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  1. 1

    Comparison Between Linear Programming And Integer Linear Programming: A Review by Sam, Mei Lee, Saptari, Adi, Salleh, Mohd Rizal, Mohamad, Effendi

    Published 2018
    “…This research discusses comparison of linear programming (LP) and integer linear programming (ILP). …”
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  2. 2

    Solving Sudoku puzzles in Binary Integer Linear Programming using Branch and Bound algorithm / Ahida Waliyyah Ahmad Fuad by Ahmad Fuad, Ahida Waliyyah

    Published 2024
    “…The puzzle starts with a partially filled grid provided by the setter, and it usually has a unique solution. This study explores the application of a Binary Integer Linear Programming (BILP) model combined with the Branch and Bound (B&B) algorithm to solve Sudoku puzzles. …”
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    Formulating and solving stochastic truck and trailer routing problems using meta-heuristic algorithms / Seyedmehdi Mirmohammadsadeghi by Seyedmehdi, Mirmohammadsadeghi

    Published 2015
    “…The initial feasible solutions have been generated for this purpose. The solutions have been significantly improved by the algorithms. …”
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    Enhancement of Ant System Algorithm for Course Timetabling Problem by Djamarus, Djasli

    Published 2009
    “…For this kind of problem, researchers believe that it will be better to find an approximate solution that can be delivered by a stochastic algorithm than waiting for an exact solution from the deterministic algorithm. …”
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    Optimize class time tabling by using genetic algorithm technique in UTHM by Ahmad, Izah Rafidah

    Published 2019
    “…This research used genetic algorithm (GA) that was applied to java programming languages with a goal of reducing conflict and optimizing the fitness. …”
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    Variable Neighbourhood Search Algorithm for Vehicle Routing Problem with Backhaul by Siaw Ying Doreen, Sek

    Published 2023
    “…The VNS algorithm is used to improve the obtained solutions in the improvement phase. …”
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  9. 9

    Solving vehicle routing problem by using improved K-nearest neighbor algorithm for best solution by Mohammed, Mazin Abed, Abd Ghani, Mohd Khanapi, Hamed, Raed Ibraheem, A. Mostafa, Salama, Ahmed Ibrahim, Dheyaa, Jameel, Humam Khaled, Alallah, Ahmed Hamed

    Published 2017
    “…The structure of the algorithm is designed so that the program does not require a large database to store the population, which speeds up the implementation of the program execution to obtain the solution; secondly, the algorithm has proven its success in solving the problem and finds a shortest route. …”
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  10. 10

    Development of dynamic programming algorithm for maintenance scheduling problem by Zafira Adlia, Mohd Fauzi

    Published 2020
    “…This research starts with reviewing the previous researches to find the gap in knowledge and find the possible solutions of the gap found. …”
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    Vehicle Routing Problem with Simultaneous Pickup and Delivery by Sze, San Nah, Sek, Siaw Ying Doreen, Sze, Jeeu Fong, Cheah, Wai Shiang, Chiew, Kang Leng

    Published 2020
    “…It is one of the most popular solutions to solve a complex problem. In this research, the algorithm solution consists of two main phases. …”
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    Programming Approach in Teaching Operations Research Techniques for Computer Science Students by Maarop, Nurazean, Masrom, Maslin

    Published 2005
    “…OR techniques include among others, linear programming, non-linear programming, integer programming, data analysis including statistics, simulation, and goal programming. …”
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    An Environmentally Energy Dispatch Using New Meta Heuristic Evolutionary Programming by Mohamad Ridzuan, Mohamad Radzi

    Published 2018
    “…Basically,one important issue in the power system network is to provide the optimal Economic Load Dispatch (ELD) solution in order to guarantee the sustainable consumer load demand.However,today ELD solution is essential to include together with the environmental aspect and known as Environmental Economic Load Dispatch (EELD).For that reason, many researchers continue in the development of new simulation tool specifically to overcome the EELD problems.Therefore,this study prepared an improved hybrid metaheuristic technique named as New Meta Heuristic Evolutionary Programming (NMEP) to provide the best possible solution in solving the identified single objective and multi objective functions for EELD solution.This new technique a merging cloning strategy that involved in an Artificial Immune System (AIS) algorithm into algorithm of Meta Heuristic Evolutionary Programming (Meta-EP).The development of NMEP technique is to minimize total cost,reduce the total emission during generator operation through the common formula in EELD and lowest total system loss.Besides that,all mentioned objective functions were also optimized together simultaneously that formulated using the weighted sum method before had been executed on the multi objective NMEP or called MONMEP.Both individual and multi objective NMEP techniques performance were verified among other two common heuristic methods known as AIS and Meta-EP techniques.In addition,the best possible solution defined using the aggregate function method.Through this method,the selection of the best MOEELD solution became effortless as compared with MO individually that required compare two or more objective function in one time manually.Among those three optimization techniques the lowest total aggregate values mostly resulted via the NMEP technique.Based upon that,the proposed technique is proving as the outstanding method compared with Meta-EP and AIS techniques in solving the EELD problem for both standard IEEE 26 bus and 57 bus systems.…”
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    Sequential and parallel multiple tabu search algorithm for multiobjective urban transit scheduling problems by Uvaraja, Vikneswary

    Published 2018
    “…Nondominated solutions are produced for every dataset to mark the tradeoff between the conflicting objectives studied in this research. …”
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    Development of a multi-objective optimization model for transport and environment in a closed-loop automotive supply chain by Sadrnia, Abdolhossein

    Published 2014
    “…Since the logistics networks are known as complex models, exact methods could not find the optimum solution. Therefore, various meta-heuristic algorithms have been tried by researchers. …”
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