Showing 8 results for Sadjadi
R. Sadeghian, G.r. Jalali-Naini, J. Sadjadi, N. Hamidi Fard ,
Volume 19, Issue 4 (IJIE 2008)
Abstract
In this paper Semi-Markov models are used to forecast the triple dimensions of next earthquake occurrences. Each earthquake can be investigated in three dimensions including temporal, spatial and magnitude. Semi-Markov models can be used for earthquake forecasting in each arbitrary area and each area can be divided into several zones. In Semi-Markov models each zone can be considered as a state of proposed Semi-Markov model. At first proposed Semi-Markov model is explained to forecast the three mentioned dimensions of next earthquake occurrences. Next, a zoning method is introduced and several algorithms for the validation of the proposed method are also described to obtain the errors of this method.
Mahmood Rezaei Sadrabadi , Seyed Jafar Sadjadi,
Volume 20, Issue 1 (IJIEPR 2009)
Abstract
Multiple Objective Programming (MOP) problems have become famous among many researchers due to more practical and realistic implementations. There have been a lot of methods proposed especially during the past four decades. In this paper, we develop a new algorithm based on a new approach to solve MOP problems by starting from a utopian point (which is usually infeasible) and moving towards the feasible region via stepwise movements and a plain continuous interaction with Decision Maker (DM). We consider the case where all objective functions and constraints are linear. The implementation of the proposed algorithm is demonstrated with two numerical examples.
S. J Sadjadi , Mir.b.gh. Aryanezhad , H.a. Sadeghi ,
Volume 20, Issue 3 (IJIEPR 2009)
Abstract
We present an improved implementation of the Wagner-Whitin algorithm for economic lot-sizing problems based on the planning-horizon theorem and the Economic- Part-Period concept. The proposed method of this paper reduces the burden of the computations significantly in two different cases. We first assume there is no backlogging and inventory holding and set-up costs are fixed. The second model of this paper considers WWA when backlogging, inventory holding and set-up costs cannot be fixed. The preliminary results also indicate that the execution time for the proposed method is approximately linear in the number of periods in the planning-horizon .
S.m. Seyedhosseini, S. J. Sadjadi , Kh. Hassanlou,
Volume 21, Issue 1 (IJIEPR 2010)
Abstract
, ,
Volume 23, Issue 2 (IJIEPR 2012)
Abstract
The problem of staff scheduling at a truck hub for loading and stripping of the trucks is an important and difficult problem to optimize the labor efficiency and cost. The trucks enter the hub at different hours a day, in different known time schedules and operating hours. In this paper, we propose a goal programming to maximize the labor efficiency via minimizing the allocation cost. The proposed model of this paper is implemented for a real-world of a case study and the results are analyzed.
Mohammad Khalilzadeh, Alborz Hajikhani, Seyed Jafar Sadjadi,
Volume 28, Issue 1 (IJIEPR 2017)
Abstract
The present paper aims to propose a fuzzy multi-objective model to allocate order to supplier in uncertainty conditions and for multi-period, multi-source, and multi-product problems at two levels with wastages considerations. The cost including the purchase, transportation, and ordering costs, timely delivering or deference shipment quality or wastages which are amongst major quality aspects, partial coverage of suppliers in respect of distance and finally, suppliers weights which make the products orders more realistic are considered as the measures to evaluate the suppliers in the proposed model. Supplier's weights in the fifth objective function are obtained using fuzzy TOPSIS technique. Coverage and wastes parameters in this model are considered as random triangular fuzzy number. Multi-objective imperial competitive optimization (MOICA) algorithm has been used to solve the model,. To demonstrate applicability of MOICA, we applied non-dominated sorting genetic algorithm (NSGA-II). Taguchi technique is executed to tune the parameters of both algorithms and results are analyzed using quantitative criteria and performing parametric.
Komeil Fattahi, Ali Bonyadi Naeini, Seyed Jafar Sadjadi,
Volume 34, Issue 1 (IJIEPR 2023)
Abstract
Venture capital (VC) financing is associated with the challenges of double-sided moral hazard, and uncertainty, which leads to the difficulty in estimating the venture's value accurately and consequently the impossibility of determining the optimal equity sharing between the entrepreneur and investor. Traditionally, convertible preferred equity mechanisms used to be implemented as an incentive to decline moral hazard. However, despite the emphasis on investor risk-taking, such mechanisms transfer the investor risk to the entrepreneur and do not mitigate the incentive of opportunistic behaviors. Furthermore, according to the literature review, and to the best of the authors’ knowledge, there has not been developed any practical mechanism for equity sharing in VC financing up to now. This paper proposes a fair equity sharing mechanism, which alleviates the above-mentioned deficiencies. It adjusts both parties' share during the equity dilution in each stage of financing, regarding the difference between the venture's ex-ante and ex-post values. Moreover, it manages uncertainty by applying staged financing and the option of abandonment at the end of each stage. The proposed mechanism has been verified by using the mathematical tools and drawing its curves for a case study.
Amirmohammad Larni-Fooeik, Hossein Ghanbari, Seyed Jafar Sadjadi, Emran Mohammadi,
Volume 35, Issue 1 (IJIEPR 2024)
Abstract
In the ever-evolving realm of finance, investors have a myriad of strategies at their disposal to effectively and cleverly allocate their wealth in the expansive financial market. Among these strategies, portfolio optimization emerges as a prominent approach used by individuals seeking to mitigate the inherent risks that accompany investments. Portfolio optimization entails the selection of the optimal combination of securities and their proportions to achieve lower risk and higher return. To delve deeper into the decision-making process of investors and assess the impact of psychology on their choices, behavioral finance biases can be introduced into the portfolio optimization model. One such bias is regret, which refers to the feeling of remorse that can induce hesitation in making significant decisions and avoiding actions that may lead to unfavorable investment outcomes. It is not uncommon for investors to hold onto losing investments for extended periods, reluctant to acknowledge mistakes and accept losses due to this behavioral tendency. Interestingly, in their quest to sidestep regret, investors may inadvertently overlook potential opportunities. This research article aims to undertake an in-depth examination of 41 publications from the past two decades, providing a comprehensive review of the models and applications proposed for the regret approach in portfolio optimization. The study categorizes these methods into accurate and approximate models, scrutinizing their respective timeframes and exploring additional constraints that are considered. Utilizing this article will provide investors with insights into the latest research advancements in the realm of regret, familiarize them with influential authors in the field, and offer a glimpse into the future direction of this area of study. The extensive review findings indicate a growth in the adoption of the regret approach in the past few years and its advancements in portfolio optimization.
