Hybrid artificial bee colony and flower pollination algorithm for grid-based optimal pathfinding

Pathfinding is essential and necessary for agent movement used in computer games and many other applications. Generally, the pathfinding algorithm searches the feasible shortest path from start to end locations. This task is computationally expensive and consumes large memory, particularly in a large map size. Obstacle avoidance in the game environment increases the complexity to find a new path in the search space. A huge number of algorithms, including heuristic and metaheuristics approaches, have been proposed to overcome the pathfinding problem. Artificial Bee Colony (ABC) is a metaheuristic algorithm that is robust, has fast convergence, high flexibility, and fewer control parameters. However, the best solution founded by the onlooker bee in the presence of constraints is still insufficient and not always satisfactory. A number of variant ABC algorithms have been proposed to achieve the optimal solution. However, it is difficult to simultaneously achieve the optimal solution. Alternatively, Flower Pollination Algorithm (FPA) is one of promising algorithms in optimising problems. The algorithm is easier to implement and faster to reach an optimum solution. Thus, this research proposed Artificial Bee Colony – Flower Pollination Algorithm to solve the pathfinding problem in games, in terms of path cost, computing time, and memory. The result showed that ABC-FPA improved the path cost result by 81.68% and reduced time by 97.84% as compared to the ABC algorithm, which led to a better pathfinding result. This performance indicated that ABC-FPA pathfinding gave better quality pathfinding results

Repetitive mutations in genetic algorithm for software test data generations

Generating test data is the most important part of dynamic software testing. One of the white box testing techniques is path coverage testing. Genetic Algorithm (GA) has proven to be an important method in generating test data for automatic path coverage testing. However, to satisfy path coverage testing, GA’s operation of a single mutation generates test data that covers the same path in a single generation, hence resulting in path coverage duplication, which negatively increases the number of iterations. Therefore, this study proposes a repetitive mutation for GA in order to eliminate path coverage duplication and reduce the number of iterations for test data generations in path coverage testing. The study was conducted in three phases. First, the limitations of existing mutation techniques used in GA to generate test data for path coverage testing were analysed. Then, a repetitive mutation technique for GA was designed and implemented in a numerical simulation using C++ language. Finally, the evaluation phase that compares the outcome of the proposed technique against existing studies in terms of the number of iterations for test data generations. The findings show that the proposed repetitive mutation technique outperformed the single mutation technique by reducing the number of iterations to more than 50 percent for test data generations. The study has revealed the importance of mutation in generating test data and how it can be harnessed to quickly guide GA in producing solutions. In addition, the proposed repetitive mutation in GA can contribute to developing an adaptive GA testing tool

Enhancement of bees algorithm for global optimisation

This research focuses on the improvement of the Bees Algorithm, a swarm-based nature-inspired optimisation algorithm that mimics the foraging behaviour of honeybees. The algorithm consists of exploitation and exploration, the two key elements of optimisation techniques that help to find the global optimum in optimisation problems. This thesis presents three new approaches to the Bees Algorithm in a pursuit to improve its convergence speed and accuracy. The first proposed algorithm focuses on intensifying the local search area by incorporating Hooke and Jeeves’ method in its exploitation mechanism. This direct search method contains a pattern move that works well in the new variant named “Bees Algorithm with Hooke and Jeeves” (BA-HJ). The second proposed algorithm replaces the randomly generated recruited bees deployment method with chaotic sequences using a well-known logistic map. This new variant called “Bees Algorithm with Chaos” (ChaosBA) was intended to use the characteristic of chaotic sequences to escape from local optima and at the same time maintain the diversity of the population. The third improvement uses the information of the current best solutions to create new candidate solutions probabilistically using the Estimation Distribution Algorithm (EDA) approach. This new version is called Bees Algorithm with Estimation Distribution (BAED). Simulation results show that these proposed algorithms perform better than the standard BA, SPSO2011 and qABC in terms of convergence for the majority of the tested benchmark functions. The BA-HJ outperformed the standard BA in thirteen out of fifteen benchmark functions and is more effective in eleven out of fifteen benchmark functions when compared to SPSO2011 and qABC. In the case of the ChaosBA, the algorithm outperformed the standard BA in twelve out of fifteen benchmark functions and significantly better in eleven out of fifteen test functions compared to qABC and SPSO2011. BAED discovered the optimal solution with the least number of evaluations in fourteen out of fifteen cases compared to the standard BA, and eleven out of fifteen functions compared to SPSO2011 and qABC. Furthermore, the results on a set of constrained mechanical design problems also show that the performance of the proposed algorithms is comparable to those of the standard BA and other swarm-based algorithms from the literature

最適化問題に対するブレインストーム最適化アルゴリズムの改善

富山大学・富理工博甲第170号・于洋・2020/3/24富山大学202

Concept demonstrator: Holding site location, ambulance allocation, and relocation decision support tool

Thesis (MEng)--Stellenbosch University, 2017.ENGLISH ABSTRACT: Before the start of a shift, the dispatchers at the Western Cape Emergency Control Centre (WC ECC) decide where to place holding sites and how many ambulance to allocate to each holding site. During a shift they decide when and where to relocate ambulances. At present, dispatchers make these decisions based solely on their experience and intuition. In this project a concept demonstrator decision support tool (DST) is developed which produces solutions for the near-optimal placement of holding sites per shift, ambulance allocation, and relocation per hour of that shift based on predicted ambulance demand rates. The DST is developed with the aim of assisting the dispatchers at the WC ECC with holding site placement, ambulance allocation, and relocation decisions. The real-world instance utilised during the development of the concept demonstrator DST consists of six months' historical call data from the City of Cape Town and the Cape Winelands municipalities. Singular spectrum analysis is used to forecast ambulance demand according to incident priority. The extended queuing maximum availability location problem model is adapted to t the real-world instance. The model aims to simultaneously maximise expected ambulance coverage and minimise ambulance relocations by manipulating holding site placement, ambulance allocation, and relocation. The solution method implemented for the model as a whole is the arti cial bee colony algorithm. The DST was solved for four planning week instances, at 95% service reliability. Predicted demand for the planning week is predicted using historical demand that precedes the planning week and a recommended schedule of holding site placement, ambulance allocation, and relocation is generated for the predicted ambulance demand. The performance of this schedule is evaluated using the observed historical demand for the planning week. Di erent approaches for the classi cation of calls { consider all calls to be life-threatening, or calls to be life-threatening or non-life-threatening { as well as for the implementation of the model constraints are considered. The results indicate that the WC ECC can improve ambulance coverage with the current, or even smaller, ambulance eet size if decisions are made with the assistance of the DST that anticipates the probable future ambulance demand. The concept demonstrator DST's solutions' expected percentage coverage compared to the actual percentage coverage exceeds 150%. However, it is invalid to compare these values like-for-like as a signi cant number of real-world factors, including the speci c road conditions at the time of each call, the responsiveness of both the ECC operator handling the call and the ambulance team involved, and the communication connection between the ECC call operator and the ambulance team, in uence the real-world response rate and could not be modelled in the DST. However, even when these factors are taken into account, the discrepancy between the actual and the predicted performance is sufficient to convincingly demonstrate the potential of the concept demonstrator DST to assist theWC ECC in further improving their response time.AFRIKAANSE OPSOMMING: Voor die aanvang van 'n skof besluit die ambulaansversenders by die Wes- Kaapse noodbeheersentrum (WC ECC) waar om wagstasies te plaas en hoeveel ambulanse om by elkeen te plaas. Tydens 'n skof besluit hulle wanneer en waarheen ambulanse geskuif moet word. Tans, maak die versenders staat slegs op hul eie ervaring en intu sie om hul besluitneming te lei. In die projek is 'n konsep demonstreerder besluitsteunstelsel (DST) gebou wat oplossings vir die naas-optimale plasing van wagstasies per skof, ambulaansplasing en -rondskuiwing per uur van daardie skof bepaal gebaseer op voorspelde ambulaansaanvraag. Die konsep demonstreerder DST is ontwikkel met die doel om die versenders by die WC ECC te help met die besluitneming aangaande wagstasieplasing, ambulaansplasing en -rondskuiwing. Die werklikheidsgeval, waarvoor die DST ontwikkel word, bestaan uit ses maande se historiese oproepdata van die Stad Kaapstad en die Kaapse Wynland munisipaliteite. `Singular spectrum analysis' is gebruik om die ambulaansaanvraag volgens voorvalprioriteit te voorspel. Die uitgebreide `queuing maximum availability location problem' model is aangepas om by die werklikheidsgeval te pas. Die model streef om die maksimum verwagte ambulaansdekking en die minimum rondskuiwingskoste deur middel van verbeterde wagstasieplasing, ambulaansplasing en -rondskuiwing te vind. Die oplossingsmetode wat gebruik is vir die algehele model is die `arti cial bee colony' algoritme. Die DST is vir vier gevalle opgelos met 'n 95% diensbetroubaarheidsvlak. Die ambulaansaanvraag vir die beplanningsweek is voorspel gebaseer op historiese ambulaansaanvraag, wat nie die beplanningsweek se historiese ambulaansaanvraag bevat nie. Daarna is'n aanbevole wagstasieplasing, ambulaansplasing en -rondskuiwing skedule gegenereer vir die voorspelde ambulaansaanvraag. Die skedule is geïmplimenteer vir die beplanningsweek. se historiese ambulaans aanvraag. Die resultate is gebruik om die skedule se prestasie the evalueer. Verskillende benaderings vir die hantering van die oproepe volgens voorvalprioriteit { ag alle oproepe as lewensbedreigend, of ag hulle as lewensbedreigend of nie-lewensbedreigend { en twee implementerings van die ambulaansplasingsbeperking word oorweeg. Die resultate dui aan dat die WC ECC die ambulaansdekking kan verbeter met die huidige, of selfs kleiner, ambulaansvloot as besluite geneem word met behulp van die konsep demonstreerder DST in afwagting van die waarskynlike ambulaansaanvraag. Die DST se oplossings se verwagte persentasie ambulaansdekking oorskry die werklike persentasie ambulaansdekking wat bepaal is vir die historiese oproepdata met 150%. Dit moet inaggeneem word dat hierdie waardes nie dieselfde is nie. Beduidende gevalle van die werklikheidsgeval se faktore, insluitend die spesi eke toestand van die paaie tydens elke oproep, die uksheid van die noodbeheersentrum se telefoonoperateur en die ambulaansbemanning, en die kommunikasie tussen die telefoonoperateur en die ambulaansbemanning, be nvloed die werklike reaksietyd en kon nie gemodelleer word nie. Tog, selfs wanneer die faktore inaggeneem word, is die verskil tussen die waargenome en voorspelde prestasies voldoende om oortuigend die potensiaal van die konsep demonstreerder DST te demonstreer as hulpmiddel vir die WC ECC om hul reaksietye verder te verbeter