Search
Search Results
-
Shortest path network interdiction with incomplete information: a robust optimization approach
In this paper, we consider a shortest path network interdiction problem with incomplete information and multiple levels of interdiction intensity....
-
A robust, resilience machine learning with risk approach: a case study of gas consumption
This research suggests a novel Robust, Resilient machine learning that focuses on the Risk approach (3R) in a hard situation for the first time. A...
-
A new proactive and reactive approach for resource-constrained project scheduling problem under activity and resource disruption: a scenario-based robust optimization approach
This paper introduces a novel two-phase framework for designing a proactive–reactive scheduling model in the multi-mode resource-constrained project...
-
Scenario-Based Distributionally Robust Unit Commitment Optimization Involving Cooperative Interaction with Robots
With the increasing penetration of renewable energy, uncertainty has become the main challenge of power systems operation. Fortunately, system...
-
Applying robust optimization to the shelter location–allocation problem: a case study for Istanbul
In this study, we consider the shelter location and allocation problem under demand uncertainty. In particular, we seek to improve the disaster...
-
An Integer Optimization Approach for Determining Building Height
Building height is of crucial importance in architectural design. In this paper, we provide an integer optimization model to determine the number of...
-
A simulation-based optimization approach for designing transit networks
Public transport network design deals with finding efficient network solution(s) from a set of alternatives that best satisfies the often-conflicting...
-
Robust, extended goal programming with uncertainty sets: an application to a multi-objective portfolio selection problem leveraging DEA
This study presents a two-phase approach of Data Envelopment Analysis (DEA) and Goal Programming (GP) for portfolio selection, representing a...
-
Robust Facility Location
This chapter discusses different possibilities for modeling and solving robust discrete facility location problems. Initially, a finite uncertainty...
-
Distributionally Robust Facility Location
This chapter discusses distributional robust optimization (DRO) models and techniques for facility location problems. The classical capacitated...
-
Two-stage stochastic/robust scheduling based on permutable operation groups
In this paper we study the performance of a two-stage approach to scheduling under uncertainty making use of sequences of groups of permutable...
-
Distributionally Robust Optimization
The robust optimization methodology that we have introduced so far is built on a fundamental modeling approach, that is based on set-theoretic,...
-
A robust-heuristic optimization approach to a green supply chain design with consideration of assorted vehicle types and carbon policies under uncertainty
Adoption of carbon regulation mechanisms facilitates an evolution toward green and sustainable supply chains followed by an increased complexity....
-
Optimization with uncertainties: a scheduling example
The optimization of manufacturing systems is rarely a deterministic task in practice, as uncertainties of various origins often have significant...
-
Develo** Robust Facility Reopening Processes Following Natural Disasters
In the wake of a natural disaster, quickly reopening services and amenities is critical for community well-being and resiliency. However, in many...
-
Multi-Echelon Inventory Optimization for Practitioners: a Predictive Global Sensitivity Analysis Approach
Intense competition in e-commerce has forced firms to provide highly precise delivery time guarantees such as ‘same-day’ and ‘2-day’ ship**. To...
-
Partition-based distributionally robust optimization via optimal transport with order cone constraints
In this paper we wish to tackle stochastic programs affected by ambiguity about the probability law that governs their uncertain parameters. Using...
-
Multi-echelon inventory optimization using deep reinforcement learning
This paper studies the applicability of a deep reinforcement learning approach to three different multi-echelon inventory systems, with the objective...
-
Transition towards sustainable mobility: the role of transport optimization
Although the concept of a transition towards sustainability has been introduced about 30 years ago, there is still a lack of progress. Transport...
-
An Improved Quantum Inspired Particle Swarm Optimization for Forest Cover Prediction
Forest cover prediction plays a crucial role in assessing and managing natural resources, biodiversity, and environmental sustainability. Traditional...
