Determining the Relationship between Time of Construction and Cranes Organization by Applying the Bees Algorithm for Reducing the Time of Construction of Houses

You can get a wide range of strong cranes able to lift and move heavy weights with constant acceleration, that result in an optimization in the construction time. However, it is possible that factors such as lack of cranes, incorrect cranes for work, lack of coordination, lack of communication, which result in a material is two transportation or more times occur, that once a job is done when another crane at the same time could be doing the following process. This is known as deferred construction time.

Maritime Logistics

In the literature, mostly, under the heading of maritime logistics, classical sea transportation issues have been studied. In actual fact, with broader scope, maritime logistics is a different field under the logistics theme and sea transportation is just one of the functions that must be carried effectively and in an integrated manner with other logistics functions. This chapter focuses on the maritime logistics functions which were selected by the authors in accordance with the gap in the literature, namely transportation and traffic management, inventory management, demand forecasting, material handling, and packaging and labelling. In addition to the maritime logistics functions; port logistics, green maritime logistics and decision problems in maritime logistics topics are handled deeply with the aim of completing the skeleton of the maritime logistics concept by which an understanding of the clear definition of maritime logistics can be achieved. The practitioners can gain more integrated and holistic viewpoint about maritime logistics with the help of this chapter.

Implementing a Container Ship Stowage Problem for Humanitarian Aid in Palestine Based on Cultural Algorithms

Bioinspired algorithms are a generic term used to refer to the solution of computational problems, based on the planning and implementation based on existing models in the evolutionary process-related nature. Most evolutionary algorithms proposed paradigms that occur in the biology of living things and concepts of natural selection, mutation and reproduction. However, other paradigms that can be taken in the creation of evolutionary algorithms also exist such as the forces of nature, which have been many algorithms based on water, gas and wind reactions. Many of the environments involving unstructured problems in this case a problem of accommodation of containers of humanitarian aid to a company with limited resources, which can be considered from the perspective of cultural paradigms, because the cultural paradigms offer a wide range categorized models that ignore the possible solutions to the problem-a common situation in real life. The purpose of this research is to apply evolutionary computation properties of cultural technology; in this case, to corroborate through data mining analysis of how low the support of various companies use technology for their own benefit to propose a solution to a given problem, in our case carry different types of goods deemed humanitarian aid . The mentioned above, to carry out an adaptation from the standpoint of the modeling societies. An environment for conducting tests for this type of analysis in our case a model arrangement of containers was developed in order to enable learning about not very conventional characteristics of a cultural technology. This environment was named Allaliyah in Palestinian culture means “Together we can achieve everything.”

Modelling the Route Choice

The issue of route choice is a key factor for the freight transport performance. Congestion at roads encourages hauliers to change routes to minimize the delays and keep lead times in a reliable range. In the context of transport planning, the route choice problem can be assessed by modelling the travel times needed to reach a destination through the different routes in a road network. Is in this point where the volume-delay functions become relevant. A Volume-Delay Function (VDF) is a mathematical representation of the increase of the travel time as more and more vehicles utilize the routes, causing congestion on the road networks. The related literature and practitioners report on the use of some known functional forms, as the BPR function, the Conical volume-delay function or the Akcelik's function, which are widely utilized in flow's assignation modelling in transport planning. A successful application of VDFs requires a proper fitting of the function's parameters. In a classical focus these parameters can be deduced from speed-flow surveys carried out at the routes or links of interest; these surveys generally require time money and personnel. As an alternative to this classical focus, particularly when facing scarcity of resources, this work carries out a mathematical analysis of the VDF functional forms, as well with an interpretation of their parameters in relation to road's operation. The results of these analyses clarifies the meaning of the functional forms for the VDFs and their parameters, and suggest other ways to assess those parameters which may be more practical for the purpose of modelling the choice of route in freight transport. Some considerations to put into practice this in Mexico are discussed at the end of this work.

Optimization of Utility Functions in an Admissible Space of Higher Dimension

S. Smale published a paper where announce a theorem which optimize a several utility functions at once (cf. Smale, 1975) using Morse Theory, this is a very abstract subject that require high skills in Differential Topology and Algebraic Topology. Our goal in this paper is announce the same theorems in terms of Calculus of Manifolds and Linear Algebra, those subjects are more reachable to engineers and economists whom are concern with maximizing functions in several variables. Moreover, the elements involved in our theorems are accessible to graduate students, also we putting forward the results we consider economically relevant.

Clio-Combinatorics

This chapter proposes to apply combinatorial optimization to past military conflicts with the aim of producing quantitative data that help explaining history. To do this, we can go beyond the classical “problem solving” vision of operations research that focuses on algorithmic development and computation analysis to privilege solution analysis and the needs of matching the obtained solution to the reality we aim to represent, study and analyze. In particular, we propose an iterative logic search method that aims to identify and analyze military strategic logic in terms of logistics. Then, to illustrate it, an application to the French troop assignment plan (Plan XVII of Joffre, 1932) is made to analyze which could be the subjacent logic behind the defense plan of French troops and state on the consequences of the optimization choices in terms of regional distribution of troops. A discussion of the proposed framework and the directions to generalize it will be presented as a conclusion.

The Premises of Logistics

The objective of this paper is to show how the French Royal Navy, faced with multiple challenges of different kinds, has built in the 17th and 18th centuries a particularly complex military-industrial and organisational tool, which foreshadows the most up-to-date industrial and logistical organisations. By reinterpreting this pre-industrial episode, one could not only set out the major principles that constitute the foundations of the logistical and SCM backgrounds (anticipation, reactivity, standardisation, normalisation, productivity, modularity, flexibility, interoperability, fluidity, continuity), but also some logistical archetypes (strategic control of space and strategic control of time, transport infrastructures and accessibility, global sourcing and suppliers' networks, nomenclatures and production ranges, warehouses and stocks availability).

Use of GVRP as a Model of Two Specific Real World Problems and Its Bioinspired Solution

The aim of this chapter is about the inclusion of real world scenarios, viewed as a Generalized Vehicle Routing Problem (GVRP) model problem, and treated by bio inspired algorithms in order to find optimum routing of product delivery. GVRP is the generalization of the classical Vehicle Routing Problem (VRP) that is well known NP-hard as generalized combinatorial optimization problem with a number of real world applications and a variety of different versions. Due to its complexity, large instances of VRP are hard to solve using exact methods. Thus a solution by a soft computing technique is desired. From a methodological standpoint, the chapter includes four bio inspired algorithms, ant colony optimization and firefly. From an application standpoint, several factors of the generalized vehicle routing are considered from a real world scenario.

A Mobile Application for Helping Urban Public Transport and Its Logistics

Urban growth in developed countries has made highly difficult the logistics of public transport in many cities. This issue is a consequence of the increase in the number of public transport routes, which has caused that citizens do not know important information on such routes. Especially, data about stops, terminals, timetables, paths and which are the easily reachable places for each single route. On the other hand, smartphones have become very popular in the last lustra. This kind of device has high-end services such as cameras, high-tech sensors and Global-Positioning-System (GPS) navigation, to mention only a few. Thus, since mobile phones are useful and practically ubiquitous, they should be applied to collective-transport logistics, giving the edge to citizens in an economic manner. Ergo, to solve the aforementioned problem, we propose here an approach based on using technology connected to mobile phones, the GPS and the Internet.

VisTHAA

In this chapter, a scientific tool designed to facilitate fair comparisons of heuristics is introduced. Making a fair comparison of the performance of different algorithms is a general problem for the heuristic community. Most of the works on experimental analysis of heuristic algorithms have been focused on tabular comparisons of experimental results over standard sets of benchmark instances. However, from a statistical point of view, and according to the experimental design theory, a minimum requirement to compare heuristic algorithms is the use of non-parametric tests. Non-parametric tests can be used for comparing algorithms whose results represent average values, in spite of the inexistence of relationships between them, and explicit conditions of normality, among others. The proposed tool, referred to as VisTHAA, incorporates four non-parametric statistical tests to facilitate the comparative analysis of heuristics. As a case study, VisTHAA is applied to analyze the published results for the best state-of-the-art algorithms that solve the one-dimensional Bin Packing Problem.