How to make a greedy heuristic for the asymmetric traveling salesman problem competitive

It is widely confirmed by many computational experiments that a greedy type heuristics for the Traveling Salesman Problem (TSP) produces rather poor solutions except for the Euclidean TSP. The selection of arcs to be included by a greedy heuristic is usually done on the base of cost values. We propose to use upper tolerances of an optimal solution to one of the relaxed Asymmetric TSP (ATSP) to guide the selection of an arc to be included in the final greedy solution. Even though it needs time to calculate tolerances, our computational experiments for the wide range of ATSP instances show that tolerance based greedy heuristics is much more accurate an faster than previously reported greedy type algorithms

A Heuristic Algorithm for Optimal Hamiltonian Cycles in Weighted Graphs

Abstract. The paper focuses on finding of the optimal Hamiltonian cycle, when it is regarded with respect to cost, time, distance or difficulty level of the route. The problem is strictly related to the traveling salesman problem proved to be NP-complete for general graphs. The paper gives a heuristic algorithm for finding the optimal spanning cycle in a weighted graph. Its idea is based on optimization of weight losses and reduction the complexity of a problem by reduction the dimension of the graph payoff matrix.&nbsp

Automating the Optimal Selection Process of Subassembly Sections of a Modular Spreader Beam Used in Lifting Operations

Spreader beams used in lifting operations undergo a purely compressive load to spread apart the ends of a sling which enables large payloads to be lifted from a single point, such as a crane hook, without damage. A modular spreader beam can be made using subcomponents of different standard sizes to create a spreader beam of any length, making them more versatile and cost-effective than non-modular spreader beams. However, while the manual calculation and selection of an optimum number of subsections for a single beam is straightforward, the process for the multiple range of spreader beam is very challenging and is labour-intensive in a lifting company. The main aim of this study was to develop an automated system for determining the optimal configuration of the modular spreader beam which leads to increasing the efficiency of the lifting company through saving the associated labour and time costs. The automated system is underpinned by designing an algorithm based on a dynamic programming optimisation search to test every possible configuration and return the optimal configuration. Hence, the main novelty in this study is the development of a computer-based system to automate the selection process of the modular beam’s subsections, which generates an optimal package immediately to create different lengths with the fewest sections needed for a lifting operation. Eventually, the process of generating quotation for clients can be significantly accelerated while the risk of human errors can be also eliminated

Purposeful selection of variables in logistic regression

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Greedy algorithms

Rad se bavi općenito algoritmima s posebnim naglaskom na pohlepne algoritme. Ukratko se predstavlja povijest nastanka algoritma. Naime, sam pojam algoritma nastao je u čast arapskom matematičaru al Khowarizmiju koji je vjerovao kako se svaki matematički problem može rastaviti na manje dijelove i na taj način ubrzati njegovo rješavanje. Upravo ta ideja dovodi do onoga što se danas naziva algoritmom. Također, navodi se kada i gdje se pronalaze prvi zapisi algoritama. Da bi se precizno izrazili koraci od kojih se sastoji algoritam mogu se koristiti prirodan jezik, pseudo jezik te pravi programski jezik. Rad donosi i klasifikaciju algoritama prema načinu implementacije na rekurzivne ili iterativne algoritme, serijske ili paralelne, determinističke ili stohastičke te na točne ili približne algoritme. Algoritme je, također, moguće podijeliti prema metodologiji dizajna. Prema metodologiji dizajna algoritmi se dijele na algoritme na silu, podijeli i vladaj algoritme, dinamičke, pohlepne te na algoritme za sortiranje i prebrojavanje. Tehnikom pohlepnog pristupa, rješenje zadanog algoritma se konstruira u nizu koraka. U svakom se koraku bira mogućnost koja je lokalno optimalna u nekom smislu. Zamisao je da će nas takvi optimalni koraci dovesti do globalnog optimalnog rješenja. No, za mnoge probleme pohlepni algoritam ne uspije proizvesti optimalno rješenje

Greedy algorithms

Rad se bavi općenito algoritmima s posebnim naglaskom na pohlepne algoritme. Ukratko se predstavlja povijest nastanka algoritma. Naime, sam pojam algoritma nastao je u čast arapskom matematičaru al Khowarizmiju koji je vjerovao kako se svaki matematički problem može rastaviti na manje dijelove i na taj način ubrzati njegovo rješavanje. Upravo ta ideja dovodi do onoga što se danas naziva algoritmom. Također, navodi se kada i gdje se pronalaze prvi zapisi algoritama. Da bi se precizno izrazili koraci od kojih se sastoji algoritam mogu se koristiti prirodan jezik, pseudo jezik te pravi programski jezik. Rad donosi i klasifikaciju algoritama prema načinu implementacije na rekurzivne ili iterativne algoritme, serijske ili paralelne, determinističke ili stohastičke te na točne ili približne algoritme. Algoritme je, također, moguće podijeliti prema metodologiji dizajna. Prema metodologiji dizajna algoritmi se dijele na algoritme na silu, podijeli i vladaj algoritme, dinamičke, pohlepne te na algoritme za sortiranje i prebrojavanje. Tehnikom pohlepnog pristupa, rješenje zadanog algoritma se konstruira u nizu koraka. U svakom se koraku bira mogućnost koja je lokalno optimalna u nekom smislu. Zamisao je da će nas takvi optimalni koraci dovesti do globalnog optimalnog rješenja. No, za mnoge probleme pohlepni algoritam ne uspije proizvesti optimalno rješenje

The farther, the safer: a manifesto for securely navigating synthetic species away from the old living world

Biotechnology has empirically established that it is easier to construct and evaluate variant genes and proteins than to account for the emergence and function of wild-type macromolecules. Systematizing this constructive approach, synthetic biology now promises to infer and assemble entirely novel genomes, cells and ecosystems. It is argued here that the theoretical and computational tools needed for this endeavor are missing altogether. However, such tools may not be required for diversifying organisms at the basic level of their chemical constitution by adding, substituting or removing elements and molecular components through directed evolution under selection. Most importantly, chemical diversification of life forms could be designed to block metabolic cross-feed and genetic cross-talk between synthetic and wild species and hence protect natural habitats and human health through novel types of containment