internet, the project pursues the vision to enable and incentivize synchro-modal relay-transport on European rail, road, and inland waterways to increase holistic network resilience. ReMuNet can identify and signal disruptive events and assess their impact on multimodal transport corridors. It reacts quickly to disruptive events in real time. It supports TMS providers to improve route planning resilience by communicating alternative, pre-defined, multimodal transport routes. ReMuNet orchestrates route utilization, suggests transshipment points, and optimizes capacity allocation, minimizing damage and shortening the recovery time. This paper introduces ReMuNet and its vision, objectives, and expected results.

Multimodal transportation is generally accepted as an efficient alternative to road transportation in terms of costs, fuel consumption, environmental externalities and road congestion. This work presents a novel optimization approach to the multimodal network design for freight transportation with applications to a case in Spain. Optimization is conducted in order to maximize the internal rate of return. Service utilization rates are evaluated by means of a parameterized model implemented in TransCAD.

Improving freight transportation performance through sustainability best practices

In order to further reduce the cost of road freight transport, the influence of the railway freight transport reformation on Ningbo road general freight transport industry are analyzed based on the review of background and core contents of the reformation. As a result, the railway freight reform will bring more cooperation opportunities than competition, which created new opportunities for Ningbo to build a comprehensive land transport system and the development of logistics services. From the standpoint of cooperation-competition development, multimodal transport and the transformation of modern logistics, countermeasures are proposed for the transport of less-than-truckload freight on road.

Distribution systems (DS) are a focal connection point for existing and new renewable energy sources. DS have increasing sizes; they connect increasing numbers of renewable energy sources and have a mandate to operate as financial entities seeking to maximize their profits in an electricity market. To achieve these goals, DS require highly efficient planning tools. In this paper, we propose a successive fuzzy mixed integer linear programming (MILP) method for optimally placing and sizing capacitors in a DS that explicitly models induction run wind electric generators (WEGs). The optimization problem is linearized, transformed into a fuzzy MILP model and is solved successively while updating the solution vector. The fuzzy MILP method employs fuzzy models of voltage constraints that are often violated in a planned system that lacks reactive power support. The use of fuzzy constraints makes the proposed solution method very robust by avoiding infeasibility and reducing the need for user expertise. Further, the fuzzy MILP method represents the dual objectives of capacitor cost and annual energy loss minimization as fuzzy sets with individual satisfaction functions. The method maximizes the minimum of these satisfaction functions during optimization. Tests on 69-bus and 2002-bus DS show that the method performs well and is robust.