Multi-objective evolutionary algorithms (MOEAs) have shown promising performance in
solving various optimization problems, but their performance may deteriorate drastically …

This paper introduces an Unmanned Aerial Vehicle (UAV) heterogeneous fleet routing
problem, dealing with vehicles limited autonomy by considering multiple charging stations …

Combining ant colony optimization (ACO) and the multiobjective evolutionary algorithm (EA)
based on decomposition (MOEA/D), this paper proposes a multiobjective EA, ie, MOEA/D …

The collaboration of drones and trucks for last-mile delivery has attracted much attention. In
this paper, we address a collaborative routing problem of the truck-drone system, in which a …

Metaheuristics are algorithms that have proven their efficiency on multi-objective
combinatorial optimisation problems. They often use local search techniques, either at their …

After more than 10 years from the first edition of this book, the need for multi-objective
optimization models in freight logistics is still growing. Companies engineer always more …

Multiobjective optimization problems are problems with several, typically conflicting, criteria
for evaluating solutions. Without any a priori preference information, the Pareto optimality …

The knapsack problem (KP) and its multidimensional version (MKP) are basic problems in
combinatorial optimization. In this paper, we consider their multiobjective extension (MOKP …

This paper studies a new variant of integrated production scheduling and vehicle routing
problem where production of customer orders are performed under job-shop environment …

Most multiobjective optimization algorithms maintain an archive explicitly or implicitly during
their search. Such an archive can be solely used to store high-quality solutions presented to …