This paper is an extensive survey of the Bee Colony Optimization (BCO) algorithm, proposed for first time in 2001. BCO and its numerous variants belong to a class nature-inspired meta-heuristic methods, based on foraging habits honeybees. Our main goal promote it among wide operations research community. simple, but efficient technique that has been successfully applied many optimization problems, mostly transport, location scheduling fields. Firstly, we shall give brief overview other...

Abstract In order for traffic authorities to attempt prevent drink driving, check truck weight limits, driver hours and service regulations, hazardous leaks from trucks, vehicle equipment safety, we need find answers the following questions: (a) What should be total number of inspection stations in network? (b) Where these facilities located? This paper develops a model determine locations uncapacitated network. We analyze two different formulations: single-objective optimization problem...

Introduction/purpose: Models developed for routing transport vehicles with an environmental focus are predominantly dedicated to reverse logistics or transporting environmentally hazardous cargo. Few models in the relevant literature consider ecological factors involved distribution of consumer goods. Methods: This paper presents a model planning vehicle routes optimize fuel consumption, considering time windows required service and payload capacity vehicles. A heuristic algorithm was...

Bee colony optimization (BCO) is a relatively new metaheuristic designed to deal with hard combinatorial problems. It belongs the group of nature-inspired methods that explore collective intelligence applied by honey bees during nectar collecting process. In this paper, BCO anticovering location problem (ACLP), one fundamental problems in area discrete location. Because algorithm has not been used literature related ACLP so far, it was challenge test its performances on nondeterministic...

Bee Colony Optimization (BCO) is a meta-heuristic method based on foraging habits of honeybees. This technique was motivated by the analogy found between natural behavior bees searching for food and optimization algorithms an optimum in combinatorial problems. BCO has been successfully applied to various hard problems, mostly transportation, location scheduling fields. There are some applications continuous field that have appeared recently. The main purpose this paper introduce scientific...

The problem of static scheduling independent tasks on homogeneous multiprocessor systems is studied in this paper. solved by the Bee Colony Optimization (BCO). BCO algorithm belongs to class stochastic swarm optimization methods. proposed inspired foraging habits bees nature. was able obtain optimal value objective function all small medium size test problems. CPU times required find best solutions are acceptable.

The bee colony optimization (BCO) algorithm is a nature-inspired meta-heuristic method for dealing with hard, real-life combinatorial and continuous optimisation problems. It based on the foraging habits of honeybees was proposed by Lučić Teodorović in 2001. BCO simple, but effective that has already been successfully applied to various problems transport, location analysis, scheduling some other fields. This paper provides theoretical verification proving convergence properties. As result,...

Proper number and optimal location of detectors in transport networks enable early traffic incident detection collecting other relevant flow data. Increasing located provides accuracy obtained data, while requiring more investments maintenance cost support. The need to be placed such that they can successfully sample the conditions with least possible error. On hand, authorities tend minimize on network achieve investment savings. proposed model locations a finite set highway corridor,...

The Bee Colony Optimization (BCO) algorithm is a meta-heuristic that belongs to the class of biologically inspired stochastic swarm optimization methods, based on foraging habits bees in nature. BCO operates population solutions, and therefore, it represents good basis for parallelization. main contribution this work development new efficient parallelization strategies BCO. We propose two synchronous asynchronous distributed memory multiprocessor architecture under Message Passing Interface...

Flow-capturing facilities make available service to passing-by client flows.The paper develops a model determine the locations of flow-capturing in transportation network.The objective function be maximized represents total flow intercepted.The basic input data are estimated numbers trips between pairs nodes.It is often impossible estimate these with enough precision.The treated this as an uncertain or fuzzy numbers.The concept proposed based on mathematical programming.The developed...

Technological developments are having a significant impact on purchasing habits and consumer behavior, threaten the traditional model of delivery goods by post. The replacement letter-post items with electronic forms communication has led to declines in volume postal items. Therefore, collection become very inefficient. This paper proposes that network segment needs be reorganized reducing current number installed postboxes. To this end, mathematical been defined. Considering postboxes one...

Transport networks in many cities are generally very seriously congested. Consequently, travel time, number of stops, unexpected delays, transport costs, level air pollution, noise, and traffic accidents increased. In addition to daily congestion, there may be congestion jams as a consequence reconstruction the roads’ lanes. During past decade, different strategies for demand management have been developed, with aim decrease existing congestion. One available is ride matching (sharing)...

Daily congestion on transportation networks is the one of biggest problems that city authorities face. Different strategies for transportation-demand management have been developed with aim to decrease existing negative traffic impacts. Available are based use accessible infrastructure and their own characteristics. In accordance these specific characteristics, each strategy more or less suitable a particular network. this paper, writers develop model best selection from drivers’...

Hub facilities serve as switching and transshipment points in transportation communication networks well logistic systems.Hub have an influence on flows the hub-to-hub links ensure benefit from economies of scale inter-hub transportation.The key factors for designing a successful hub-and-spoke network are to determine optimal number hubs, properly locate allocate non-hubs hubs.This paper presents model locations p-hub hubs.The problem is solved by Bee Colony Optimization (BCO) algorithm,...

Abstract Managing ticket reservations in passenger rail transport is a complex task. A hybrid algorithm developed as decision support tool. The aim of the proposed to provide real‐time decisions on seat inventory allocation taking into account relevant information from past. This paper considers revenue management application with variable capacity sleeping cars. Uncertainty availability embedded through payoff table, while an Artificial Neural Network used tool for making decisions. tested...