A Hybrid Monte Carlo Local Branching Algorithm For The Single Vehicle Routing Problem With Stochastic Demands

Evolutionary Computation in Combinatorial Optimization

This book constitutes the refereed proceedings of the 15th European Conference on Evolutionary Computation in Combinatorial Optimization, EvoCOP 2015, held in Copenhagen, Denmark, in April 2015, co-located with the Evo*2015 events EuroGP, EvoMUSART and EvoApplications. The 19 revised full papers presented were carefully reviewed and selected from 46 submissions. The papers cover methodology, applications and theoretical studies. The methods included evolutionary and memetic (hybrid) algorithms, iterated local search, variable neighbourhood search, ant colony optimization, artificial immune systems, hyper-heuristics and other adaptive approaches. The applications include both traditional domains, such as graph coloring, knapsack, vehicle routing, job-shop scheduling, the p-median and the orienteering problems; and new(er) domains such as designing deep recurrent neural networks, detecting network community structure, lock scheduling of ships, cloud resource management, the fire-fighter problem and AI planning. The theoretical studies involved approximation ratio, runtime and black-box complexity analyses.

A Hybrid Monte Carlo Local Branching Algorithm for the Single Vehicle Routing Problem with Stochastic Demands

Logistics Operations and Management

This book provides a comprehensive overview of how to strategically manage the movement and storage of products or materials from any point in the manufacturing process to customer fulfillment. Topics covered include important tools for strategic decision making, transport, packaging, warehousing, retailing, customer services and future trends. - An introduction to logistics - Provides practical applications - Discusses trends and new strategies in major parts of the logistic industry