One of the primary concerns on supply chain management is to select appropriate suppliers based on different criteria, which are often in serious conflict. In this paper, we present a fuzzy TOPSIS technique to prioritize suppliers on reverse logistic network based on different criteria and then the proposed model of this paper applies fuzzy linear programming technique to determine optimum order quantity associated with each supplier. There are three criteria associated with each supplier including technical skills, equipment and ability to analyze. The implementation of the proposed method has been demonstrated in case study.

This paper proposes the social network analysis (SNA), to study interaction among various
activities in a product development process (PDP). The implementation of SNA helps to
measure the properties of information flow and identifies PDP activities and limitations. The
findings of an exploratory research project which explores the potential of SNA, as an improve
tool for visually mapping and analyzing the stakeholders relationships found across the IC
substrates design/manufacturing’s PDP of the Unimicron Technology Corp. From the findings,
the authors prescribe the necessary SNA recommendations to improve the social conditions
within the PDP.

In this paper, a bi-objective mathematical model for emergency services location-allocation
problem on a tree network considering maximum distance constraint is presented. The first
objective function called centdian is a weighted mean of a minisum and a minimax criterion
and the second one is a maximal covering criterion. For the solution of the bi-objective
optimization problem, the problem is split in two sub problems: the selection of the best set of
locations, and a demand assignment problem to evaluate each selection of locations. We
propose a heuristic algorithm to characterize the efficient location point set on the network.
Finally, some numerical examples are presented to illustrate the effectiveness of the proposed
algorithm.

The economic lot scheduling problem (ELSP) is a challenge between sequencing and lot sizing. In this problem, several products must be produced on a single machine in a cyclical production pattern and the primary goal is to minimize the total setup and holding expenditures. Since time affects the value of money, it is necessary to take into account the time value of money when gradual payment is the case. In this paper, a new ELSP model with the consideration of the time value of money is considered. The proposed model of this paper is formulated as a nonlinear mixed integer model and a hybrid GA is presented to solve the resulted model for large-scale problems. The proposed method is solved for some benchmark problems for large-scale problems.

One of the most important issues on quality of building structure is its resistance against
earthquake. Earthquake, as one of natural disasters, has been one of the main reasons of fatal
incidents in developing countries. Any attempt to increase the quality of building structure
could reduce any possible damages an earthquake could cause on society. This paper presents a
system dynamic model to study the importance and behavior of the factors which affect the
construction quality of buildings & apos; structures. The proposed model of this paper is analyzed for a
case study and the results are discussed. The paper also uses DEMATEL technique to compare
the results of the proposed method. The paper concludes that among the whole factors which
affect the construction quality of buildings & apos; structures, the "performance of related
organizations and institutions" is of the most important ones.

In this paper, we address the optimization of an integrated line balancing process with workstation inventory management. While doing so, we have studied the interconnection between line balancing and its conversion process. Almost each and every moderate to large manufacturing industry depends on a long and integrated supply chain, consisting of inbound logistic, conversion process and outbound logistic. In this sense an approach addresses a very general problem of integrated line balancing. Research works reported in the literature so far mainly deals with minimization of cost for inbound and outbound logistic subsystems. In most of the cases conversion process has been ignored. We suggest a generic approach for linking the balancing of the line of production in the conversion area with the customers’ rate of demand in the market and for configuring the related stock chambers. Thus, the main aim of this paper is to translate the underlying problem in the form of mixed nonlinear programming problem and design the optimum supply chain so that the total inventory cost and the cost of balancing loss of the conversion process is jointly minimized and ideal cycle time of the production process is determined along with ideal sizes of the stock chambers. A numerical example has been added to demonstrate the suitability of our approach.

One of the primary issues on marketing planning is to know the customer & apos; s behavioral trends. A
customer & apos; s purchasing interest may fluctuate for different reasons and it is important to find the
declining or increasing trends whenever they happen. It is important to study these fluctuations
to improve customer relationships. There are different methods to increase the customer & apos; s
willingness such as planning good promotions, an increase on advertisement, etc. This paper
proposes a new methodology to measure customer & apos; s behavioral trends called customer
electrocardiogram. The proposed model of this paper uses K-means clustering method with
RFM analysis to study customer & apos; s fluctuations over different time frames. We also apply the
proposed electrocardiogram methodology for a real-world case study of food industry and the
results are discussed in details

This paper addresses a bi-criteria scheduling problem with deteriorating jobs on a single machine. We develop a model for a single machine bi-criteria scheduling problem (SMBSP) with the aim of minimizing total tardiness and work in process (WIP) costs. WIP cost increases as a job passes through a series of stages in the production process. Due to the uncertainty involved in real-world scheduling problems, it is sometimes unrealistic or even impossible to acquire exact input data. Hence, we consider the SMBSP under the hypothesis of fuzzy L-R processing time's knowledge and fuzzy L-R due date. The effectiveness of the proposed model and the denoted methodology is demonstrated through a test problem.

Supply chain management (SCM) is becoming critical as firms recognize that competition is
shifting from company versus company to supply chain versus supply chain. In the present
competitive scenario, the fierce competition has driven most companies to seek for means of
enhancing performance beyond their four wall boundaries. The firm’s ability in collaborating
with its upstream and downstream partners determines its success in attaining better
performance with supply chain collaboration; a firm is able to serve fragmented markets in
which end customers require more product varieties and availability with shorter product life
cycle and, at the same time, lower supply chain costs. This paper introduces the framework of
continuous supply chain collaboration (CSCC), which extends the traditional frame of reference
in strategic sourcing from a supplier centric to a supply-chain-scope as continuous
improvement efforts to enhance the customer satisfaction. CSCC practices are rather
exceptional, yet CSCC is believed to be the single most comprehensive framework for attaining
operational excellence.

This paper proposes a particle swarm optimization (PSO) algorithm to solve various types of economic dispatch (ED) problems in power systems such as, environmental/economic dispatch (EED) and multi-area environmental/economic dispatch. The proposed model considers the environmental impact to achieve the minimization of fuel costs and pollutant emissions, simultaneously. The EED problem is further extended to dispatch the power among different areas to aid emission allowance trading. The performance of the proposed PSO is compared with conventional method and genetic algorithm. The results clearly show that the proposed algorithms give global optimum solution compared to the other methods. The results obtained also show that the proposed PSO algorithms can provide comparable dispatch solutions with reduced computation time for all types of ED problems.