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Optimising the design of a supply chain network with economies of scale using mixed integer programming
Published 2011“…Using this linearisation technique, a mixed integer linear programming model is developed that can be efficiently solved using a branch-and-bound-based optimisation package. …”
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Optimization of Energy Consumption in Cloud Computing Datacenters
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Queuing-Based Optimization of EV Charging Stations: A Case Study of Manama City, Bahrain
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A matheuristic approach for solving the 2-connected dominating set problem
Published 2019“…Its performance is enhanced by combining it with a second local search method that uses a Mixed Integer Program. The performance of the proposed method is evaluated on large unit disc graphs having varying edge densities and on general graphs.…”
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A GRASP Approach for Solving Large-Scale Electric Bus Scheduling Problems
Published 2021“…The problem is modelled using a mixed integer program (MIP) in which the charging time of an EB is pertinent to the battery’s state-of-charge level. …”
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A linear programming approach for the weighted graph matchingproblem
Published 1993“…The linear program is solved using a simplex-based algorithm. …”
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A LINEAR-PROGRAMMING APPROACH FOR THE WEIGHTED GRAPH MATCHING PROBLEM
Published 2020“…The linear program is solved using a Simplex-based algorithm. …”
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Quarantine-aware home healthcare routing and scheduling: a bi-objective approach
Published 2025“…To address these pressing needs, our research introduces a Mixed Integer Linear Programming (MILP) model tailored to the COVID-19 era. …”
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A hybrid of clustering and meta-heuristic algorithms to solve a p-mobile hub location–allocation problem with the depreciation cost of hub facilities
Published 2021“…A multi-objective mixed-integer non-linear programming (MINLP) model is developed. …”
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Degree-Based Network Anonymization
Published 2020“…A corresponding graph realization approach is introduced based on a reduction to the Weighted Edge Cover problem, which in turn is solved using Integer Linear Programming to obtain the best possible solution. …”
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Supply chain planning of vaccine and pharmaceutical clusters under uncertainty: The case of COVID-19
Published 2023“…To propose a model for planning the pharmaceutical supply chains, a mixed-integer linear programming (MILP) model is used for a four-echelon supply chain design. …”
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Optimal Routing and Scheduling in E-commerce Logistics using Crowdsourcing Strategies
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Joint Location and Beamforming Design for Cooperative UAVs with Limited Storage Capacity
Published 2019“…Since the formulated problem is a mixed-integer non-linear program which is generally non-deterministic polynomial-time hard, we proposed a framework that is developed on the basis of difference-of-convex (DC) programming to transform the original problem into a series of approximate convex problems which can be iteratively solved until convergence. …”
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UAV-assisted Multi-tier Computing Framework for IoT Networks
Published 2022“…The problem is formulated as a mixed integer programming problem and solved using Successive Convex Approximation. …”
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A genetic algorithm for corrective retesting. (c1995)
Published 1995Get full text
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Natural optimization algorithms for optimal regression testing
Published 1997“…The present two natural optimization algorithms, namely simulated annealing and genetic algorithms, for solving this problem. The algorithms are based on an integer programming problem formulation and the program's control-flow graph. …”
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Convex Hull Representations Of Models For Computing Collisions Between Multiple Bodies
Published 2020“…For this case, we again compare an integer programming approach with its linear programming convex hull representation, and exhibit the effectiveness of solving a sequence of mathematical programs for each time segment over a global programming scheme which considers all segments at once. …”
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Correlation Clustering via s-Club Cluster Edge Deletion
Published 2023“…In this work, we implement three approaches to tackle the 2-club clustering via edge deletion: a heuristic approach based on the influence of the edge to resolve maximum conflicts, a parameterized algorithm in which by deleting a maximum of k edges, the graph can be transformed into a 2-club cluster based on a branching algorithm, and the approach in Integer Linear Programming to find the optimized solution in an integer formulation. …”
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