Returtømmer - Effektiv bruk av retursløyfer i tømmertransport

Denne rapporten presenterer resultatene fra arbeidet utført i prosjektet "Returtømmer". Prosjektet har hatt som mål å belyse muligheten for økt bruk av returkjøring i transport av tømmer gjennom bruk av optimeringsbaserte modeller. I prosjektet er det utviklet metoder for automatisk planlegging av tømmertranport slik at transportplanleggere kan få ruteforslag basert på transportklart tømmer, avstander, kvanta med mer. Basert på de foreslåtte metodene er det utviklet en enkel demonstrator for testing og denne er benyttet på et testcase basert på historiske data for hele Midt-Norge. Resultatene viser at en optimeringsbasert tilnærming er teknisk gjennomførbar med betydelig muligheter for økt bruk av returkjøring. Analysene utført på testcaset viser mulige reduksjoner rundt 15 % i total kjøredistanse sammenlignet med å ikke benytte seg av returkjøring.publishedVersio

Optimization and reconstruction of hv-convex (0,1)-matrices

AbstractWe consider a variant of the NP-hard problem of reconstructing hv-convex (0,1)-matrices from known row and column sums. Instead of requiring the ones to occur consecutively in each row and column, we maximize the number of neighboring ones. This is reformulated as an integer programming problem. A solution method based on variable splitting is proposed and tested with good results on moderately sized test problems

GAFT - Economic viability assessment

publishedVersio

Returtømmer - Effektiv bruk av retursløyfer i tømmertransport

Denne rapporten presenterer resultatene fra arbeidet utført i prosjektet "Returtømmer". Prosjektet har hatt som mål å belyse muligheten for økt bruk av returkjøring i transport av tømmer gjennom bruk av optimeringsbaserte modeller. I prosjektet er det utviklet metoder for automatisk planlegging av tømmertranport slik at transportplanleggere kan få ruteforslag basert på transportklart tømmer, avstander, kvanta med mer. Basert på de foreslåtte metodene er det utviklet en enkel demonstrator for testing og denne er benyttet på et testcase basert på historiske data for hele Midt-Norge. Resultatene viser at en optimeringsbasert tilnærming er teknisk gjennomførbar med betydelig muligheter for økt bruk av returkjøring. Analysene utført på testcaset viser mulige reduksjoner rundt 15 % i total kjøredistanse sammenlignet med å ikke benytte seg av returkjøring

A heuristic for rich maritime inventory routing problems

In maritime inventory routing, a fleet of vessels is employed to transport products that are produced and consumed in different ports with limited storage capacity. The tight coupling between inventory management and routing, and diverse constraints make this a challenging problem. We generate a routing plan using an iterative construction algorithm, starting from an empty plan. In each iteration, a constraint violation, e.g. a stockout, is identified. We generate a number of different journeys that can fix the violation and add the best one. This continues until the plan is feasible or no remaining violation can be fixed. The construction algorithm is reused in the optimization phase, where each iteration consists of removing and then rebuilding a part of the plan. We present results on real world cases.A heuristic for rich maritime inventory routing problem

The HyOpt model Input data and mathematical formulation

This report gives a description of the mathematical model underlying the HyOpt model and the associated input data. HyOpt is an optimization model for the design and evaluation of energy systems with a focus on hydrogen-based technology. Given a structure of the energy system plus expected energy demands and costs, the model decides which elements should be included and with what capacity, in order to optimize a given objective—typically maximizing the net present value of the whole modelled system. This problem is formulated as a mixed integer linear optimization problem and solved used using a commercial solver.publishedVersio

The HyOpt model Input data and mathematical formulation

This report gives a description of the mathematical model underlying the HyOpt model and the associated input data. HyOpt is an optimization model for the design and evaluation of energy systems with a focus on hydrogen-based technology. Given a structure of the energy system plus expected energy demands and costs, the model decides which elements should be included and with what capacity, in order to optimize a given objective—typically maximizing the net present value of the whole modelled system. This problem is formulated as a mixed integer linear optimization problem and solved used using a commercial solver

Solving Node Edge Arc Routing Problems in the Distribution of Media Products

There is a strong pressure on economy in the distribution of media products. Two important remedies are more efficient carrier routes and distribution of side products. Both call for effective and dynamic route design and revision processes. These processes are complex, time-consuming, and costly. The size of industrial carrier route planning instances may cause performance problems for VRP algorithms. In the VRP literature, the Capacitated Arc Routing Problem (CARP) is often advocated as an adequate model for applications such as newspaper delivery and garbage collection. We argue that a better model is the Node Edge Arc Routing Problem (NEARP). We describe how we have extended a VRP solver to enable modeling of the NEARP, and extended it with a framework for multi-level aggregation of demand. An aggregation heuristic that is based on the underlying road topology is presented. The resulting solver has been integrated in a commercial web based system for route management and tested by pilot users. We present experimental results on real-life data from newspaper distribution. Results on standard CARP and NEARP instances from the literature are given, including several new best known solutions.Solving Node Edge Arc Routing Problems in the Distribution of Media Product

The Node Edge Arc Routing Problem - applications and heuristics

In the VRP literature, the Arc Routing Problem is often advocated as an adequate model for routing applications such as newspaper delivery and garbage collection. We argue that a better model is the Node Edge Arc Routing Problem (NEARP), combining demand on nodes, edges, and arcs in a transportation network. We describe how we have extended a node based VRP solver to enable modeling and resolution of the NEARP, and network based heuristics for aggregating node-based demand into demands on arcs and edges. Experimental results on standard benchmarks and industrial cases are presented.The Node Edge Arc Routing Problem - applications and heuristic