Ali H. Kashan - Academia.edu (original) (raw)

Papers by Ali H. Kashan

Complexity

Order picking, which is collecting a set of products from different locations in a warehouse, has... more Order picking, which is collecting a set of products from different locations in a warehouse, has repeatedly been described as one of the most laborious and time-consuming internal logistic processes. Each order is issued to pick some products located at given locations in the warehouse. In this paper, we consider an order picking problem, in which a number of orders with different delivery due dates are going to be retrieved by a limited number of order pickers in multiperiods such that the total tardiness is minimized. The aim is to determine a retrieval plan in terms of order batching and order picker multitrip routing as decision variables. Besides, products are arrived and replenished at the predetermined locations at different periods. Therefore, products sitting in those locations should be delivered soon to provide empty rooms for replenishment. A mixed integer linear programming formulation is proposed for this new problem. The model is optimally solved for small-size probl...

Journal of Combinatorial Optimization

This study proposes a framework for the main parties of a sustainable supply chain network consid... more This study proposes a framework for the main parties of a sustainable supply chain network considering lot-sizing impact with quantity discounts under disruption risk among the first studies. The proposed problem differs from most studies considering supplier selection and order allocation in this area. First, regarding the concept of the triple bottom line, total cost, environmental emissions, and job opportunities are considered to cover the criteria of sustainability. Second, the application of this supply chain network is transformer production. Third, applying an economic order quantity model lets our model have a smart inventory plan to control the uncertainties. Most significantly, we present both centralized and decentralized optimization models to cope with the considered problem. The proposed centralized model focuses on pricing and inventory decisions of a supply chain network with a focus on supplier selection and order allocation parts. This model is formulated by a scenario-based stochastic mixed-integer non-linear programming approach. Our second model focuses on the competition of suppliers based on the price of products with regard to sustainability. In this regard, a Stackelberg game model is developed. Based on this comparison, we can see that the sum of the costs for both levels is lower than the cost without the bi-level approach. However, the computational time for the bi-level approach is more B Parisa Rafigh

Energies

Policy-makers should focus on solar energy due to the increasing energy demand and adverse conseq... more Policy-makers should focus on solar energy due to the increasing energy demand and adverse consequences such as global warming. Conflicting criteria influence choosing the most desirable place to construct a Solar Power Plant (SPP). Researchers have popularized multicriteria decision-making (MCDM) methods because of the potential. Although the simultaneous use of several methods increases the robustness and accuracy of the results, existing methods to integrate MCDM methods mainly consider the same weight for all methods and utilize the alternatives ranking for the final comparison. This paper presents a hybrid decision-making framework to determine the best location for SPPs in Iran using a set of criteria extracted from the literature and expert opinions. An initial list of decision-making alternatives is prepared and evaluated using GIS software in terms of criteria. Decision-makers prioritized the identified alternatives using the MCDM methods, including SWARA and different rank...

Algorithms for Intelligent Systems, 2019

Civil engineering infrastructures journal, 2018

In this paper a league championship algorithm (LCA) is developed for structural optimization wher... more In this paper a league championship algorithm (LCA) is developed for structural optimization where the optimization variables are of discrete type and the set of the values possibly obtained by each variable is also given. LCA is a relatively new metaheuristic algorithm inspired from sport championship process. In LCA, each individual can choose to approach to or retreat from other individuals in the population. This makes it able to provide a good balance between exploration and exploitation tasks in course of the search. To check the suitability and effectiveness of LCA for structural optimization, five benchmark problems are adopted and the performance of LCA is investigated and deeply compared with other approaches. Numerical results indicate that the proposed LCA method is very promising for solving structural optimization problems with discrete variables.

Journal of Hospital, 2016

Background: Medical centers location is one of the most important problems which should be consid... more Background: Medical centers location is one of the most important problems which should be considered in different dimensions to improve services delivery. In this paper, the hierarchical maximum covering problem was assessed for bi-level healthcare systems including Clinics and hospitals using taking the service rates into account. The initial objective was minimizing the uncovered demand nodes, and secondary objective was minimizing the lost demand rate as a measure of potentially patients’ retention in coverage radius. Materials and Methods: In order to queue system analysis, the serving system assessed in the Tehran heart center hospital. The proposed method is a mathematical optimization model called probabilistic two-stage programming model. To evaluate this model, a number of numerical problems solved by GAMS software. Results: Study results revealed that the best condition for locating the medical centers is adjacent to a hospital. Decision making about the location problem ...

Environmental Science and Pollution Research, 2021

Multi-criterion decision-making models are widely used in supplier selection problems. This study... more Multi-criterion decision-making models are widely used in supplier selection problems. This study contributes to a green supplier selection problem considering the green manufacturing, green transportation, and green procurement. This study contributes to reverse logistics, eco-design, reusing, recycling, and remanufacturing with their high impact on the industries. In addition to the logistics costs and transportation costs, the carbon emissions are considered. With regard to the game theory, this paper uses a cooperative green supplier selection model. If transportation requirements of two or more companies are combined, it will help manufacturers to have less CO 2 emissions with lower cost. After creating the optimization model to consider the uncertainty, this cooperative game theory model is established in a fuzzy environment. In this regard, a fuzzy rule-based (FRB) system is deployed and the set of fuzzy IF-THEN rules is considered. The proposed FRB model is contributed for the first time in the area of green supplier selection problem. Finally, some sensitivity analyses are conducted in a numerical example to evaluate the proposed model. With regard to the findings, although the cost of CO2 emission of horizontal cooperation is increased, the cost saving of companies is increased. It means our total cost is optimal in a logistic network using the cooperative game theory. The results also indicate that horizontal cooperation in logistic network causes less cost and benefits for each company.

Soft Computing, 2020

In online direct selling, three effective elements, namely price, refund and quality, affect the ... more In online direct selling, three effective elements, namely price, refund and quality, affect the increment (or decrement) of demand and product return. This paper considers forward and backward (i.e., return) pricing decisions under uncertainty and develops a fuzzy mathematical model based on the Stackelberg game approach utilizing the proper action and reaction between a manufacturer and a retailer. Moreover, media advertising and manufacturer's desire for accepting massive payments made us take into account the advertising as another factor influencing the demand. By an agreement between the manufacturer and the retailer, the costs of advertising and raising the level of the product quality are shared by two agreed rates. Two numerical examples are considered and the associated results are analyzed under fuzzy and crisp conditions when customers are sensitive or insensitive to the quality of the product. It is found that incorporation of the quality factor under a fuzzy environment has a better performance compared with the case of ignoring the quality and uncertainty in the parameters.

Socio-cultural Inspired Metaheuristics, 2019

Environmental Science and Pollution Research, 2021

This study proposes a sustainable closed-loop supply chain under uncertainty to create a response... more This study proposes a sustainable closed-loop supply chain under uncertainty to create a response to the COVID-19 pandemic. In this paper, a novel stochastic optimization model integrating strategic and tactical decision-making is presented for the sustainable closed-loop supply chain network design problem. This paper for the first time implements the concept of sustainable closedloop supply chain for the application of ventilators using a stochastic optimization model. To make the problem more realistic, most of the parameters are considered to be uncertain along with the normal probability distribution. Since the proposed model is more complex than majority of previous studies, a hybrid whale optimization algorithm as an enhanced metaheuristic is proposed to solve the proposed model. The efficiency of the proposed model is tested in an Iranian medical ventilator production and distribution network in the case of the COVID-19 pandemic. The results confirm the performance of the proposed algorithm in comparison with two other similar algorithms based on different multi-objective criteria. To show the impact of sustainability dimensions and COVID-19 pandemic for our proposed model, some sensitivity analyses are done. Generally, the findings confirm the performance of the proposed sustainable closed-loop supply chain for the pandemic cases like COVID-19.

Scientia Iranica, 2020

During the years of imposed sanctions against Iran, Iran Khodro Company (IKCO) got into a hazardo... more During the years of imposed sanctions against Iran, Iran Khodro Company (IKCO) got into a hazardous situation due to CKD parts' purchasing cost increment and emersion of new product variants in the competitive market. To examine such situation, this study examines a multi-period semi-centralized dual-channel supply chain where a common retailer (free market) and two manufacturers' (IKCO and Saipa as a major competitor) direct channels are confronted with reference price dependent and stochastic demand. The problem is analyzed under Stackelberg and cooperative games scenarios using heuristic algorithm and a League Championship algorithm respectively, as solution methods. Results obtained from solving the problem with IKCO data proves higher profitability of the cooperative game and its remarkable resilience for all products' memory types i.e. short/long term memory against production cost disruption which is imposed to IKCO in some periods. Besides calculating Saipa's optimal wholesale price in the disruption periods, our approach with support of experimental analyses is able to assign a supply chain's degree of resilience against disruptions to its product's memory type and also power structure. 1 Introduction In industrial world, considerable increase in number of manufacturers stimulates their concern about continuity and as a result, persuades them to enhance their product to meet customer's preferences and interests. Therefore, the manufacturers should have a close relationship with the customers. Dual-channel supply chain is a kind of supply chain providing this 2 relationship. The dual-channel supply chain, as it is evident from its name, has two selling channels, including retail channel (also known as traditional channel) in which product is offered by retailer and E-direct channel wherein selling of the product is conducted by the manufacturer and ordinarily using internet. Academic researches orientation towards the dualchannel supply chain and using this type of supply chain by top manufacturers of the world like Samsung, HP, IBM, Sony, Dell, Lenovo, Panasonic, and Pioneer Electrics demonstrate the profitability and its vital role in survival of a manufacturer [1]. Some Iranian companies like IKCO, Saipa, Pars Shahab Light Company and Rasa Nour Neishabour Company have two selling channels. Pricing is one of the crucial decisions in the supply chain and is influential in its profitability. There is a strong literature in supply chain pricing field. Due to the fact that most of the researches utilized game theoretical approach, some of them are indicated briefly in this section. Sana et al (2014) studied a three-layer supply chain and considered both collaborative and Stackelberg scenarios [2]. Modak et al (2016) studied a closed loop supply chain and considered cooperative and Stackelberg games scenarios that in the stackelberg game, the retailers' competition was modeled under Cournot and collusion games [3]. Modak et al (2016) investigated a supply chain wherein they considered manufacturer-led Stackelberg vertical game in which the retailers have three different behaviors namely Cournot, Collusion and Stackelberg. They utilized all units discount contract with franchise fee as a channel conflict respondent [4]. Sana et al (2017) considered knowledge management approach in agro-industrial supply chain of cocoa wherein they took into consideration collection centers-led Estackelberg and collaboration scenarios [5]. Modak et al (2018) considered a two-echelon closed loop supply chain in which in addition to considering three possible collection activities of used product for recycling namely retailer led collection, manufacturer led collection and third party led collection, they introduced the concept of sub-game perfect equilibrium and alternative offer bargaining strategy to resolve the channel conflict and distribute surplus profit [6] Roy et al (2018) studied a two-echelon supply chain and obtained optimal order quantity under Estackelberg, Bertland, Cournot-Bertland and integrated scenarios [7]. It is worth mentioning that, the importance of pricing in the dual-channel supply chain is higher than the one-channel supply chain due to the existence of price competition that generates channel conflict. Multiplicity of the channel conflict-related researches in the literature proves the critical importance of this field. These researches have analyzed the channel conflict and introduced some strategies to decline the effects of the conflict, additionally. The strategies are divided into two groups, including use of contracts and improvement of sales services as well as customer loyalty. In the first group, Tsay and Agraval (2004) utilized game theory to examine the channel conflict and coordinate the chain members as well [8]. Mukhapaday (2006) instituted profit sharing contract while the retailer has the ability to add on some values to the product

Scientia Iranica, 2019

Origin-Destination Matrix, one of the most important elements in transportation planning, is usua... more Origin-Destination Matrix, one of the most important elements in transportation planning, is usually estimated by various techniques such as mathematical modeling, statistical methods, and heuristic approaches. Since using electronic devices is rapidly increased to help decision makers to improve models' capabilities, an iterative procedure is proposed in this paper to estimate the O-D Matrix according to vehicles' license plates detection. The main concept is to track vehicles on the first and the last links equipped by plate camera over the shortest path from origins to destinations. A two-step procedure and mathematical models are developed to adjust assigned the passing traffic to the network links by minimizing deviations between the observed and estimated truck traffic volumes. The proposed procedure is explained by an illustrative example followed by validation using experimental road network that covers seven eastern provinces of Iran including 310 nodes, 400 two-way edges, and around 3600 origin and destination pairs. Results revealed that the proposed procedure is capable to estimate O-D matrix when the network links are optimally located and equipped by road camera detection systems. In addition, such as the other heuristic approaches, the proposed procedure is sensitive to the number of iterations on the estimation accuracy.

Operational Research, 2020

This paper seeks to develop a reliable network of cross-docks by taking in to account disruption ... more This paper seeks to develop a reliable network of cross-docks by taking in to account disruption and reliability issues to hedge against heterogeneous risk of cross-docking failure. In real environments, applying a recovery policy can be a feasible strategy to handle disruptions. Hence, in this study, a recovery policy has been addressed in the form of reallocating suppliers to alternative cross-docks or altering the transportation strategy to move shipments. In addition to cross-dock location design, the optimum capacity of opened cross-docks will be determined considering the loads that will be served by each cross-docking center under regular and disruption conditions. A mixed integer nonlinear programming formulation is presented for the problem and is then linearized to present an efficient model. In order to solve it, two Lagrangian relaxation algorithms are designed and tested on 40 problem instances with different values of parameters. The results achieved by GAMS/CPLEX are compared with those of two algorithms and some analyses are performed on the solutions. Moreover, as the case study, the focus has been placed on logistic part of a car-manufacturing company with a vast supply chain network, containing more than 600 suppliers. The logistic strategies have been applied in order to reduce the transportation cost through the supply chain network and diminish the disruption subsequences in such a network. Based on the results, some managerial recommendations are presented.

International Journal of Computational Intelligence Systems, 2018

Cluster Validity Indices (CVI) evaluate the efficiency of a clustering algorithm and Data Envelop... more Cluster Validity Indices (CVI) evaluate the efficiency of a clustering algorithm and Data Envelopment Analysis (DEA) evaluate the efficiency of Decision-Making Units (DMUs) using a number of inputs data and outputs data. Combination of the CVI and DEA inspired the development of a new automatic clustering algorithm called Automatic Clustering Based on Data Envelopment Analysis (ACDEA). ACDEA is able to determine the optimal number of clusters in four main steps. In the first step, a new clustering algorithm called CSA-Kmeans is introduced. In this algorithm, clustering is performed by the Crow Search Algorithm (CSA), in which the K-means algorithm generates the initial centers of the clusters. In the second step, the clustering of data is performed from cluster to cluster, using CSA-Kmeans. At each iteration of clustering, using correct data labels, Within-Group Scatter (WGS) index, Between-Group Scatter (BGS) index, Dunn Index (DI), the Calinski-Harabasz (CH) index, and the Silhouette index (SI) are extracted and stored, which ultimately these indices make a matrix that the columns of this matrix indicate the values of validity indices and the rows or DMUs represent the number of clustering times from cluster to cluster. In the third step, the efficiency of the DMUs is calculated using the DEA method based on the second stage matrix, and given that the DI, CH, and SI estimate the relationship within group scatter and between group scatter, WGS and BGS are used as input variables and the indices of DI, CH and SI are used as output variables to DEA. Finally, in step four, AP method is used to calculate the efficiency of DMUs, so that an efficiency value is obtained for each DMU that maximum efficiency represents the optimal number of clusters. In this study, three categories of data are used to measure the efficiency of the ACDEA algorithm. Also, the efficiency of ACDEA is compared with the DCPSO, GCUK and ACDE algorithms. According to the results, there is a positive significant relationship between input CVI and output CVI in data envelopment analysis, and the optimal number of clusters is achieved for many cases.

Applied Soft Computing, 2018

Computers & Industrial Engineering, 2019

A novel population-based evolutionary meta-heuristic algorithm is introduced, which imitates the ... more A novel population-based evolutionary meta-heuristic algorithm is introduced, which imitates the Find-Fix-Finish-Exploit-Analyze (F3EA) targeting process. It considers the surface of the objective function as the battlefield and executes Find-Fix-Finish-Exploit-Analyze steps in an iterative manner. Following the radar detection rationale, a new evolutionary selection operator is introduced during the Find step. It is justified how to model the Fix step as a one-dimensional optimization problem to attain a local search operator. To produce a new solution by the Finish step, the target solution selected in the Find step is actioned artificially. This is an adaptive mutation stage, in which the position of the new potential solution is identified via modeling of projectile motion. The Exploit step takes over opportunities provided by mating the generated solution and its parent solution. Finally, the Analyze step, updates the population. Extensive experiments are conducted based on engineering optimization problems and a large set of benchmark functions for performance assessment, sensitivity analysis of the control parameters, and effectiveness analysis of different steps of the algorithm. Results of statistical tests signify that equipping the algorithm with new selection, mutation and local search operators makes it effective and efficient enough to exceed or match the best of rivals.

Scientia Iranica, 2018

The multi-period portfolio optimization models were introduced to overcome the weaknesses of the ... more The multi-period portfolio optimization models were introduced to overcome the weaknesses of the single-period models via considering a dynamic optimization system. However, due to the nonlinear nature of the problem and rapid growth of the size complexity with increasing the number of periods and scenarios, this study is devoted to developing a novel league championship algorithm (LCA) to maximize the portfolio's mean-variance function subject to different constraints. A Vector Auto Regression model is also developed to estimate the return on risky assets in different time periods and to simulate different scenarios of the rate of return accordingly. Besides, we proved a valid upper bound of the objective function based on the idea of using surrogate relaxation of constraints. Our computational results based on sample data collected from S&P 500 and 10-year T. Bond indices indicate that the quality of portfolios, in terms of the meanvariance measure, obtained by LCA is 10 to 20 percent better than those of the commercial software. This sounds promising that our method can be a suitable tool for solving a variety of portfolio optimization problems.

Scientia Iranica, 2018

Under restructuring of electric power industry and changing traditional vertically integrated ele... more Under restructuring of electric power industry and changing traditional vertically integrated electric utility structure to competitive, market clearing price (MCP) prediction models are essential for all generation company (GenCos). In this paper, a hybrid model is presented to predict hourly electricity MCP. The proposed model contains a Neural Network (NN), Particle swarm optimization (PSO) and Genetic Algorithm (GA). The NN is used as the major forecasting module to prediction and PSO applied to improve the traditional neural network learning capability and GA applied to optimize NN architecture. The main contribution of this paper includes: (a) presenting a new hybrid intelligent model for market clearing price prediction; (b) applying K-Means algorithm to clustering NN's test set and seasonality pattern detection; and (c) evaluation of proposed model performance by improved MAE with penalty factor for positive error. The proposed method has been tested on real-world electricity market of Iran for the one month of the year 2010 and 2013 that result shown, average weighted MAE for prediction is equal to 0.12 and forecasting of MCP by a proposed model can be improved by more than 6.7% and 4%in MAE in compare of simple NN and combination of NN and bat algorithm.

Scientia Iranica, 2018

In this paper, we consider a manufacturer that produces products in a finite horizon time and sel... more In this paper, we consider a manufacturer that produces products in a finite horizon time and sells products with non-renewing free replacement warranty policy. The manufacturer is responsible to provide spare parts for failed products, whether the products are under or out of warranty. Previous research on warranty optimization has focused on maximizing manufacturer profit without considering the spare part market for out-of-warranty products. This study proposes a novel nonlinear model that maximizes manufacturer profit by optimization of price, warranty length and spare part inventory for under-and out-of-warranty products in a manufacturing/remanufacturing system. Due to the model's unique structure, we propose a new two-stage approach that combines metaheuristic and an exact method, in which the first stage is to determine product's prices and warranty length with metaheuristic algorithm and in the second stage the remaining inventory related problem is transferred to a Minimum Cost Network Flow Problem which is solved for spare part inventory control. To illustrate the effectiveness of the suggested method, the model is solved for a case study of Iranian SANAM electronic company with two different metaheuristic algorithms and a sensitivity analysis is conducted to study the effect of various parameters on the optimal solution.

Complexity

Journal of Combinatorial Optimization

Energies

Algorithms for Intelligent Systems, 2019

Civil engineering infrastructures journal, 2018

Journal of Hospital, 2016

Environmental Science and Pollution Research, 2021

Soft Computing, 2020

Socio-cultural Inspired Metaheuristics, 2019

Environmental Science and Pollution Research, 2021

Scientia Iranica, 2020

Scientia Iranica, 2019

Operational Research, 2020

International Journal of Computational Intelligence Systems, 2018

Applied Soft Computing, 2018

Computers & Industrial Engineering, 2019

Scientia Iranica, 2018