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Showing 7 results for Sadjadi
Applying Semi-Markov Models for forecasting the Triple Dimensions of Next Earthquake Occurrences: with Case Study in Iran Area
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.


A New Approach to Solve Multiple Objective Programming Problems
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.
An Improved WAGNER-WHITIN Algorithm
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 .
A Multi-Objective Programming to Increase Labor Efficiency of a Truck Hub: A Case Study
, ,
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.
A Fuzzy Multi-Objective Supplier Selection Model with price and wastages considerations
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. 


New Applied Mechanism for Fair Equity Sharing to Overcome The Challenges of Venture Capital Financing
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.
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