International Journal of Supply and Operations Management
Volume:6 Issue: 1, Winter 2019

The distribution of goods from suppliers to customers plays an important role in the supply chain. In this paper, the approach of Demand Driven Distribution Resource Planning (DDDRP) is proposed in order to optimize the distribution flow in the supply chain. The purpose is to manage all sources of variability "operational, management, supply and demand", while improving the traditional methods as Distribution Resource Planning (DRP). A literature review is presented about the impact of variability on distribution flow, and the solutions proposed in this context. Then, a general study of distribution industries is investigated in order to apply the DDDRP method; we show the buffer positioning in the distribution network, and the profile and levels for these buffers. After the dynamic adjustment, we present the Demand Driven Planning and the execution based on the net flow equation. The results discuss the approach and the steps of the implementation in the distribution industry.

The present study proposes an integrated model for hub location problem in a Multi-location, Multi-period, Multi-commodity (3M), three echelon supply chain. The problem is formulated as a mixed integer programming model and solved using GAMS software. As the developed model is a mixed integer non leaner programming and NP-hard, a new algorithm for re-formulation is proposed to change it to a mixed integer leaner programming and also a new heuristic algorithms is proposed to solve it in a reasonable time. To prove the applicability of the model, the well-known real CAB data set is used. Numerical examples show the benefit of the proposed model in both solution time and result quality.

In this paper, we propose a credibility-based fuzzy mathematical programming model for integrating the production and distribution in milk supply chain under uncertainty. The proposed model is a mixed integer linear programming, which takes into account technological constraints and aims to maximize the total profit including the total costs such as production, storage, and distribution. To bring the model closer to real-world planning problems, the objective function coefficients (e.g. production cost, inventory holding and transport costs) and other parameters (e.g., demand, production capacity, and safety stock level), are all considered fuzzy numbers. In the uncertain environment, the most known criteria widely employed are optimistic and pessimistic value criterions. Both criteria present some deficiency. For the optimistic criterion, it suggests an audacious who is attracted by high payoffs (low cost), while for the pessimistic criterion, it suggests a conservative decision-maker who tries to make sure that in the case of an unfavorable outcome (loss), there is at least (in most) a known minimum payoff (loss maximum). To overcome these problems, the Hurwicz criterion is used for the concerned problem. By varying the value of θ, it can balance the optimistic and pessimistic levels of the decision makers. Moreover, the different property of the credibility measure is used to build the crisp equivalent model, which is a MILP model that can solve, by using a commercial solver such as GAMS. Finally, numerical results are reported for a real case study to demonstrate the efficiency and applicability of the proposed model.

This study aimed to determine the applicability to which green supply chain practices employed by Shell and Co-operation Petroleum Company in Egypt. Additionally, the impact of Green Supply Chain practices on the operational performance of each company. The results, based on benchmarking, were statistically analyzed by Fischer analysis. Concerning the company's practices of green procurement, the results revealed highly significant differences (p

This paper shows that cooperative grey game theory can help us to establish a fair cost share between private organizations for supporting the temporary housing problem by using facility location games under uncertainty. Temporary accommodation may be a method that ought to get started before the tragedy happens, as a preventative pre-planning. In spite of being temporary constructions, the housing buildings are one of the most essential parts to produce in emergency situations, to contribute to the reconstruction and to recover better. Our study is based on a default earthquake in Izmir of western Turkey. A number of tents are being built in the following three cities, Aydin, Usak, and Balikesir near Izmir as illustrated in Figure 1. Two companies are selected, one is local and another is foreign to distribute the tents in a fair way between the three cities. For this purpose, we use cooperative grey game theory to help us to define a fair cost allocation between private organizations for supporting the housing problem by using facility location games under uncertainty.

This paper addresses a dynamic cell formation problem (DCFP) including a multi-period planning horizon in which demands for each product in each period are different and uncertain. Because the demand uncertainty is considered as stochastic data by discrete scenarios on a scenario tree, a multi-stage nonlinear mixed-integer stochastic programming is applied such that the objective function is minimizing of machine purchase costs, the operating costs, both inter and intra-cell material handling costs, and the machine relocation costs over the planning horizon. The main goal of the current study is to determine the optimal cell configuration in each period in order to achieve the minimum total expected costs under the given constraints. The nonlinear model is transformed into a linear form to this reason that GAMS can get to global optimal solutions in linear models. In order to find the optimal solutions, by using the GAMS for small and medium-sized problems, the optimal solutions are obtained. They applied in two bounds namely the Sum of Pairs Expected Values (SPEV) and the Expectation of Pairs Expected Value (EPEV). Also, according to the scenario-based model, the efficiency of two suggested bounds is shown in terms of the computational time. Finally, a practical case study is presented in detail to illustrate the application of the proposed model and it's solving method. The results show the efficiency of using SPEV and EPEV for several random examples as well as the proposed case study.

The purposes of this research were (1) To develop of supply chain management-information system for curriculum management Based on National Qualifications Framework for Higher Education. (2) To study the efficiency development of supply chain management-information system for curriculum management based on National Qualifications Framework for Higher Education. In this system was designed by PHP script and MySQL database for store the data. The research methodology was done according to System Development Life Cycle concept. This system was separated into 4 groups 1) Administrator main menu 2) Student home menu 3) Lectures home menu 4) Entrepreneurs home menu .The efficiency development of supply chain management-information system for curriculum management based on national qualifications framework for higher Education. The Black Box Testing evaluation included tests as follows: 1) System Requirement Test; 2) System Requirement Test; 3) Usability Test; 4) Security Test, shows the average score was 8.63 out of 10 scale. suggesting that, Supply Chain Management-Information System for Curriculum Management based on National Qualifications Framework for Higher Education may be applied to support.