The Traveling Salesman Problem (TSP) is a classical NPhard combinatorial problem that has been intensively studied through several decades. A large amount of literature is dedicated to this problem. TSP can be directly applied to some real life problems, and to be generalized to some other set of important combinatorial problems. Nowadays, a large collection of TSP instances can be found such a...

Service network design involves determination of the most cost-effective transportation network and service characteristics subject to various constraints. Good progress has been made in developing metaheuristic approaches that can compete or even outperform some commercial software packages (Ghamlouche et al 2004; Pedersen et al 2009). However, since most of these metaheuristic methods involve...

Many metaheuristic approaches are inherently stochastic. In order to compare such methods, statistical tests needed. However, choosing an appropriate test is not trivial, given that each has some assumptions about the distribution of underlying data must be true before it can used. Permutation (P-Tests) with minimal number assumptions. These simple, intuitive and nonparametric. this paper, we a...

Annual Crop Planning (ACP) is an NP-hard-type optimization problem in agricultural planning. It involves finding optimal solutions concerning the seasonal allocations of a limited amount of agricultural land amongst the various competing crops that are required to be grown on it. This study investigates the effectiveness of employing three new local search (LS) metaheuristic techniques in deter...

In studies of genetic algorithms, evolutionary computing, and ant colony mechanisms, it is recognized that the higher-order forms of collective intelligence play an important role in metaheuristic computing and computational intelligence. Collective intelligence is an integration of collective behaviors of individuals in social groups or collective functions of components in computational intel...

This paper presents an investigation on application of metaheuristic approaches to handle the optimization of planting areas with regards to Lining Layout Planning (LLP). Metaheuristic is approximate solution that sacrifice the guarantee of finding an optimal solution. However, it is an appropriate approach to be employed in two basic situations: 1. a problem may not has an exact method because...

characterizations of ABMs, however, may be viewed chiefly as “after-the-fact” attempts to group together ideas that are intuitively conveyed by the agent terminology. While a thoroughly precise and universally agreed-upon definition of agent-based models may not exist, the relevance of ABMs in science and industry is manifested in its diverse applications. These include explorations into the tr...

We consider the multi-vehicle one-to-one pickup and delivery problem with split loads, a NP-hard problem linked with a variety of applications for bulk product transportation, bike-sharing systems and inventory re-balancing. This problem is notoriously difficult due to the interaction of two challenging vehicle routing attributes, “pickups and deliveries” and “split deliveries”. This possibly l...

A typical modern optimization technique is usually either heuristic or metaheuristic. This technique has managed to solve some optimization problems in the research area of science, engineering, and industry. However, implementation strategy of metaheuristic for accuracy improvement on convolution neural networks (CNN), a famous deep learning method, is still rarely investigated. Deep learning ...