This paper derives a deterministic inventory model for deteriorating items with inventory dependent demand rate. This study develops an order level inventory model with single warehouse where shortages are allowed and it is completely backlogged. The planning horizon is finite. This paper shows that there exists a unique optimal cycle time to minimize the total inventory cost per cycle. Truncated Taylor’s series expansion is used for finding closed form optimal cycle time, optimal time to finish positive inventory and optimal total inventory cost per cycle. The numerical example is given to validate the proposed model. The sensitivity analysis of the solution with the changes of the values of parameters associated with the model has also been discussed.

The improvement in manufacturing process is never ending effort, which is being derived by the culture of the organization. Therefore, an attitude of perfection, innovation and devotion is an essential part for the process improvement of an organization. Recently, innovations in the field of engineering help an entrepreneur sell the products through competitive environment. Moreover, the timely delivery of goods and cost effective product is the yardstick, which contributes to the performance index. These improvements resulted from continued performance enhancement efforts, helps in producing right quality in the right times which means providing stability to the organization performance. The role of lean thinking and supply chain characteristics is to create an effective marked on the organizational performance including bonding of all the participants where-so-ever possible. The purpose of this work is to examine the challenges, which integrate the Lean Principles to Supply Chain Characteristics for the real world situation to achieve better utilization of resources, timely delivery to the customer, and deletion of non-value added items including the control on all type of wastages as linked with supply chain systems.

Global supply chains have to manage production over the whole world. Therefore, production plants are needed to supply the demand of products and parts. Due to complication and uncertainty of production market, portfolio selection is one of the most challenging problems. Type-2(T2) fuzzy is a model, which provides the ability to handle the effect of uncertainty. Aiming at this problem, we propose a T2 supplier management system operation scheme, which not only employs fuzzy C-Means clustering algorithm by dynamically increasing cluster center, but also it achieves good classification performance. The key result is that fuzzy classification applications improve the planning and operating of supply and demand in a distributed production and global supply chain.

The objective of this study is to measure the performance improvement of supply chain (SC) stages through implementing the national standardization system (NSS) in an innovative way. There are many studies on the positive effects of standardization system on supply chain performance (SCP), but very few studies have measured and prioritized the impact of this system on SCP. This paper introduces a new approach to the performance improvement of each stage of SC through implementing the NSS. First, we use fuzzy analytical hierarchical process method to measure the relative importance of each stage and determine the characteristics of SC. Then, the amount of SC stages improvement after implementing the NSS is determined. Finally, using a combination of results, the stages of SC are ranked according to the effectiveness of NSS implementation. In order to validate the proposed approach, the case analysis of Iran NSS is carried out on broiler SC. The stages of SC are ranked according to the performance improvement through implementing standardization system, subsequently. This approach can be generalized to other standardization systems and SCs.

In this paper, we have modeled a decision making problem of a tea industry as a multi-objective optimization problem in interval environment. The goal of this problem is to maximize the overall profit as well as to minimize the total production cost subject to the given resource constraints depending on budget, storage space and allotted processing times in different machines. For this purpose, the problem has been formulated as a multi-objective integer linear programming problem with interval objectives. To solve the problem, we have proposed extended elitist non-dominated sorting genetic algorithm (ENSGA-II) for integer variables with interval fitness, crowded tournament selection, intermediate crossover, one neighborhood mutation and elitism. To develop this algorithm, we have proposed modified non-dominated sorting and crowding distance based on interval mathematics and interval order relations. Finally, to test the performance of the proposed algorithm, a numerical example has been solved.

Contractor selection plays essential role on development of business industries and any selection strategy is normally involved with various factors. This paper presents an empirical investigation to determine important factors influencing contractor selection to increase profitability. The proposed model of this paper is implemented for an Iranian constructor firm named Kayson Company located in city of Tehran, Iran. The study has been accomplished among top managers who worked for this firm. Using structural equation modeling, the study determines that five factors including performance, believes, flexibility, quality, price and services influence on profitability when a contractor is to be chosen.

Considering the importance and extensive range of decision-making, scientists from various fields have had many discussions on this issue. Various models have been proposed to facilitate decision-making and have had much utilization. In many site selection problems, multiple objectives must be obtained, simultaneously. This study uses a mathematical model to select a suitable location for the refinery in the multi attribute environment. The proposed model uses a large amount of qualitative and quantitative information in the frame of multi objective functions for the first time in the refinery site selection and is flexible enough to use decision makers’ opinions in order to achieve goals. For this reason, after a brief overview of the selected area characteristics, using analytic hierarchy process (AHP) for weighting the criteria, a mathematical operation research model is proposed to determine the best alternatives.

This paper presents a study to investigate the effects of open innovation factors on supply chain behavior in Iranian gas industry. The study uses two questionnaires, one to measure the effects of open innovation factors developed by Chesbrough (2003) [Chesbrough, H. W. (2003). Open innovation: The new imperative for creating and profiting from technology. Harvard Business Press.] and the other to measure the effects of supply chain behavior. Using Pearson correlation ratio as well as Stepwise regression model, the study has determined a positive and meaningful relationship between open innovation and supply chain behavior. In our survey, while intellectual property management and networking had no impact on supply chain behavior, three variables of research and development, cooperation and entrepreneurship influence positively on supply chain behavior.

Nowadays, the advance and enhance in competitive area, convert the supply chain management into one of the most important issues for industries, organization, and firms. Increasing the quality of products, decreasing the costs, and representing the satisfying service are the primary objectives of organization and managers. Apart from that, the amount of CNGs (such as CO2) has been raised by industrial activities. Therefore, the concern of air pollution motivates managers and researchers to consider this issue in the process. This paper represents a multi objective supply chain network fuzzy programming, which is multi product, multi period, multi-layer, and has reverse product network. Operational risks are considered as deficiency in suppliers’ units and production center. The model’s duty is to choose the optimal suppliers based on different factors such as selling price, the average of deficiency and transportation costs. In order to solve the model, the Jimenez and TH approach are used and for large-scale problems, the paper uses the NSGA-II algorithm.

Globalization, intensification of governmental and non-governmental organization & apos; s provisions and squeeze and the demand of clients about concerning environmental affairs have motivated many organizations to start considering Green Supply Chain management in order to facilitate environmental and economic functions. Administration of green supply chain management unifies the management of supply chain with environment requirements during the functioning of levels of supply chain. This paper aims to identify green supply change management & apos; s factors in order to facilitate implementation of green supply chain management in rail industry. Thus, the effective factors of green supply chain management establishment are extracted and the method of interactions between sub-scales is studied by DEMATEL technique. The result specifies that reduction of production loss sub-scale is the most effective factor on other agents. In addition, the effective elements peered out by fuzzy TOPSIS that the scale of loss management stands on the first ranking and improvement of production process and interior environment management scales stand on the second and the third level and other scales follow them.