This paper formulates the 3D containership loading planning problem (3D CLPP) and also proposes a new and compact representation to efficiently solve it. The key objective of stowage planning is to minimise the number of container movements and also the ship's instability. The binary formulation...

Facility location under uncertain environments is an important and challenging problem. The problem deals with the optimal placement of facilities that serve a set of spatially distributed nodes. One way to deal with this problem is to model uncertainty by means of scenarios and to optimise some...

In this paper a multi-objective genetic algorithm is used to solve a multi-objective model to optimize the time allocation of domestic loads within a planning period of 36 h, in a smart grid context. The management of controllable domestic loads is aimed at minimizing the electricity bill and...

Optimization approaches for PV grid-connected system (PVGCS) have focused on optimizing the technical and economic performances. The main objective of this study is thus to propose an integrated framework that manages simultaneously technical, economic and environmental criteria. Life Cycle...

In this research, a permutation flowshop sequence-dependent group scheduling problem with minimisation of total completion time is considered. Since the problem is shown to be strongly NP-hard, a hybrid genetic (HG) algorithm is proposed. The only available lower bounding (LB) method for the...

Given a settled reduction in the present level of tax revenue, and by exploring a very large combinatorial space of tax structures, in this paper we employ a genetic algorithm in order to determine the optimal structure of a personal income tax that allows the maximization of the redistributive...