We develop a hybrid algorithm using Genetic Algorithms (GA) and Simulated Annealing (SA) to solve multi-objective step function maximization problems. We then apply the algorithm to a specific economic problem which is taken out of the corporate governance literature.

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...

Bird watching is one of many recreational activities popular in ecotourism. Its popularity, therefore, prompts the need for studies on energy conservation. One such environmentally friendly approach toward minimizing bird watching’s ecological impact is ensuring a reduced carbon footprint by...

The job shop problem is among the class of non-deterministic polynomial time hard combinatorial problems. This research article addresses the problem of static job shop scheduling on the job-based representation and the rule-based representations. The popular search techniques, such as the...

In this paper we propose an approach to predict insolvency of non-life insurance companies based on the application of Support Vector Machines (SVMs), hybridized with two global search heuristics: a Genetic Algorithm (GA) and a Simulated Annealing (SA). A SVM is used to classify firms as failed...

Generalised assignment problem (GAP) is a well-known non-deterministic polynomial (NP) hard combinatorial optimisation problem to find the minimum cost during assignment of jobs to agents so that each job is assigned exactly once and agents are not overloaded. In this research, we look at the...

Non-hierarchical cluster analysis for panel data is known to be hampered by structural preservation, computational complexity and efficiency, and dependency problems. Resolving these issues becomes increasingly important as efficient collection and maintenance of panel data make application more...

This paper presents a new approach to solve the short-term unit commitment problem using genetic algorithm-based simulated annealing method for utility system. The objective of this paper is to find the generation scheduling such that the total operating cost can be minimised when subjected to a...

This paper presents a new approach to solve the short-term unit commitment problem using genetic algorithm-based simulated annealing method for utility system. The objective of this paper is to find the generation scheduling such that the total operating cost can be minimised when subjected to a...

Generalised assignment problem (GAP) is a well-known non-deterministic polynomial (NP) hard combinatorial optimisation problem to find the minimum cost during assignment of jobs to agents so that each job is assigned exactly once and agents are not overloaded. In this research, we look at the...