Many real life optimization problems are nonconvex and may have several local minima within their feasible region. Therefore, global search methods are needed. Metaheuristics are efficient global optimizers including a metastrategy that guides a heuristic search. Genetic algorithms, simulated annealing, tabu search and scatter search are the most well-know metaheuristics. In general, they do no...

This paper deals with the problem of inaccuracy of the solutions generated by metaheuristic approaches for bi-criteria {0,1}-knapsack problems. A hybrid approach which combines systematic and heuristic search is proposed to reduce that inaccuracy in the context of a scatter search method. The components of the method are used to determine regions in the decision space to be systematically searc...

In this paper, we study a two-dimensional vehicle loading and routing problem in which customer orders with deadlines become available for dispatch as per their release dates. The objective is to minimize the sum of transportation, inventory, tardiness costs while respecting various constraints. This scenario allows us tradeoffs that tend arise due temporal order aggregation across We thereby p...

Scatter search (SS) and path relinking (PR) are evolutionary methods that have been successfully applied to a wide range of hard optimization problems. The fundamental concepts and principles of the methods were first proposed in the 1970s and 1980s, and were based on formulations, dating back to the 1960s, for combining decision rules and problem constraints. The methods use strategies for sea...

We focus on hybrid solution methods for a large-scale realworld multimodal homecare scheduling (MHS) problem, where the objective is to find an optimal roster for nurses who travel in tours from patient to patient, using different modes of transport. In a first step, we generate a valid initial solution using Constraint Programming (CP). In a second step, we improve the solution using one of th...

the bi-objective warehouse problem in a crisp environment is often not eective in dealing with the imprecision or vagueness in the values of the problem parameters. to deal with such situations, several researchers have proposed that the parameters be represented as fuzzy numbers. we describe a new algorithm for fuzzy bi-objective warehouse problem using a ranking function followed by an applic...

In presence of multiple objectives to be optimized in Search-Based Software Engineering (SBSE), Pareto search has been commonly adopted. It searches for a good approximation the problem’s Pareto-optimal solutions, from which stakeholders choose most preferred solution according their preferences. However, when clear preferences (e.g., set weights that reflect relative importance between objecti...