Results 11 to 20 of about 200 (108)
A New Simheuristics Procedure for Stochastic Combinatorial Optimization
SNE Simulation Notes EuropeIgnoring uncertainty in combinatorial optimization leads to suboptimal decisions in practice. Nevertheless, the focus is often on deterministic combinatorial optimization problems, mainly because they are already challenging enough without stochasticity.
Joost Berkhout
exaly +4 more sources
Solving Vehicle Routing Problems under Uncertainty and in Dynamic Scenarios: From Simheuristics to Agile Optimization [PDF]
Applied Sciences, 2022 Many real-life applications of the vehicle routing problem (VRP) occur in scenarios subject to uncertainty or dynamic conditions. Thus, for instance, traveling times or customers’ demands might be better modeled as random variables than as deterministic ...
Majsa Ammouriova +4 more
doaj +2 more sources
Current Trends in Simheuristics: from smart transportation to agent-based simheuristics [PDF]
, 2018 Simheuristics extend metaheuristics by adding a simulation layer that allows the optimization component to deal efficiently with scenarios under uncertainty. This presentation reviews both initial as well as recent applications of simheuristics, mainly in the area of logistics and transportation.
Estrada-Moreno, Alejandro +4 more
core +4 more sources
International Transactions in Operational ResearchAbstract The team orienteering problem (TOP) is an NP‐hard optimization problem with an increasing number of potential applications in smart cities, humanitarian logistics, wildfire surveillance, etc. In the TOP, a fixed fleet of vehicles is employed to obtain rewards by visiting nodes in a network.
Javier Panadero +2 more
exaly +2 more sources
Simheuristics for Strategic Workforce Planning at a Busy Airport [PDF]
2024 Winter Simulation Conference (WSC)Airport demand frequently exceeds capacity. An airport’s capacity bottleneck is often located in its runway system. Other times, it is elsewhere, including the terminal facilities. At one of the busiest UK airports, the subject of this study, the bottleneck is located in the passenger security hall, where staff are employed directly by the airport ...
Johanna Wiesflecker +2 more
core +4 more sources
A Simheuristic Algorithm for Service Placement in Community Networks [PDF]
2020 Winter Simulation Conference (WSC), 2020 The growing demand for network connectivity has boosted the number of community networks (CNs). CNs are decentralized and self-organized communication networks owned and managed at the edge by volunteers. Due to the heterogeneity of edge node characteristics, high software and hardware diversity, irregular topology and unreliable behavior of the ...
Javier Panadero +5 more
openaire +2 more sources
A Discrete-Event Simheuristic for Solving a Realistic Storage Location Assignment Problem
Mathematics, 2023 In the context of increasing complexity in manufacturing and logistic systems, the combination of optimization and simulation can be considered a versatile tool for supporting managerial decision-making.
Jonas F. Leon +4 more
doaj +1 more source
The Stochastic Team Orienteering Problem with Position-Dependent Rewards
Mathematics, 2022 In this paper, we analyze both the deterministic and stochastic versions of a team orienteering problem (TOP) in which rewards from customers are dynamic. The typical goal of the TOP is to select a set of customers to visit in order to maximize the total
Javier Panadero +3 more
doaj +1 more source
A Memetic Algorithm With Reinforcement Learning for Sociotechnical Production Scheduling
IEEE Access, 2023 The following interdisciplinary article presents a memetic algorithm with deep reinforcement learning (DRL) for solving practically oriented dual resource constrained flexible job shop scheduling problems (DRC-FJSSP).
Felix Grumbach +3 more
doaj +1 more source
A Fuzzy Simheuristic for the Permutation Flow Shop Problem under Stochastic and Fuzzy Uncertainty
Mathematics, 2022 Stochastic, as well as fuzzy uncertainty, can be found in most real-world systems. Considering both types of uncertainties simultaneously makes optimization problems incredibly challenging.
Juliana Castaneda +4 more
doaj +1 more source