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A Lagrangian bounding and heuristic principle for bi-objective discrete optimization
Lagrangian relaxation is a common and often successful way to approach computationally challenging single-objective discrete optimization problems...
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Discrete Optimization
When solving optimization problems we typically have to make some discrete decisions because of natural constraints that may restrict decision...
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Discrete Stochastic Optimization for Public Health Interventions with Constraints
Many public health threats exist, motivating the need to find optimal intervention strategies. Given the stochastic nature of the threats (e.g., the...
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Mathematical modelling and a discrete cuckoo search particle swarm optimization algorithm for mixed model sequencing problem with interval task times
This paper addresses a sequencing problem with uncertain task times in mixed model assembly lines. In this problem, task times are not known exactly...
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Enhanced migrating birds optimization algorithm for optimization problems in different domains
Migrating birds optimization algorithm is a promising metaheuristic algorithm recently introduced to the optimization community. In this study, we...
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Consensus Building for Uncertain Large-Scale Group Decision-Making Based on the Clustering Algorithm and Robust Discrete Optimization
Consensus reaching processes (CRPs) including the feedback adjustment mechanism generally require extended periods of time to bridge the opinion gap...
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Simulation-based metaheuristic optimization algorithm for material handling
Modern technologies and the emergent Industry 4.0 paradigm have empowered the emergence of flexible production systems suitable to cope with custom...
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A simulation-based optimization approach for the calibration of a discrete event simulation model of an emergency department
Accurate modeling of the patient flow within an Emergency Department (ED) is required by all studies dealing with the increasing and well-known...
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Cost scrutiny of discrete-time priority queue with cluster arrival and Bernoulli feedback
This work describes the economic feasibility of a single server discrete-time queueing model, (Geo/G/1) where interarrival times have a geometric...
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A sequential choice model for multiple discrete demand
Consumer demand in a marketplace is often characterized to be multiple discrete in that discrete units of multiple products are chosen together. This...
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Capacity and Patient Flow Problems: Solutions Using Queuing Analytics and Discrete Event Simulation
A brief comparative overview is provided for queuing analytics and discrete event simulation. Comparative analysis is provided for 13 capacity and...
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A novel two-phase trigonometric algorithm for solving global optimization problems
Metaheuristics play a major role in the important domain of global optimization. Since they are problem independent, they can be effectively used in...
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Newton’s Method for Global Free Flight Trajectory Optimization
Globally optimal free flight trajectory optimization can be achieved with a combination of discrete and continuous optimization. A key requirement is...
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Distributed continuous-time optimization for convex problems with coupling linear inequality constraints
In this paper we propose a novel distributed continuous-time algorithm aimed to solve optimization problems with cost function being a sum of local...
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Robust combinatorial optimization problems under budgeted interdiction uncertainty
In robust combinatorial optimization, we would like to find a solution that performs well under all realizations of an uncertainty set of possible...
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Hybrid simplicial-randomized approximate stochastic dynamic programming for multireservoir optimization
We revisit an approximate stochastic dynamic programming method that we proposed earlier for the optimization of multireservoir problems. The method...
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Augmented simulation methods for discrete stochastic optimization with recourse
We develop an augmented simulation approach to solve discrete stochastic optimization problems by converting them into a grand simulation problem in...
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A modified grey wolf optimization algorithm to solve global optimization problems
The Grey Wolf Optimizer (GWO) algorithm is a very famous algorithm in the field of swarm intelligence for solving global optimization problems and...
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The value of shape constraints in discrete moment problems: a review and extension
This research reviews the use of shape constraints in discrete moment problems. In particular, we investigate the impact of incorporating...
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Assortment optimization: a systematic literature review
Assortment optimization is a core topic of demand management that finds application in a broad set of different areas including retail, airline,...
