Abstract For developing countries, scarcity of climatic data is the biggest challenge, and model development with limited meteorological input critical importance. In this study, five intelligent hybrid metaheuristic machine learning algorithms, namely additive regression (AR), AR-bagging, AR-random subspace (AR-RSS), AR-M5P, AR-REPTree, were applied to predict monthly mean daily reference evap...

A computer program, capable of carrying out the mathematical modelling and optimization multi effect evaporation (MEE) systems is developed in scope this study. C# programming language used development program. Particle Swarm Optimization (PSO) based algorithm hybridized with a Levenberg-Marquardt (LM) algorithm. program interface .NET platform for user to give inputs such as feed product strea...

The challenging idea of using drones in last-mile delivery systems logistics addresses a new routing problem referred to as the traveling salesman with drone (TSP-D). TSP-D aims construct route deliver parcels set customers by either truck or drone, thereby minimizing operational costs. Since is considered NP-hard, metaheuristics one most promising solutions. This paper presents hybrid metaheur...

logistic network design is one of the most important strategic decisions in supply chain management that has recently attracted the attention of many researchers. transportation network design is then one of the most important fields of logistic network. this study is concerned with designing a multi-stage and multi-product logistic network. at first, a mixed integer nonlinear programming model...

the traveling salesman problem (tsp) is the problem of finding the shortest tour through all the nodes that a salesman has to visit. the tsp is probably the most famous and extensively studied problem in the field of combinatorial optimization. because this problem is an np-hard problem, practical large-scale instances cannot be solved by exact algorithms within acceptable computational times. ...

This paper describes the development of a novel metaheuristic that combines an electromagnetic-like mechanism (EM) and the great deluge algorithm (GD) for the University course timetabling problem. This well-known timetabling problem assigns lectures to specific numbers of timeslots and rooms maximizing the overall quality of the timetable while taking various constraints into account. EM is a ...

The conventional Unconstrained Binary Quadratic Programming (UBQP) problem is known to be a unified modeling and solution framework for many combinatorial optimization problems. This paper extends the single-objective UBQP to the multiobjective case (mUBQP) where multiple objectives are to be optimized simultaneously. We propose a hybrid metaheuristic which combines an elitist evolutionary mult...