Discrete optimization

About: Discrete optimization is a research topic. Over the lifetime, 4598 publications have been published within this topic receiving 158297 citations. The topic is also known as: discrete optimisation.

Multi-Colony Ant Algorithm for Continuous Multi-Reservoir Operation Optimization Problem

Abstract: Ant Colony Optimization (ACO) algorithms are basically developed for discrete optimization and hence their application to continuous optimization problems require the transformation of a continuous search space to a discrete one by discretization of the continuous decision variables. Thus, the allowable continuous range of decision variables is usually discretized into a discrete set of allowable values and a search is then conducted over the resulting discrete search space for the optimum solution. Due to the discretization of the search space on the decision variable, the performance of the ACO algorithms in continuous problems is poor. In this paper a special version of multi-colony algorithm is proposed which helps to generate a non-homogeneous and more or less random mesh in entire search space to minimize the possibility of loosing global optimum domain. The proposed multi-colony algorithm presents a new scheme which is quite different from those used in multi criteria and multi objective problems and parallelization schemes. The proposed algorithm can efficiently handle the combination of discrete and continuous decision variables. To investigate the performance of the proposed algorithm, the well-known multimodal, continuous, nonseparable, nonlinear, and illegal (CNNI) Fletcher–Powell function and complex 10-reservoir problem operation optimization have been considered. It is concluded that the proposed algorithm provides promising and comparable solutions with known global optimum results.

Optimization of trusses using genetic algorithms for discrete and continuous variables

Abstract: This paper demonstrates the use of genetic algorithms (GAs) for size optimization of trusses. The concept of rebirthing is shown to be considerably effective for problems involving continuous design variables. Some benchmark examples are studied involving 4‐bar, 10‐bar, 64‐bar, 200‐bar and 940‐bar two‐dimensional trusses. Both continuous and discrete variables are considered.

Optimal kinematic design of a haptic pen

Abstract: This paper investigates the performance demands of a haptic interface and shows how this information can be used to design a suitable mechanism. A design procedure, previously developed by the authors (1996), consisting of a global isotropy index and a discrete optimization algorithm, allows one to compare a range of geometric variables, actuator scale factors, and even different robot devices for optimum performance. The approach is used to compare the performance of three 6-DOF robots including two well-known parallel platform robots and a novel hybrid robot called the Twin-Pantograph in terms of their semi-dextrous workspaces and static force capabilities. Since the Twin-Pantograph yields the best results, its design is refined to address practical constraints and it is implemented as a haptic pen. The performance of the resulting design is analysed and presented.

Introduction to engineering design optimization

Abstract: 1: Introduction. 2: Linear Programming. 3: Single-Variable Optimization Techniques. 4: Unconstrained Multivariable Optimization. 5: Constrained Optimization. 6: Monotonicity Analysis and Johnson's Method. 7: Probabilistic Design Optimization. 8: Further Topics in Optimization.