A5072421143- Advanced Manufacturing and Logistics Optimization
- Supply Chain and Inventory Management
- Scheduling and Optimization Algorithms
- Supply Chain Resilience and Risk Management
- Risk and Safety Analysis
- Infrastructure Resilience and Vulnerability Analysis
- Sustainable Supply Chain Management
- Vehicle Routing Optimization Methods
- Digital Transformation in Industry
- Flexible and Reconfigurable Manufacturing Systems
- Advanced Control Systems Optimization
- Reliability and Maintenance Optimization
- Smart Grid Energy Management
- Product Development and Customization
- Assembly Line Balancing Optimization
- Process Optimization and Integration
- Vehicle emissions and performance
- Microgrid Control and Optimization
- Hybrid Renewable Energy Systems
- Quality and Supply Management
- Blood donation and transfusion practices
- Transportation Planning and Optimization
- Facility Location and Emergency Management
Technische Universität Dresden
2020-2022
University of Tehran
2018
Iran University of Science and Technology
2015-2016
Many supply chains suffer from a lack of flexibility, adaptability, and robustness, which imposes customer dissatisfaction, transportation, backlog, rework costs on companies. The mobile chain (MSC) is newly developed idea that aims to rectify this problem. In kind chain, production, distribution, delivery product family are performed by factory (MF), can be carried truck, while stationary production sites no longer required. process completed directly at the customer's location following...
The miniaturization and modularization of production capacity brings with it not only greater agility efficiency, but also increased flexibility in the form mobility. This allows to be moved when where is most needed, generating new business opportunities, e.g., allowing modular units rented, leased, or shared. flexibility, however, requires information control systems that ensure a correct secure flow between different stakeholders supply chain. Based on this, present article characterizes...
AbstractThis research aims to adopt two robust optimisation approaches for a real-world flow shop manufacturing system with batch processing machines, where the time and size of job are non-deterministic uncertain. Each machine can process multiple jobs simultaneously as long capacity is not exceeded. Two important decisions required: (1) grouping into batches (2) scheduling established on machines. A mathematical model presented, then famous adopted purpose converting deterministic one. An...
For years, there have been tremendous endeavors to reduce makespan in an attempt decrease the production expenses. This investigation aims develop a scenario-based robust optimization approach for real-world flow shop with any number of batch processing machines. The study assumes are some uncertainties associated times as well size jobs. Each machine can process multiple jobs simultaneously long machines’ capacities not violated. In order verify this developed model and evaluate performance...
We study the maintenance task scheduling problem for an aircraft fleet in uncertain environment from viewpoint of robust optimization. Given a daily horizon, tasks delegated to shop should be scheduled such way that sufficient aircrafts are available on time meet demand planned missions. The either activities or unexpected repair jobs when major fault is detected during preor after-flight check each mission. availability skilled labour main constraint. propose formulation so duration subject...
With increasing adoption of supply-dependent energy sources like renewables, Energy Storage Systems (ESS) are needed to remove the gap between demand and supply at different time periods.During daylight there is an excess during night, it drops considerably.This paper focuses on possibility storage in vertically stacked blocks as suggested by recent startups.An algorithm proposed based conceptual constraints, allow for removal electrical form gravitational potential energy.To improve these...
This paper presents a robust methodology to deal with novel resilient hub covering flow problem (HCFP) capacity and budget constraints. The primary HCFP is determine the best network setting, which minimises total cost of establishing hubs shipping demand, subject some In order cope inherent uncertainty associated input data, (RHCFP) proposed. evaluate performance presented models, we use Monte Carlo simulation technique measure efficiency model. select conservatism level, combine several...
This paper presents a robust methodology to deal with novel resilient hub covering flow problem (HCFP) capacity and budget constraints. The primary HCFP is determine the best network setting, which minimises total cost of establishing hubs shipping demand, subject some In order cope inherent uncertainty associated input data, (RHCFP) proposed. evaluate performance presented models, we use Monte Carlo simulation technique measure efficiency model. select conservatism level, combine several...