A Simulation Framework for Evaluation of Multi-objective Master Production Scheduling Policy and Rolling Schedules in Make-to-order Supply Chains

, M.Sc. Thesis Sharif University of Technology Nedaei Hoor, Hessam (Author) ; Mahlooji, Hashem (Supervisor)

Abstract

This research studies multi-objective master production schedule (MPS) and advanced order commitment (AOC) in two-stage supply chains. Simulation-based experimental analysis evaluates the impact of environmental and MPS design factors on schedule cost and instability. The results provide insight into multi-objective MPS design considerations through rolling schedule policies. The study reveals that the manufacturer's production smoothness utility coefficient and its interaction with other experimental factors considerably impact the system's performance. In addition, it introduces a simulation framework with embedded mixed integer programming models that could be used as a framework for...

A Copula Based Joint Model of Residential and Work Location Choice

, M.Sc. Thesis Sharif University of Technology Movaghar Hoor, Sara (Author) ; Samimi, Amir (Supervisor)

Abstract

Residential location choice is one of the most important decisions that households should make. This decision has many effects on household's travel patterns and urban built environment. Considering predetermined residential locations is one of the weaknesses of these models. Joint modelling of residential and work location choices is a solution to this problem. So far, multinomial logit, nested logit and mixed logit are the structures that have been used for this joint modeling. Independence from irrevelant alternatives, forcing sequential structure and complicated calculations in large dimension problems are respectively weaknesses of mentioned structures. In this researsh a copula based...

Joint multi-objective master production scheduling and rolling horizon policy analysis in make-to-order supply chains

, Article International Journal of Production Research ; Vol. 52, issue. 9 , Feb , 2014 , pp. 2767-2787 ; ISSN: 00207543 Nedaei, H ; Mahlooji, H ; Sharif University of Technology

2014

Abstract

This research studies multi-objective master production schedule (MPS) and advanced order commitment (AOC) in two-stage supply chains. Simulation-based experimental analysis evaluates the impact of environmental and MPS design factors on schedule cost and instability. The results provide insight into multi-objective MPS design considerations through rolling schedule policies. The study reveals that the manufacturers production smoothness utility coefficient and its interaction with other experimental factors considerably impact on the systems performance. In addition, it introduces a simulation framework with embedded mixed integer programming models that could be used as a framework for...

Investigating Conformal Vector Field on Riemannian Manifolds

, M.Sc. Thesis Sharif University of Technology Hessam, Hamed (Author) ; Fanai, Hamid Reza (Supervisor)

Abstract

At first the killing vector fields will be investigated. Conditions are introduced for the hypersurface of a Riemannian manifold with a killing vector field to be equipped with the same killing vector field. Then 2-killing vector field is studied and its relation with killing vector fields and monotone vector fields is presented. After that conformal vector fields are discussed and conditions are introduced in order that the Riemannian manifold equipped with a conformal vector field, isisometric to n-dimensional sphere with constant curvature. Finally we will present the conditions which conformal vector field is a 2-killing vector field. Then we will present the results in which the...

Efficient Data Aggregation in Mobile Wireless Sensor Networks

, M.Sc. Thesis Sharif University of Technology Mohammadmoradi, Hessam Aldin (Author) ; Habibi, Jafar (Supervisor)

Abstract

Due to the advances in wireless communications and electronics over the last few years, the development of networks of low-cost, low-power, and multifunctional sensors has received increasing attention. Most important constraints of this network are energy and bandwidth. Data aggregation is one of the effective approaches for reducing energy consumption in wireless sensor networks. Recent research on data collection reveals that, rather than reporting data through long, multi-hop and error-prone routes to a static sink using tree or cluster network structure, allowing and leveraging sink mobility is more promising for energy efﬁcient data gathering. In this work we proposed an effective...

Inbound e-marketing using neural network based visual and phonetic user experience analytics

, Article 2018 4th International Conference on Web Research, ICWR 2018 ; 15 June , 2018 , Pages 12-18 ; 9781538653647 (ISBN) Nedaei, D ; Khanzadi, P ; Majidi, B ; Movaghar, A ; Sharif University of Technology

Institute of Electrical and Electronics Engineers Inc 2018

Abstract

Inbound marketing is the process of attracting the probable customers to a business before they have any intention to become customers. An effective method for inbound marketing is creation of a positive psychological business environment to attract the customers. A significant portion of traditional business environment is moving online and the new business environment is the company website. One of the major elements in online inbound marketing is the website address and the website logo, which are the first factors of brand personality that the visitor to the company website encounters when looking up the website in a search engine. In this paper, a framework for inbound e-marketing using...

Optimisation of combined cooling, heating and power (CCHP) systems incorporating the solar and geothermal energy: a review study

, Article International Journal of Ambient Energy ; Volume 43, Issue 1 , 2022 , Pages 42-60 ; 01430750 (ISSN) Asadi, R ; Assareh, E ; Moltames, R ; Olazar, M ; Nedaei, M ; Parvaz, F ; Sharif University of Technology

Taylor and Francis Ltd 2022

Abstract

Recently, numerous studies have focused on simulation and optimisation of combined cooling, heat, and power (CCHP) systems. This research, from a different perspective, aims to conduct a comprehensive review of the studies performed in the field of solar, geothermal or combined sources, and subsequently analysing the multi-objective evolutionary algorithms to identify the most efficient situation, which satisfy researchers' needs in order to attain a better performance in their ongoing or future research projects. It is worth noting that multi-objective optimisation in these cycles is based on optimising a thermodynamic term (exergy efficiency, thermal efficiency, etc.) and an economic term...

Integration of the intelligent optimisation algorithms with the artificial neural networks to predict the performance of a counter flow wet cooling tower with rotational packing

, Article International Journal of Ambient Energy ; 2021 ; 01430750 (ISSN) Assari, N ; Assareh, E ; Alirahmi, M ; Hosseini, H ; Nedaei, M ; Rahimof, Y ; Fathi, A ; Behrang, M ; Jafarinejad, T ; Sharif University of Technology

Taylor and Francis Ltd 2021

Abstract

The present study investigated a counter-flow cooling tower performance by integrating the Artificial Neural Networks and Intelligent Optimisation Algorithms (ANN-IOAs). For this purpose, two scenarios were evaluated. In the first scenario, inlet air wet-bulb temperature (T aw), inlet air dry bulb temperature (T ad), water to the air mass flow rate ratio (mw /ma), and rotor speed (υ) were the input parameters for the ANNs, while the output temperature (T wo) was the ANNs output. In the second scenario, the same input parameters applied for the first scenario were used as input variables and the tower efficiency (ε) was considered as an output parameter. The well-known IOAs methods, namely,...

Integration of the intelligent optimisation algorithms with the artificial neural networks to predict the performance of a counter flow wet cooling tower with rotational packing

, Article International Journal of Ambient Energy ; Volume 43, Issue 1 , 2022 , Pages 5780-5787 ; 01430750 (ISSN) Assari, N ; Assareh, E ; Alirahmi, S. M ; Hosseini, S. H ; Nedaei, M ; Rahimof, Y ; Fathi, A ; Behrang, M ; Jafarinejad, T ; Sharif University of Technology

Taylor and Francis Ltd 2022

Abstract

The present study investigated a counter-flow cooling tower performance by integrating the Artificial Neural Networks and Intelligent Optimisation Algorithms (ANN-IOAs). For this purpose, two scenarios were evaluated. In the first scenario, inlet air wet-bulb temperature (T aw), inlet air dry bulb temperature (T ad), water to the air mass flow rate ratio (mw /ma), and rotor speed (υ) were the input parameters for the ANNs, while the output temperature (T wo) was the ANNs output. In the second scenario, the same input parameters applied for the first scenario were used as input variables and the tower efficiency (ε) was considered as an output parameter. The well-known IOAs methods, namely,...