Industrial and Tramp Ship Routing Problems: Closing the Gap for Real-Scale Instances

Recent studies in maritime logistics have introduced a general ship routing problem and a benchmark suite based on real shipping segments, considering pickups and deliveries, cargo selection, ship-dependent starting locations, travel times and costs, time windows, and incompatibility constraints, among other features. Together, these characteristics pose considerable challenges for exact and heuristic methods, and some cases with as few as 18 cargoes remain unsolved. To face this challenge, we propose an exact branch-and-price (B&P) algorithm and a hybrid metaheuristic. Our exact method generates elementary routes, but exploits decremental state-space relaxation to speed up column generation, heuristic strong branching, as well as advanced preprocessing and route enumeration techniques. Our metaheuristic is a sophisticated extension of the unified hybrid genetic search. It exploits a set-partitioning phase and uses problem-tailored variation operators to efficiently handle all the problem characteristics. As shown in our experimental analyses, the B&P optimally solves 239/240 existing instances within one hour. Scalability experiments on even larger problems demonstrate that it can optimally solve problems with around 60 ships and 200 cargoes (i.e., 400 pickup and delivery services) and find optimality gaps below 1.04% on the largest cases with up to 260 cargoes. The hybrid metaheuristic outperforms all previous heuristics and produces near-optimal solutions within minutes. These results are noteworthy, since these instances are comparable in size with the largest problems routinely solved by shipping companies

Extending sustainability from food to fashion consumption:the lived experience of working mothers

This report isa collection of the memos written in work package 1 of the LambdaRoad project, where the overall project objectives is to study the need and requirements for electronic communication (ecom) in the future transport system in Norway and develop a planning tool for ecom for the transport sector. lntroductory studies were performed in work package 1 and documented in this report. In particular we 1) have established va lue networks for ecom in Norway, 2) described the crucial terms in C-ITS ecom, including motivation for the planning tool, 3) established a comprehensive state of the art study for path loss models, a crucial part of the planning tool to be developed, 4) studied the literature to summarize the ecom requirements in the future transport system, and 5) conducted in-depth semi -structured interviews to reveal the requirements and needs of the planning tool in LambdaRoad for the project partners. Please note that some of the memos included might change during the rest of the project period, and that updates may occur

Risk control in maritime shipping investments

In this paper we extend the state-of-the-art stochastic programming models for the Maritime Fleet Renewal Problem (MFRP) to explicitly limit the risk of insolvency due to negative cash flows when making maritime shipping investments. This is achieved by modeling the payment of ships in a number of periodical installments rather than in a lump sum paid upfront, representing more closely the actual cash flows for a shipping company. Based on this, we propose two alternative risk control measures, where the first imposes that the cash flow in each time period is always higher than a desired threshold, while the second limits the Conditional Value-at-Risk. We test the two models on realistic test instances based on data from a shipping company. The computational study demonstrates how the two models can be used to assess the trade-offs between risk of insolvency and expected profits in the MFRP

Tramp Ship Scheduling Problem with Berth Allocation Considerations and Time-dependent Constraints

This work presents a model for the Tramp Ship Scheduling problem including berth allocation considerations, motivated by a real case of a shipping company. The aim is to determine the travel schedule for each vessel considering multiple docking and multiple time windows at the berths. This work is innovative due to the consideration of both spatial and temporal attributes during the scheduling process. The resulting model is formulated as a mixed-integer linear programming problem, and a heuristic method to deal with multiple vessel schedules is also presented. Numerical experimentation is performed to highlight the benefits of the proposed approach and the applicability of the heuristic. Conclusions and recommendations for further research are provided.Comment: 16 pages, 3 figures, 5 tables, proceedings paper of Mexican International Conference on Artificial Intelligence (MICAI) 201

Heuristics for dynamic and stochastic routing in industrial shipping

Maritime transportation plays a central role in international trade, being responsible for the majority of long-distance shipments in terms of volume. One of the key aspects in the planning of maritime transportation systems is the routing of ships. While static and deterministic vehicle routing problems have been extensively studied in the last decades and can now be solved effectively with metaheuristics, many industrial applications are both dynamic and stochastic. In this spirit, this paper addresses a dynamic and stochastic maritime transportation problem arising in industrial shipping. Three heuristics adapted to this problem are considered and their performance in minimizing transportation costs is assessed. Extensive computational experiments show that the use of stochastic information within the proposed solution methods yields average cost savings of 2.5% on a set of realistic test instances

Å lede i en ny æra : Et konseptuelt studie av positivt lederskap, innovasjon og digitalisering

Problemet​: Å lede kunnskapsarbeidere til å forløse den kunnskap og kreativitet som kreves for verdiskapning i den fjerde industrielle revolusjon. Problemstilling​: Hvordan kan digitalisering fremme innovasjon gjennom positivt lederskap? Fremgangsmåte​: Ved hjelp av konseptuell generalisering har vi utviklet en analytisk modell som viser hvordan positivt lederskap kan fremme innovasjon gjennom digitalisering. Hensikt​: Å kunne lede de menneskelige ressurser og den interne kunnskap som ligger latent i organisasjonen for å fremme innovasjon i et samfunn der individualisering og høy endringstakt står i sentrum. Hovedfunn​: - Positivt lederskap gir rom for selvledelse gjennom oppmuntring til positive tankemønstre og naturlig belønning, ved hjelp av motivasjon og mestring i en samhandlingskontekst mellom leder og medarbeider. - Tillit fungerer som et sentralt virkemiddel ved oppmuntring til selvledelse. - Selvledelse gir rom for kreativitet gjennom ekspertise, indremotivasjon, mestringstro og autonomi. - Kunnskapsdeling fremmer kreativitet gjennom samhandling. - Digitalisering skaper produktivitet som frigjør menneskelige ressurser fra standardiserte oppgaver, som viser seg nyttig for innovasjon

På hvilke måter kan TOMS og Uggs sitt samfunnsengasjement påvirke forbrukerens holdninger til merkevaren?

Denne oppgaven tar for seg temaene påvirkning og samfunnsansvar. Vi ønsket å teste hvordan samfunnsansvaret til skomerkene TOMS og UGGS kan påvirke forbrukeres holdninger til merkevarene. Vi har benyttet Cialdinis forskning som en grunnmur for videre analyser. Vi ønsker også å teste hvilke bakgrunnsvariabler som er med å påvirke og danne holdninger knyttet til merkevarene. Basert på dette utformet vi problemstillingen “På hvilke måter kan TOMS og Uggs sitt samfunnsengasjement påvirke forbrukerens holdninger til merkevaren?”. For å kunne svare på denne problemstillingen utviklet vi tre hypoteser. Vi starter oppgaven med en teoridel hvor vi ser på de ulike elementene i problemstillingen. Vi ønsket å se nærmere på samfunnsansvar, påvirkning, forbrukere, holdninger og merkevarer. Vi startet prosessen ved å utføre en pre-test, for å teste kvaliteten på spørsmålene våres. Undersøkelsen består av en kvantitativ metode og tverrsnittsundersøkelse design. For å teste hypotesene våre, ble respondentene presentert for en caseoppgave i undersøkelsen. Casen besto av to alternativer hvor de enten hadde muligheten til å kjøpe sko og støtte et godt formål, eller kjøpe billigere sko til egen fordel. Resultatene fra undersøkelsen ble analysert i det statistiske programmet SPSS, der vi blant annet gjennomførte en deskriptiv-, regresjons og multiple response analyse. Vi benytter ulike analyser for ulike variabler, for å kunne tolke og forstå data. Multiple response analysen viser prosentvis hva respondentene har svart, og vi har tilgang til alle bakgrunnsvariabler. Modellen skiller gruppen, og vi ser hva som påvirker, hvilke holdninger og hva respondentene assosierer med merkevaren

Combined maritime fleet deployment and inventory management with port visit flexibility in roll-on roll-off shipping

We consider a combined fleet deployment and inventory management problem in Roll-on Roll-off shipping. Along given trade routes there are ports with inventories that should be kept within their limits. Current planning practice is to visit all ports every time a trade route is serviced. We instead aim at determining the sailing routes of each voyage along the trade route, where some ports can be skipped on certain voyages. A novel mixed integer programming model is proposed and tested on realistic instances. The results indicate that substantial gains can be achieved from this more flexible way of planning

Titrating complex mass cytometry panels

We describe here a simple and efficient antibody titration approach for cell‐surface markers and intracellular cell signaling targets for mass cytometry. The iterative approach builds upon a well‐characterized backbone panel of antibodies and analysis using bioinformatic tools such as SPADE. Healthy peripheral blood and bone marrow cells are stained with a pre‐optimized “backbone” antibody panel in addition to the progressively diluted (titrated) antibodies. Clustering based on the backbone panel enables the titration of each antibody against a rich hematopoietic background and assures that nonspecific binding and signal spillover can be quantified accurately. Using a slightly expanded backbone panel, antibodies quantifying changes in transcription factors and phosphorylated antigens are titrated on ex vivo stimulated cells to optimize sensitivity and evaluate baseline expression. Based on this information, complex panels of antibodies can be thoroughly optimized for use on healthy whole blood and bone marrow and are easily adaptable to the investigation of samples from for example clinical studies.publishedVersio