Intermodal transport problem of container terminal in emission control area

Scheduling local and express trains in suburban rail transit lines: Mixed–integer nonlinear programming and adaptive genetic algorithm

A bi-level optimization model is proposed for locating billboards on road network links in cities. Since billboard locations are largely driven by the flow on the underlying network, factors that impact traffic considerations of users are accounted for, including link congestion and road link pricing. Safety aspects associated with billboard distraction to users of the network are also incorporated within the proposed Mixed Integer Non-Linear Programming (MINLP) model. The model is multi-objective in nature, and it is solved through adopting the augmented ε -constraint method to obtain a sample of non-dominated points on the Pareto front. Due to the non-convexity induced by the bi-level structure of the model, a model reformulation scheme based on the use of equilibrium conditions is presented. A linearization scheme is also adopted that involves the introduction of mixed integer variables.

Global optimization of multiscenario mixed integer nonlinear programming models arising in the synthesis of integrated water networks under uncertainty

The development of intermodal container transport is hampered in part by the cost associated with the shunting of trains in marshalling yards, inland and port railway terminals. Many new technologies have been developed in the past decade, but have still not been applied because of high capital investment costs, lack of sufficient market demand and uncertain rates of return. The key for increasing the competitiveness of intermodal container transport by rail is the operation of heavy haul container trains between port and inland railway terminals more frequently with fast, flexible and automatic transhipment, shunting and coupling of container wagons. The operation of self-driven railcars equipped with automatic centre coupling on terminal tracks, which can also be train-hauled on conventional hinterland railway lines, would enable a reduction of shunting and transhipment time and costs in intermodal container terminals by more than 30%.

To solve the problem of long logistics delivery time in supply chain, a Mixed Integer Non-linear Program (MINLP) model is built by using Mixed Integer nonlinear programming theory. Firstly, the General algebraic modeling system (GAMS) is used to build the model to fully integrate each parameter of logistics transportation, the total distribution time of the supply chain network, the coverage radius of the logistics base, the number of users, the total capacity of the logistics base, the mode of railway and road transportation, the nonlinear programming model is built and solved by DICOPT solver in GAMS. The cost of logistics can be decreased, transportation time can be reduced, and the logistics system's operating efficiency can be increased in the long term with the help of this algorithm. The proper operation of the logistics system is critical in encouraging the supply chain circulation of various industries and has a direct impact on the society's economic development. The optimal logistics distribution plan with 5 logistics bases covered users of 18 and railway capacity of 2. With the same railway capacity and the same total budget, the larger the number of covered users, the greater the total distribution time increases, but the larger the total budget, the growth of the total distribution time slows down significantly. Experiments show that MINLP model can solve the problem of logistics-based layout optimization in nonlinear logistics management.

Optimising crop planning in conjunction with intra-seasonal water allocation necessitates the use of daily water budget calculations to determine the timing and amount of irrigation events, which complicates the solution of the problem to global optimality. The main objective of this research was to compare the intra-seasonal water allocation of a mixed integer nonlinear programming (MINLP) model with that of differential evolution (DE), to allocate a limited amount of water while considering irrigable area and the irrigation schedule that will maximise the total gross margin. Results show that both solution procedures adhere to economic theory of water allocation under limited water supply. The conclusion is that the MINLP model most likely achieved very near global optimality as the solutions of the two models were very close to each other. DE holds promise to solve more complex models involving risk and multiple crops.

Abstract. International initiatives have successfully brought down the emissions, and hence also the related negative impacts on environment and human health, from shipping in Emission Control Areas (ECAs). However, the question remains as to whether increased shipping in the future will counteract these emission reductions. The overall goal of this study is to provide an up-to-date view on future ship emissions and provide a holistic view on atmospheric pollutants and their contribution to air quality in the Nordic (and Arctic) area. The first step has been to set up new and detailed scenarios for the potential developments in global shipping emissions, including different regulations and new routes in the Arctic. The scenarios include a Baseline scenario and two additional SOx Emission Control Areas (SECAs) and heavy fuel oil (HFO) ban scenarios. All three scenarios are calculated in two variants involving Business-As-Usual (BAU) and High-Growth (HiG) traffic scenarios. Additionally a Polar route scenario is included with new ship traffic routes in the future Arctic with less sea ice. This has been combined with existing Current Legislation scenarios for the land-based emissions (ECLIPSE V5a) and used as input for two Nordic chemistry transport models (DEHM and MATCH). Thereby, the current (2015) and future (2030, 2050) air pollution levels and the contribution from shipping have been simulated for the Nordic and Arctic areas. Population exposure and the number of premature deaths attributable to air pollution in the Nordic area have thereafter been assessed by using the health assessment model EVA (Economic Valuation of Air pollution). It is estimated that within the Nordic region approximately 9900 persons died prematurely due to air pollution in 2015 (corresponding to approximately 37 premature deaths for every 100 000 inhabitants). When including the projected development in both shipping and land-based emissions, this number is estimated to decrease to approximately 7900 in 2050. Shipping alone is associated with about 850 premature deaths during present-day conditions (as a mean over the two models), decreasing to approximately 600 cases in the 2050 BAU scenario. Introducing a HFO ban has the potential to lower the number of cases associated with emissions from shipping to approximately 550 in 2050, while the SECA scenario has a smaller impact. The “worst-case” scenario of no additional regulation of shipping emissions combined with a high growth in the shipping traffic will, on the other hand, lead to a small increase in the relative impact of shipping, and the number of premature deaths related to shipping is in that scenario projected to be around 900 in 2050. This scenario also leads to increased deposition of nitrogen and black carbon in the Arctic, with potential impacts on environment and climate.

A new, R-graph based, superstructure and corresponding MINLP model for designing conventional distillation columns are presented. A GDP representation (GR) of the superstructure is first constructed, then it is transformed to MINLP representation to which, in turn, additional trivial improvements are added. The new model has been tested on binary mixture examples, and the obtained results are compared to the results of an MINLP model which developed according to the GDP model of Yeomans and Grossmann. 9 The new model yields shorter computation time and provides better local optima. Additionally, the new model has been used for optimizing a complex multicomponent separation system consisting of several distillation columns. In order to handle such a complex system with a huge number of nonlinear equations, the outer approximation algorithm is modified to provide good initial values for the NLP subproblems. Distillation is one of the most widespread processes applied for separating multicomponent liquid mixtures. It is used for working up large volume or stream, and it requires high investment and operation outlays. The significance of the design of economically optimal distillation processes is of no question. Enormous interest has also been addressed to the area of designing optimal heat integrated distillation columns and distillation sequences. Minimizing the cost of a distillation process implies finding the optimal configuration of each individual column, as well. In the present article we consider staged column models only. The number of stages, and the stage numbers of the feed and side-stream points, are discrete decision variables. The total cost of a column may be modeled as the sum of the fix (capital) cost, depending on the number of stages and on the column diameter, and the variable (operation) cost related to the utility consumption. The objective of the design procedure is to find the optimal configuration of the column, which has the minimum total (annualized) cost. In order to model these processes, discrete decisions are required for calculating the number of stages. Optimizing single columns is a well-known procedure; all the basic textbooks outline how to do it in an easy manner. 1 After approximately determining the minimum and the estimated optimal number of theoretical stages, optimizing over the continuous variables is performed at varied values of the discrete variables. This is a 2-dimension discrete array of continuous optimization tasks in the case of a single-feed, two-product column, because there are merely two column sections in this case. This task becomes much more difficult if several feeds and side-products are to be taken into account. The real problem, however, is synthesizing a distillation sequence, or a system of advanced distillation columns, or a complex flowsheet containing distillation units when the number of distillation columns and their connections are not known in advance. In order to solve the complex synthesis problem outlined above, a proper superstructure for a single column, together with a proper generalized disjunctive programming (GDP) model or a proper mixed-integer nonlinear programming (MINLP) model, is a minimum requirement. Once such a model works well for a single column, the problem of more complex flowsheets may also be addressed. Mixed-integer nonlinear programming (MINLP) and generalized disjunctive programming (GDP) are the two exact methodologies commonly applied for solving process engineering problems with discrete decisions. The former includes algebraic equations describing the process, and binary variables related to discrete decisions. The latter method uses logic variables and expressions to represent the problem. 2 Both formulations have been successfully applied to rigorous models of distillation columns. Both methods apply a fixed maximum number of stages, and the actually used stages are selected from this set. Mathematical formulations that represent rigorous models of distillation column configurations fall into two categories: (i) one task-one equipment (OTOE) representations and (ii) variable task-equipment (VTE) representations. 3

Reformulation, linearization, and a hybrid iterated local search algorithm for economic lot-sizing and sequencing in hybrid flow shop problems

In order to make better assessment of intermodal container transportation, the authors have analyzed DEA (Data Envelopment Analysis) method in deciding the most favorable container line from Serbian ports to the near East ports. To allow for applications to a wide variety of activities, term organization unit (Decision Making Unit – DMU) refers to container line. DEA Method has been used to give the estimation of efficiency of operations in organization units. Organization units are container lines in which containers are loaded with mineral water in bottles. The main points in transportation net are factories of mineral water (Knjaz Milos Arandjelovac and Minaqua Novi Sad), Serbian ports ( the Port of Belgrade, the Port of Danube Pancevo and the Port of Prahovo) and nine Mediterranean ports in the near East area. Amount of mineral water that is dispatching from factories to Serbian ports is equal to amount that can be loaded to one container. Having containerized in Serbian ports mineral water is reloaded to the river–sea ships with unified dimensions, so the ships are continuing to travel to the near East ports. The near East ports are the ending points. Input variables in DEA problem are transportation costs and strategy resistance factor in function of container line. Time traveling of one container is in a function of container line and transportation capabilities of container lines are output variables. Transportation costs are counted on the base of integer programming method and Dijkstra algorithm.

The Design and Synthesis of Batch/Semicontinuous Processes

The study analyzes the participation of technologies related to the development of the Internet of Things (IoT) network concept in the intermodal container transportation system. Since the beginning of the XXI century, IoT-related technologies have been dynamically spreading in almost all areas of international business, and this has changed the understanding of cargo owners about the quality of transportation services, among other things. Since transparency in monitoring the location of high-value goods is extremely important for transport companies, cargo owners, and all other stakeholders, and the intermodal transportation system is extremely complex due to the number and diversity of communications, the need to use IoT is obvious. As analysts predict that the introduction of IoT technologies in containerization will become widespread in the coming years, a study to assess the level of research on the introduction of such technologies and implementation in the practical activities of transport enterprises is relevant. The aim of the proposed review is to determine the degree of IoT implementation in the container transportation industry, areas of research on the topic, and identify factors that may impede the predicted rapid development of IoT in containerization. The proposed study includes an analysis of scientific publications related to the use of the Internet of Things in the field of international container transportation, identifies the main priority areas of such publications, establishes the areas of current implementation of IoT technology and determines the prospects for its use. Since the solutions that can potentially be obtained with the help of IoT are quite heterogeneous, the literature analysis is organized by grouping such publications into the following areas: container monitoring and tracking, enhancing supply chain transparency and visibility, optimization of operational efficiency, security and risk management, environmental impact and sustainability, challenges and barriers. The paper provides examples of online platforms and applications currently offered by major container operators that are related to this technology.

Handling of removable discontinuities in MINLP models for process synthesis problems, formulations of the Kremser equation

Optimization of alternative structures of integrated power and desalination plants

This chapter presents a mixed integer non-linear programming (MINLP) model for a fuzzy parallel machine scheduling problem under fuzzy job deterioration and learning effects with fuzzy processing times in order to minimize fuzzy makespan. The uncertainty of parameters such as learning/deterioration effects and processing times in a scheduling problem makes the solution of the problem uncertain. Fuzzy sets can be used to encode uncertainty in parameters. In this chapter, possibilistic distributions of fuzzy parameters and possibilistic linear programming approaches are used in order to create a solution method for MINLP model of fuzzy parallel machine scheduling problem.