الصفحة 1
الصفحة 1
Online Storage Systems and Transportation Problems with Applications : Optimization Models and Mathematical Solutions
This books covers the analysis and development of online algorithms involving exact optimization and heuristic techniques, and their application to solve two real life problems. The first problem is concerned with a complex technical system: a special carousel based high-speed storage system - Rotastore. It is shown that this logistic problem leads to an NP-hard Batch PreSorting problem which is not easy to solve optimally in offline situations. The second problem originates in the health sector and leads to a vehicle routing problem. Reasonable solutions for the offline case covering a whole day with a few hundred orders are constructed with a heuristic approach, as well as by simulated annealing. Optimal solutions for typical online instances are computed by an efficient column enumeration approach leading to a set partitioning problem and a set of routing-scheduling subproblems. The latter are solved exactly with a branch-and-bound method which prunes nodes if they are value-dominated by previous found solutions or if they are infeasible with respect to the capacity or temporal constraints.
Metaheuristics for Hard Optimization : Methods and Case Studies
Metaheuristics for Hard Optimization comprises of three parts. The first part is devoted to the detailed presentation of the four most widely known metaheuristics: the simulated annealing method, tabu search, the evolutionary algorithms, and ant colony algorithms. Each one of these metaheuristics is actually a family of methods, of which the essential elements are discussed. In the second part, the book presents some other less widespread metaheuristics, then, extensions of metaheuristics and some ways of research are described . The problem of the choice of a metaheuristic is posed and solution methods are discussed. The last part concentrates on three case studies from telecommunications, air traffic control, and vehicle routing.
Metaheuristic Procedures for Training Neural Networks
Metaheuristic Procedures For Training Neural Networks provides successful implementations of metaheuristic methods for neural network training. Apart from Chapter 1, which reviews classical training methods, the chapters are divided into three main categories. The first one is devoted to local search based methods, including Simulated Annealing, Tabu Search, and Variable Neighborhood Search.
Flexible and Efficient Information Handling ; 23rd British National Conference on Databases, BNCOD 23, Belfast, Northern Ireland, UK, July 18-20, 2006, Proceedings
This book constitutes the refereed proceedings of the 23rd British National Conference on Databases, BNCOD 23, held in Belfast, Northern Ireland, July 2006. The volume presents 12 revised full papers and 6 revised short papers, together with 2 invited lectures and 13 poster papers. Topical sections include data modelling and architectures and transaction management, data integration and interoperability and information retrieval, query processing and optimisation, data mining, data warehousing and more.
Evolutionary computation in combinatorial optimization ; 8th European Conference, EvoCOP 2008, Naples, Italy, March 26-28, 2008. Proceedings
Metaheuristics have been shown to be e?ective for di?cult combinatorial - timization problems appearing in various industrial, economical, and scientifc domains. Prominent examples of metaheuristics are evolutionary algorithms, tabu search, simulated annealing, scatter search, memetic algorithms, variable neighborhood search, iterated local search, greedy randomized adaptive search procedures, ant colony optimization and estimation of distribution algorithms. Problems solved successfully include scheduling, timetabling, network design, transportation and distribution, vehicle routing, the travelling salesman pr- lem, packing and cutting, satisfability and general mixed integer programming.
