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Problem strnjenega polnjenja košev
ID GRZIN, DOMEN (Author), ID Mihelič, Jurij (Mentor) More about this mentor... This link opens in a new window

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Abstract
Predstavimo problem strnjenega polnjenja košev, podamo formalno definicijo problema in navedemo primer za boljšo predstavo bralcu ter kasnejšo razlago algoritmov. Predstavimo tudi preslikavo problema razvršča\-nja štud\-entov v predavalnice na ta problem in druge uporabe. Predstavimo tri natančne in dva približna algoritma, s katerimi rešujemo optimizacijske probleme, kot je problem strnjenega polnjenja košev. Razvijemo implementacije predstavljenih algoritmov za problem. Implementacije algoritmov ekperimentalno ovrednotimo in med seboj primerjamo po času, ki ga porabijo, da pridejo do rešitve. Približne algoritme primerjamo tudi po tem, kako blizu je njihova rešitev optimalni.

Language:Slovenian
Keywords:optimizacijski problem, požrešni algoritem, izčrpno preiskovanje, razveji in omeji, iskanje v širino, eksperimentalno ovrednotenje
Work type:Bachelor thesis/paper
Typology:2.11 - Undergraduate Thesis
Organization:FRI - Faculty of Computer and Information Science
Year:2022
PID:20.500.12556/RUL-135411 This link opens in a new window
COBISS.SI-ID:100742915 This link opens in a new window
Publication date in RUL:11.03.2022
Views:1195
Downloads:66
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Secondary language

Language:English
Title:Contiguous bin packing problem
Abstract:
We present the problem of contiguous bin packing, give a formal definition of the problem and an example, for a better presentation to the reader and an easier explanation of the algorithms in later chapters. We also present a mapping of classifying students into lecture halls onto our problem and other uses. We present three exact algorithms and two heuristic algorithms for solving optimization problems such as the problem of contiguous bin packing. We develop an implementation for each of the presented algorithms. After developing the implementations we experimentally evaluate them and compare with each other in terms of the time it takes for them to return a solution. For approximate algorithms we also compare their given solutions, specifically how close these are to the correct ones given by the exact algorithms.

Keywords:optimization problem, greedy algorithm, exhaustive enumeration, branch and bound, breadth-first search, experimental evaluation

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