Selecting Algorithms for the Efficient Solving of Large Berth Allocation Problems

International audienceIn this presentation, the algorithm selection for the berth allocation problem (BAP) under solution time limits is considered. BAP consists in scheduling ships on berths subject to ready times and ship size constraints, in minimum turnaround time. For the purposes of strategic port capacity planning, BAP must be solved many times in extensive simulations, needed to account for uncertainties on ship traffic, handling times, and also to consider alternative terminal designs. Exact methods exist that solve BAP problems on medium size instances in a few minutes. However, theses methods cannot be adapted to solve many large instances in a short time limit. Even metaheuristics may be too consuming in this setting. The Algorithm Selection Problem (ASP) is the challenge of selecting algorithms with the best overall performance for the considered application. An approach is proposed here to select a portfolio of algorithms, that will each solve the considered BAP instances and return good solutions. The portfolio is built thanks to training instances. The performance is measured by runtime and solution quality. A linear program minimizing the solution quality loss, subject to overall runtime limit, is used to select the portfolio. Thus, the portfolio evolves with changing runtime limits, which is a key design decision in the simulations. For the training and validating datasets, random instances and real ship traffic logs are used. In our experimental study, a portfolio of heuristics is developed which can be used to solve efficiently very large instances of BAP, emerging when time horizons of months or years come into consideration. The evolution of the algorithm portfolios under changing runtime limits as well as their ability to solve new instances are studied

MEDtube Science

ABSTRACT Kidney transplantation from a living donor is a method of choice in the treatment of end-stage renal disease. The programme of care for a living kidney donor should cover the assessment of health status and quality of life and an analysis of the data collected on the basis of the same criteria. The conclusions drawn should be used in the assessment of the risk associated with the kidney harvesting procedure, assessment of the health status of the living donor and an improvement of the results of kidney transplantation from a living donor

From online to offline – a website for organisation of social meetings

Przedmiotem niniejszej pracy jest serwis internetowy umożliwiający użytkownikom planowanie spotkań towarzyskich organizowanych w celu realizowania wspólnych pasji ich uczestników. Motywacją do stworzenia tego typu aplikacji była chęć zbudowania w Internecie miejsca, gdzie każda pełnoletnia osoba miałaby możliwość znajdowania ludzi podobnych sobie, z którymi mogłaby rozwijać swoje, często oryginalne, zainteresowania. Zadaniem projektu jest umożliwianie internautom zawieranie znajomości online, a następnie rozwijanie ich już w realnym świecie poprzez realizowanie określonych aktywności. Za pośrednictwem serwisu można zarówno organizować własne, maksymalnie kilkunastoosobowe spotkania, jak i dołączać do tych już istniejących, utworzonych przez innych użytkowników.Aplikacja została napisana w języku Python przy użyciu frameworka Django zgodnie z obowiązującymi standardami oraz współczesnymi trendami tworzenia stron internetowych.The subject of this study is the website which enables users to plan social meetings in order to realize common passions of their participants. Motivation for creating this kind of web application was inclination to build a place, in the Internet, where every adult would have an opportunity to find people with similar interests, with whom he or she could develop his/her passions. The project’s aim is to make it possible for Internet users to make acquaintances online and then develop acquaintanceship in the real world by realizing specified activities together. Through the website it is possible both organising own group meetings and joining to already existing concepts, created by other users.Application was written in Python language using Django framework according to applicable standards and modern trends of creating websites

Selecting Algorithms for Large Berth Allocation Problems

International audienceThis paper considers algorithm selection for the berth allocation problem (BAP) under algorithmruntime limits. BAP consists in scheduling ships on berths subject to ship ready times and sizeconstraints, for a certain objective function. For the purposes of strategic port capacity planning,BAP must be solved many times in extensive simulations, needed to account for ship traffic andhandling times uncertainties, and alternative terminal designs. The algorithm selection problem(ASP) consists in selecting algorithms with the best performance for a considered application. Wepropose a new method of selecting a portfolio of algorithms that will solve the considered BAPinstances and return good solutions. The portfolio selection is based on the performance on thetraining instances. The performance is measured by the runtime and solution quality. In orderto select the portfolio, a linear program minimizing the solution quality loss, subject to overallruntime limit is used. Thus, the portfolio evolves with the runtime limit, which is a key parameter indesigning the port capacity simulations. For the training and validating datasets, random instancesand real ship traffic logs are used. A portfolio of heuristics is developed which can be used forsolving large instances of BAP, emerging when time horizons of months or years are considered.The evolution of the algorithm portfolios under changing runtime limits is studied. The portfolioabilities to solve new instances are assessed

A container ship traffic model for simulation studies

The aim of this paper is to develop a container ship traffic model for port simulation studies. Such a model is essential for terminal design analyses and testing the performance of optimization algorithms. This kind of studies requires accurate information about the ship stream to build test scenarios and benchmark instances. A statistical model of ship traffic is developed on the basis of container ship arrivals in eight world ports. The model provides three parameters of the arriving ships: ship size, arrival time and service time. The stream of ships is divided into classes according to vessel sizes. For each class, service time distributions and mixes of return time distributions are provided. A model of aperiodic arrivals is also proposed. Moreover, the results achieved are used to compare port specific features

Selecting Algorithms for the Efficient Solving of Large Berth Allocation Problems

International audienceIn this presentation, the algorithm selection for the berth allocation problem (BAP) under solution time limits is considered. BAP consists in scheduling ships on berths subject to ready times and ship size constraints, in minimum turnaround time. For the purposes of strategic port capacity planning, BAP must be solved many times in extensive simulations, needed to account for uncertainties on ship traffic, handling times, and also to consider alternative terminal designs. Exact methods exist that solve BAP problems on medium size instances in a few minutes. However, theses methods cannot be adapted to solve many large instances in a short time limit. Even metaheuristics may be too consuming in this setting. The Algorithm Selection Problem (ASP) is the challenge of selecting algorithms with the best overall performance for the considered application. An approach is proposed here to select a portfolio of algorithms, that will each solve the considered BAP instances and return good solutions. The portfolio is built thanks to training instances. The performance is measured by runtime and solution quality. A linear program minimizing the solution quality loss, subject to overall runtime limit, is used to select the portfolio. Thus, the portfolio evolves with changing runtime limits, which is a key design decision in the simulations. For the training and validating datasets, random instances and real ship traffic logs are used. In our experimental study, a portfolio of heuristics is developed which can be used to solve efficiently very large instances of BAP, emerging when time horizons of months or years come into consideration. The evolution of the algorithm portfolios under changing runtime limits as well as their ability to solve new instances are studied

The use of expanded clay aggregate for the pretreatment of surface waters on the example of a tributary of Lake Klasztorne Górne in Strzelce Krajeńskie

The paper presents a proposal for the treatment of river water based on expanded clay (ceramsite). It is a lightweight mineral aggregate containing components relative to phosphorus adsorption (calcium, iron, manganese, aluminum). A pilot plant on a fractional technical scale was built on a nutrient rich (phosphorus up to 0.4 mg dm−3, nitrogen up to 10.0 mg dm−3), small (mean annual flow about 0.04 m3 s−1), natural watercourse (Młynówka River, a tributary of the Otok Channel, Noteć basin, the municipality of Strzelce Krajeńskie). The monitoring included quantitative and qualitative measurements of the water stream in 2014-2015. On the basis of the examinations, the calculated effectiveness of ceramsite filters in removing major contaminants from water was: for total nitrogen 5-6%, phosphorus 12-16%, and for suspensions 17-29%. The effectiveness of the treatment is highly influenced by hydraulic load, so this type application on a full-scale should occupy a sufficiently large volume. Taking into account simplicity of performance, ease of operation and low cost of construction and maintenance, such pretreatment plants based on expanded clay would seem to be a promising tool for the protection of surface waters in catchments of small rivers and streams

Quay partitioning problem

International audienceAbstract In this paper, we introduce the quay partitioning problem (QPP), that is, a problem of partitioning quay length into berths for minimum ship waiting time. Such a problem arises when designing the terminal layout. Two schemes of quay layout are considered: with at most one ship in a berth and with at most two ships in a berth. Ship arrival times, service times, lengths, and weights are given. We show that QPP is NP ‐hard. The two versions of QPP are formulated as mixed integer linear programs (MIPs). Scalability of solving QPPs as MIPs is studied. We investigate, analytically and in computational experiments, features of the QPP solutions such as (i) changes in solution quality when one long berth length is used versus choosing various berth lengths flexibly, (ii) what lengths of berths are chosen when ship lengths mixture is changing, (iii) what is the impact of congestion on the chosen berth lengths, and (iv) how much is one quay layout scheme better than the other