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  • Best Fit Scheduling Algorithm

    - by Teegijee
    I'm writing a scheduling program with a difficult programming problem. There are several events, each with multiple meeting times. I need to find an arrangement of meeting times such that each schedule contains any given event exactly once, using one of each event's multiple meeting times. Obviously I could use brute force, but that's rarely the best solution. I'm guessing this is a relatively basic computer science problem, which I'll learn about once I am able to start taking computer science classes. In the meantime, I'd prefer any links where I could read up on this, or even just a name I could Google.

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  • Best Fit Scheduling Algorithim

    - by Teegijee
    I'm writing a scheduling program with a difficult programming problem. There are several events, each with multiple meeting times. I need to find an arrangement of meeting times such that each schedule contains any given event exactly once, using one of each event's multiple meeting times. Obviously I could use brute force, but that's rarely the best solution. I'm guessing this is a relatively basic computer science problem, which I'll learn about once I am able to start taking computer science classes. In the meantime, I'd prefer any links where I could read up on this, or even just a name I could Google.

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  • How to choose an integer linear programming solver ?

    - by Cassie
    Hi all, I am newbie for integer linear programming. I plan to use a integer linear programming solver to solve my combinatorial optimization problem. I am more familiar with C++/object oriented programming on an IDE. Now I am using NetBeans with Cygwin to write my applications most of time. May I ask if there is an easy use ILP solver for me? Or it depends on the problem I want to solve ? I am trying to do some resources mapping optimization. Please let me know if any further information is required. Thank you very much, Cassie.

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  • Classical task-scheduling assignment

    - by Bruno
    I am working on a flight scheduling app (disclaimer: it's for a college project, so no code answers, please). Please read this question w/ a quantum of attention before answering as it has a lot of peculiarities :( First, some terminology issues: You have planes and flights, and you have to pair them up. For simplicity's sake, we'll assume that a plane is free as soon as the flight using it prior lands. Flights are seen as tasks: They have a duration They have dependencies They have an expected date/time for beginning Planes can be seen as resources to be used by tasks (or flights, in our terminology). Flights have a specific type of plane needed. e.g. flight 200 needs a plane of type B. Planes obviously are of one and only one specific type, e.g., Plane Airforce One is of type C. A "project" is the set of all the flights by an airline in a given time period. The functionality required is: Finding the shortest possible duration for a said project The earliest and latest possible start for a task (flight) The critical tasks, with basis on provided data, complete with identifiers of preceding tasks. Automatically pair up flights and planes, so as to get all flights paired up with a plane. (Note: the duration of flights is fixed) Get a Gantt diagram with the projects scheduling, in which all flights begin as early as possible, showing all previously referred data graphically (dependencies, time info, etc.) So the questions is: How in the world do I achieve this? Particularly: We are required to use a graph. What do the graph's edges and nodes respectively symbolise? Are we required to discard tasks to achieve the critical tasks set? If you could also recommend some algorithms for us to look up, that'd be great.

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  • Alternative to MS Project 2007 for production scheduling?

    - by john c
    OK... Im coming to grips with the fact that MS Project 2007 may not be the correct tool for my production scheduling. We serve 120 to 150 projects a year with durations from 6 weeks to 12 months. The task are simple (6 to 8 per project) and the resource pool is stable (15 to 20 people). It's really an assembly line product but with extremely varied durations. I need to be able to prioritize the projects for production and run projects concurrently to fully utilize my resources. What are the feelings of the stackoverflow community. Am I using the wrong program? I was really hoping to make this simple for non-programer types to input project data into a form and have the schedule software automated enough to make most of the decisions. Is there a better solution available commercially? I'd like to hold on writing a custom spreadsheet as a last resort but if that's the best route then so be it. Thank you so much for your input.

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  • Significance of Bresenhams Line of Sight algorithm

    - by GamDroid
    What is the significance of Bresenhams Line of Sight algorithm in chasing and evading in games? As far as i know and implemented this algorithm calulates the straight line between two given points. However while implementing it in game development i stored the points calculated using this algorithm in an array.Then im traversing this array for chasing and evading purpose. This looks to be working good with some angles only.In an pixel based environment/tile based. What if there are some obstacles added in the paths of the two points? then this algorithm will not work right? How well can we use the Bresenhams Line algorithm in game development?

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  • Scheduling of tasks to a single resource using Prolog

    - by Reed Debaets
    I searched through here as best I could and though I found some relevant questions, I don't think they covered the question at hand: Assume a single resource and a known list of requests to schedule a task. Each request includes a start_after, start_by, expected_duration, and action. The goal is to schedule the tasks for execution as soon as possible while keeping each task scheduled between start_after and start_by. I coded up a simple prolog example that I "thought" should work but I've been unfortunately getting errors during run time: "=/2: Arguments are not sufficiently instantiated". Any help or advice would be greatly appreciated startAfter(1,0). startAfter(2,0). startAfter(3,0). startBy(1,100). startBy(2,500). startBy(3,300). duration(1,199). duration(2,199). duration(3,199). action(1,'noop1'). action(2,'noop2'). action(3,'noop3'). can_run(R,T) :- startAfter(R,TA),startBy(R,TB),T>=TA,T=<TB. conflicts(T,R1,T1) :- duration(R1,D1),T=<D1+T1,T>T1. schedule(R1,T1,R2,T2,R3,T3) :- can_run(R1,T1),\+conflicts(T1,R2,T2),\+conflicts(T1,R3,T3), can_run(R2,T2),\+conflicts(T2,R1,T1),\+conflicts(T2,R3,T3), can_run(R3,T3),\+conflicts(T3,R1,T1),\+conflicts(T3,R2,T2). % when traced I *should* see T1=0, T2=400, T3=200 Edit: conflicts goal wasn't quite right: needed extra TT1 clause. Edit: Apparently my schedule goal works if I supply valid Request,Time pairs ... but I'm stucking trying to force prolog to find valid values for T1..3 when given R1..3?

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  • How do tight timelines and scheduling pressure affect TCO and delivery time?

    - by JonathanHayward
    A friend's father, who is a software engineering manager, said, emphatically, "The number one cause of scheduling overruns is scheduling pressure." Where does the research stand? Is a moderate amount of scheduling pressure invigorating, or is the manager I mentioned right or wrong, or is it a matter of "the more scheduling pressure you have, the longer the delivery time and the more TCO?" Is it one of those things where ideally software engineering would work without scheduling pressure but practically we have to work with constraints of real-world situations? Any links to software engineering literature would be appreciated.

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  • Multilevel Queue Scheduling (MQS) with Round Robin

    - by stackuser
    I'm trying to use MQS to create a Gantt chart of 5 processes (P1-P5) as well as their waiting, response, and turnaround times (and averages of those metrics) within a CPU task schedule. Here's the basic table of arrival times and bursts: Here's my actual work version after ticking off the finished processes. The time quantum for each time slice is (2 queues) TQ1=4 and TQ2=3. Note that I'm doing MQS and NOT MLFQ: It just doesn't feel like I'm doing MQS right here, I know this gets a little complex but maybe someone can point out where I'm going totally wrong.

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  • The best algorithm enhancing alpha-beta?

    - by Risa
    I'm studying AI. My teacher gave us source code of a chess-like game and asked us to enhance it. My exercise is to improve the alpha/beta algorithm implementing in that game. The programmer already uses transposition tables, MTD(f) with alpha/beta+memory (MTD(f) is the best algorithm I know by far). So is there any better algorithm to enhance alpha-beta search or a good way to implement MTD(f) in coding a game?

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  • Lawler's Algorithm Implementation Assistance

    - by Richard Knop
    Here is my implemenation of Lawler's algorithm in PHP (I know... but I'm used to it): <?php $jobs = array(1, 2, 3, 4, 5, 6); $jobsSubset = array(2, 5, 6); $n = count($jobs); $processingTimes = array(2, 3, 4, 3, 2, 1); $dueDates = array(3, 15, 9, 7, 11, 20); $optimalSchedule = array(); foreach ($jobs as $j) { $optimalSchedule[] = 0; } $dicreasedCardinality = array(); for ($i = $n; $i >= 1; $i--) { $x = 0; $max = 0; // loop through all jobs for ($j = 0; $j < $i; $j++) { // ignore if $j already is in the $dicreasedCardinality array if (false === in_array($j, $dicreasedCardinality)) { // if the job has no succesor in $jobsSubset if (false === isset($jobs[$j+1]) || false === in_array($jobs[$j+1], $jobsSubset)) { // here I find an array index of a job with the maximum due date // amongst jobs with no sucessor in $jobsSubset if ($x < $dueDates[$j]) { $x = $dueDates[$j]; $max = $j; } } } } // move the job at the end of $optimalSchedule $optimalSchedule[$i-1] = $jobs[$max]; // decrease the cardinality of $jobs $dicreasedCardinality[] = $max; } print_r($optimalSchedule); Now the above returns an optimal schedule like this: Array ( [0] => 1 [1] => 1 [2] => 1 [3] => 3 [4] => 2 [5] => 6 ) Which doesn't seem right to me. The problem might be with my implementation of the algorithm because I am not sure I understand it correctly. I used this source to implement it: http://www.google.com/books?id=aSiBs6PDm9AC&pg=PA166&dq=lawler%27s+algorithm+code&lr=&hl=sk&cd=4#v=onepage&q=&f=false The description there is a little confusing. For example, I didn't quite get how is the subset D defined (I guess it is arbitrary). Could anyone help me out with this? I have been trying to find some sources with simpler explanation of the algorithm but all sources I found were even more complicated (with math proofs and such) so I am stuck with the link above. Yes, this is a homework, if it wasn't obvious. I still have few weeks to crack this but I have spent few days already trying to get how exactly this algorithm works with no success so I don't think I will get any brighter during that time.

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  • Graph colouring algorithm: typical scheduling problem

    - by newba
    Hi, I'm training code problems like UvA and I have this one in which I have to, given a set of n exams and k students enrolled in the exams, find whether it is possible to schedule all exams in two time slots. Input Several test cases. Each one starts with a line containing 1 < n < 200 of different examinations to be scheduled. The 2nd line has the number of cases k in which there exist at least 1 student enrolled in 2 examinations. Then, k lines will follow, each containing 2 numbers that specify the pair of examinations for each case above. (An input with n = 0 will means end of the input and is not to be processed). Output: You have to decide whether the examination plan is possible or not for 2 time slots. Example: Input: 3 3 0 1 1 2 2 0 9 8 0 1 0 2 0 3 0 4 0 5 0 6 0 7 0 8 0 Ouput: NOT POSSIBLE. POSSIBLE. I think the general approach is graph colouring, but I'm really a newb and I may confess that I had some trouble understanding the problem. Anyway, I'm trying to do it and then submit it. Could someone please help me doing some code for this problem? I will have to handle and understand this algo now in order to use it later, over and over. I prefer C or C++, but if you want, Java is fine to me ;) Thanks in advance

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  • Matchmaking algorithm with a set of filters

    - by Yuriy Pogrebnyak
    I'm looking for matchmaking algorithm for 1x1 online game. Players must be matched not by their skill or level, as usual, but by some specific filters. Each player sends request, where he specifies some set of parameters (generally, 2-4 parameters). If some parameter is specified, player can be matched only with those who has sent this parameter with exactly the same value, or those who hasn't specified this parameter. I need this algorithm to be thread-safe and preferably fast. It would be great if it'll work for 3-4 or even more parameters, but also I'm looking for algorithm that works with only one parameter (in my case it's game bet). Also I'd appreciate ideas on how to implement or improve this algorithm on my server platform - ASP.NET. One more problem I'm facing is that finding match can't be executed right after user sends request, because if other user sends request before matching for previous is finished, they won't be matched even is they possibly could. So it seems that match finding should be started on schedule, and I need help on how to optimize it and how to choose time interval for starting new match finding. P.S. I've also posted this question on stackoverflow

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  • Control diamond square algorithm to generate islands/pangea.

    - by Gabriel A. Zorrilla
    I generated a height map with the diamond square algorithm. The thing is i do not manage to create islands, this is, restrict the height other than water level range to a certain value in the center of the map. I manualy seeded a circle in the middle of the map but the rest of the map still receives heights over the water level. I dont fully understand the Perlin noise algorithm so i'd like to work with my current implementation of the diamond square algorithm which took me 3 days to interpret and code in PHP. :P

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  • word disambiguation algorithm (Lesk algorithm)

    - by anyssnordin
    Hii.. Can anybody help me to find an algorithm in Java code to find synonyms of a search word based on the context and I want to implement the algorithm with WordNet database. For example, "I am running a Java program". From the context, I want to find the synonyms for the word "running", but the synonyms must be suitable according to a context.

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  • Hopcroft–Karp algorithm in Python

    - by Simon
    I am trying to implement the Hopcroft Karp algorithm in Python using networkx as graph representation. Currently I am as far as this: #Algorithms for bipartite graphs import networkx as nx import collections class HopcroftKarp(object): INFINITY = -1 def __init__(self, G): self.G = G def match(self): self.N1, self.N2 = self.partition() self.pair = {} self.dist = {} self.q = collections.deque() #init for v in self.G: self.pair[v] = None self.dist[v] = HopcroftKarp.INFINITY matching = 0 while self.bfs(): for v in self.N1: if self.pair[v] and self.dfs(v): matching = matching + 1 return matching def dfs(self, v): if v != None: for u in self.G.neighbors_iter(v): if self.dist[ self.pair[u] ] == self.dist[v] + 1 and self.dfs(self.pair[u]): self.pair[u] = v self.pair[v] = u return True self.dist[v] = HopcroftKarp.INFINITY return False return True def bfs(self): for v in self.N1: if self.pair[v] == None: self.dist[v] = 0 self.q.append(v) else: self.dist[v] = HopcroftKarp.INFINITY self.dist[None] = HopcroftKarp.INFINITY while len(self.q) > 0: v = self.q.pop() if v != None: for u in self.G.neighbors_iter(v): if self.dist[ self.pair[u] ] == HopcroftKarp.INFINITY: self.dist[ self.pair[u] ] = self.dist[v] + 1 self.q.append(self.pair[u]) return self.dist[None] != HopcroftKarp.INFINITY def partition(self): return nx.bipartite_sets(self.G) The algorithm is taken from http://en.wikipedia.org/wiki/Hopcroft%E2%80%93Karp_algorithm However it does not work. I use the following test code G = nx.Graph([ (1,"a"), (1,"c"), (2,"a"), (2,"b"), (3,"a"), (3,"c"), (4,"d"), (4,"e"),(4,"f"),(4,"g"), (5,"b"), (5,"c"), (6,"c"), (6,"d") ]) matching = HopcroftKarp(G).match() print matching Unfortunately this does not work, I end up in an endless loop :(. Can someone spot the error, I am out of ideas and I must admit that I have not yet fully understand the algorithm, so it is mostly an implementation of the pseudo code on wikipedia

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  • Space partitioning algorithm

    - by Karol Kolenda
    I have a set of points which are contained within the rectangle. I'd like to split the rectangles into subrectangles based on point density (giving a number of subrectangles or desired density, whichever is easiest). The partitioning doesn't have to be exact (almost any approximation better than regular grid would do), but the algorithm have to cope with the large number of points - approx. 200 millions. The desired number of subrectangles however is substantially lower (around 1000). Does anyone knows any algorithm which may help me with this particular task?

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  • Polygonal Triangulation - algorithm with O(n log n) complexity

    - by Arthur Wulf White
    I wish to triangulate a polygon I only have the outline of (p0, p1, p2 ... pn) like described in this question: polygon triangulation algorithm and this webpage: http://cgm.cs.mcgill.ca/~godfried/teaching/cg-projects/97/Ian/algorithm2.html I do not wish to learn the subject and have a deep understanding of it at the moment. I only want to see an effective algorithm that can be used out of the box. The one described in the site seems to be of somewhat high complexity O(n) for finding one ear. I heard this could be done in O(n log n) time. Is there any well known easy to use algorithm that I can translate port to use in my engine that runs with somewhat reasonable complexity? The reason I need to triangulate is that I wish to feel out a 2d-outline and render it 3d. Much like we fill out a 2d-outline in paint. I could use sprites. This would not serve cause I am planning to play with the resulting model on the z-axis, giving it different heights in the different areas. I would love to try the books that were mentioned, although I suspect that is not the answer most readers are hoping for when they read this Q & A format. Mostly I like to see a code snippet I can cut and paste with some modifications and start running.

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  • Heuristic algorithm for load balancing among threads.

    - by Il-Bhima
    I'm working on a multithreaded program where I have a number of worker threads performing tasks of unequal length. I want to load-balance the tasks to ensure that they do roughly the same amount of work. For task T_i I have a number c_i which provides a good approximation to the amount of work that is required for that task. I'm looking for an efficient (O(N) N = num tasks or better) algorithm which will give me "roughly" a good load balance given the values of c_i. It doesn't have to be optimal, but I would like to be able to have some theoretical bounds on how bad the resulting allocations are. Any ideas?

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  • Non-perfect maze generation algorithm

    - by Shylux
    I want to generate a maze with the following properties: The maze is non-perfect. Means it has loops and multiple ways to reach the exit. The maze should be random. The algorithm should output different mazes for different input parameters The maze doesn't have to be braided. Means dead-ends are allowed and appreciated. I just can't find the right resources on google. The closest i found was this description of the different types of algorithms: http://www.astrolog.org/labyrnth/algrithm.htm. All other algorithms were for perfect mazes. Can anyone give me a website where i can look this up or maybe an algorithm directly?

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  • Quick 2D sight area calculation algorithm?

    - by Rogach
    I have a matrix of tiles, on some of that tiles there are objects. I want to calculate which tiles are visible to player, and which are not, and I need to do it quite efficiently (so it would compute fast enough even when I have a big matrices (100x100) and lots of objects). I tried to do it with Besenham's algorithm, but it was slow. Also, it gave me some errors: ----XXX- ----X**- ----XXX- -@------ -@------ -@------ ----XXX- ----X**- ----XXX- (raw version) (Besenham) (correct, since tunnel walls are still visible at distance) (@ is the player, X is obstacle, * is invisible, - is visible) I'm sure this can be done - after all, we have NetHack, Zangband, and they all dealt with this problem somehow :) What algorithm can you recommend for this? EDIT: Definition of visible (in my opinion): tile is visible when at least a part (e.g. corner) of the tile can be connected to center of player tile with a straight line which does not intersect any of obstacles.

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  • Dijkstra's Bankers Algorithm

    - by idea_
    Could somebody please provide a step-through approach to solving the following problem using the Banker's Algorithm? How do I determine whether a "safe-state" exists? What is meant when a process can "run to completion"? In this example, I have four processes and 10 instances of the same resource. Resources Allocated | Resources Needed Process A 1 6 Process B 1 5 Process C 2 4 Process D 4 7

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  • Suggested GA operators for a TSP problem?

    - by Mark
    I'm building a genetic algorithm to tackle the traveling salesman problem. Unfortunately, I hit peaks that can sustain for over a thousand generations before mutating out of them and getting better results. What crossover and mutation operators generally do well in this case?

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  • Infinite loop during A* algorithm

    - by Tashu
    The A* algorithm is used by enemies to have a path to the goal. It's working but when sometimes I placed a tower in a grid (randomly) it produces a stack overflow error. The A* algorithm would iterate the enemy and find its path and pass the list to the enemy's path. I added debug logs and the list that I'm getting it looks like it would arrive from start cell to goal cell. Here's the log - 06-19 19:26:41.982: DEBUG/findEnemyPath, enemy X:Y(4281): X2.8256836:Y3.5 06-19 19:26:41.990: DEBUG/findEnemyPath, grid X:Y(4281): X3:Y2 06-19 19:26:41.990: DEBUG/START CELL ID:(4281): 38 06-19 19:26:41.990: DEBUG/GOAL CELL ID:(4281): 47 06-19 19:26:41.990: DEBUG/Best : 38(4281): passThrough:0.0 06-19 19:26:41.990: DEBUG/Neighbor's Parent:(4281): 38 06-19 19:26:41.990: DEBUG/Neighbor's Parent:(4281): 38 06-19 19:26:41.990: DEBUG/Neighbor's Parent:(4281): 38 06-19 19:26:41.990: DEBUG/Neighbor's Parent:(4281): 38 06-19 19:26:41.990: DEBUG/Best : 39(4281): passThrough:8.875 06-19 19:26:41.990: DEBUG/Neighbor's Parent:(4281): 39 06-19 19:26:41.990: DEBUG/Neighbor's Parent:(4281): 39 06-19 19:26:41.990: DEBUG/Neighbor's Parent:(4281): 39 06-19 19:26:41.990: DEBUG/Best : 40(4281): passThrough:7.9375 06-19 19:26:41.990: DEBUG/Neighbor's Parent:(4281): 40 06-19 19:26:41.990: DEBUG/Neighbor's Parent:(4281): 40 06-19 19:26:41.990: DEBUG/Best : 52(4281): passThrough:8.9375 06-19 19:26:41.990: DEBUG/Neighbor's Parent:(4281): 52 06-19 19:26:41.990: DEBUG/Neighbor's Parent:(4281): 52 06-19 19:26:41.990: DEBUG/Best : 53(4281): passThrough:7.96875 06-19 19:26:41.990: DEBUG/Neighbor's Parent:(4281): 53 06-19 19:26:41.990: DEBUG/Best : 28(4281): passThrough:8.9375 06-19 19:26:41.990: DEBUG/Neighbor's Parent:(4281): 28 06-19 19:26:41.990: DEBUG/Best : 65(4281): passThrough:8.984375 06-19 19:26:41.990: DEBUG/Neighbor's Parent:(4281): 65 06-19 19:26:41.990: DEBUG/Neighbor's Parent:(4281): 65 06-19 19:26:41.990: DEBUG/Best : 66(4281): passThrough:7.9921875 06-19 19:26:41.990: DEBUG/Neighbor's Parent:(4281): 66 06-19 19:26:42.000: DEBUG/Best : 78(4281): passThrough:8.99609375 06-19 19:26:42.000: DEBUG/Neighbor's Parent:(4281): 78 06-19 19:26:42.000: DEBUG/Best : 79(4281): passThrough:7.998046875 06-19 19:26:42.000: DEBUG/Neighbor's Parent:(4281): 79 06-19 19:26:42.000: DEBUG/Best : 80(4281): passThrough:6.9990234375 06-19 19:26:42.000: DEBUG/Neighbor's Parent:(4281): 80 06-19 19:26:42.000: DEBUG/Neighbor's Parent:(4281): 80 06-19 19:26:42.000: DEBUG/Best : 81(4281): passThrough:5.99951171875 06-19 19:26:42.000: DEBUG/Neighbor's Parent:(4281): 81 06-19 19:26:42.000: DEBUG/Neighbor's Parent:(4281): 81 06-19 19:26:42.000: DEBUG/Best : 82(4281): passThrough:4.999755859375 06-19 19:26:42.000: DEBUG/Neighbor's Parent:(4281): 82 06-19 19:26:42.000: DEBUG/Neighbor's Parent:(4281): 82 06-19 19:26:42.000: DEBUG/Best : 83(4281): passThrough:3.9998779296875 06-19 19:26:42.000: DEBUG/Neighbor's Parent:(4281): 83 06-19 19:26:42.000: DEBUG/Best : 71(4281): passThrough:2.99993896484375 06-19 19:26:42.000: DEBUG/Neighbor's Parent:(4281): 71 06-19 19:26:42.000: DEBUG/Best : 59(4281): passThrough:1.99951171875 06-19 19:26:42.000: DEBUG/Neighbor's Parent:(4281): 59 06-19 19:26:42.000: DEBUG/Neighbor's Parent:(4281): 59 06-19 19:26:42.000: DEBUG/Neighbor's Parent:(4281): 59 06-19 19:26:42.000: DEBUG/Best : 47(4281): passThrough:0.99951171875 Then, the goal cell would be iterating its parent till start cell to break off the loop. private void populateBestList(Cell cell, List<Cell> bestList) { bestList.add(cell); if (cell.parent.start == false) { Log.d("ID:", ""+cell.id); Log.d("ParentID:", ""+cell.parent.id); populateBestList(cell.parent, bestList); } return; } The log with error above would show like this - 06-19 19:26:42.010: DEBUG/ID:(4281): 47 06-19 19:26:42.010: DEBUG/ParentID:(4281): 59 06-19 19:26:42.010: DEBUG/ID:(4281): 59 06-19 19:26:42.010: DEBUG/ParentID:(4281): 71 06-19 19:26:42.010: DEBUG/ID:(4281): 71 06-19 19:26:42.010: DEBUG/ParentID:(4281): 59 06-19 19:26:42.010: DEBUG/ID:(4281): 59 06-19 19:26:42.010: DEBUG/ParentID:(4281): 71 06-19 19:26:42.010: DEBUG/ID:(4281): 71 71 and 59 would switch over and goes on. I thought the grid is the issue due to the fact that enemies are using the single grid so I make the parent, start, and goal clear before starting the A* algorithm for an enemy. for(int i = 0; i < GRID_HEIGHT; i++) { for(int j = 0; j < GRID_WIDTH; j++) { grid[i][j].parent = null; grid[i][j].start = false; grid[i][j].goal = false; } } That didn't work. I thought it might be something related to this code, but not sure if I'm on right track - neighbor.parent = best; openList.remove(neighbor); closedList.remove(neighbor); openList.add(0, neighbor); Here's the code of the A* algorithm - private List<Cell> findEnemyPath(Enemy enemy) { for(int i = 0; i < GRID_HEIGHT; i++) { for(int j = 0; j < GRID_WIDTH; j++) { grid[i][j].parent = null; grid[i][j].start = false; grid[i][j].goal = false; } } List<Cell> openList = new ArrayList<Cell>(); List<Cell> closedList = new ArrayList<Cell>(); List<Cell> bestList = new ArrayList<Cell>(); int width = (int)Math.floor(enemy.position.x); int height = (int)Math.floor(enemy.position.y); width = (width < 0) ? 0 : width; height = (height < 0) ? 0 : height; Log.d("findEnemyPath, enemy X:Y", "X"+enemy.position.x+":"+"Y"+enemy.position.y); Log.d("findEnemyPath, grid X:Y", "X"+height+":"+"Y"+width); Cell start = grid[height][width]; Cell goal = grid[ENEMY_GOAL_HEIGHT][ENEMY_GOAL_WIDTH]; if(start.id != goal.id) { Log.d("START CELL ID: ", ""+start.id); Log.d("GOAL CELL ID: ", ""+goal.id); //Log.d("findEnemyPath, grid X:Y", "X"+start.position.x+":"+"Y"+start.position.y); start.start = true; goal.goal = true; openList.add(start); while(openList.size() > 0) { Cell best = findBestPassThrough(openList, goal); //Log.d("ID:", ""+best.id); openList.remove(best); closedList.add(best); if (best.goal) { System.out.println("Found Goal"); System.out.println(bestList.size()); populateBestList(goal, bestList); /* for(Cell cell : bestList) { Log.d("ID:", ""+cell.id); Log.d("ParentID:", ""+cell.parent.id); } */ Collections.reverse(bestList); Cell exit = new Cell(13.5f, 3.5f, 1, 1); exit.isExit = true; bestList.add(exit); //Log.d("PathList", "Enemy ID : " + enemy.id); return bestList; } else { List<Cell> neighbors = getNeighbors(best); for (Cell neighbor : neighbors) { if(neighbor.isTower) { continue; } if (openList.contains(neighbor)) { Cell tmpCell = new Cell(neighbor.position.x, neighbor.position.y, 1, 1); tmpCell.parent = best; if (tmpCell.getPassThrough(goal) >= neighbor.getPassThrough(goal)) { continue; } } if (closedList.contains(neighbor)) { Cell tmpCell = new Cell(neighbor.position.x, neighbor.position.y, 1, 1); tmpCell.parent = best; if (tmpCell.getPassThrough(goal) >= neighbor.getPassThrough(goal)) { continue; } } Log.d("Neighbor's Parent: ", ""+best.id); neighbor.parent = best; openList.remove(neighbor); closedList.remove(neighbor); openList.add(0, neighbor); } } } } Log.d("Cannot find a path", ""); return null; }

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