Supply chain coordination for the joint determination of order quantity and reorder point using credit option

Decisions regarding order quantity and reorder point are two major challenges in supply chain inventory management. In this paper, a coordination model of the joint determination of these two decision variables is proposed. A decentralized supply chain consisting of one buyer and one supplier in a multi-period setting is investigated. Demand and lead times are uncertain in our model. An incentive scheme based on credit option has been developed to encourage the buyer to participate in the coordination model. In this model, the downstream member has the option of using credit to purchase goods during the credit time, subject to its commitment to a jointly agreed order quantity and reorder point. The credit time is determined in such a way that the two parties have incentives to participate. The proposed incentive scheme can share the benefits of coordination between the two members based on their bargaining power. The proposed model shows that the coordination of the reorder point, together with order quantity, can increase the overall chain profitability as well as each member's profitability.Supply chain Coordination Reorder point Safety stock Credit option

LT variance or LT mean reduction in supply chain management: Which one has a higher impact on SC performance?

Lead time (LT) is an inseparable factor of any supply chain (SC). Lead time uncertainty is known as a type of supply uncertainty that affects ordering policies, inventory levels, and product availability level. There are two main strategies concerning SC uncertainties: adapter and shaper strategies that can be used in environments with LT uncertainty. As for LT mean, it can be reduced by improving the performance of upstream members. In this paper, relative importance of these two parameters to be reduced by these strategies is determined by investigating the effects of both LT mean and LT variance on supply chain performance indices. Simulation and multivariate models have shown that LT variance has a stronger impact on SC performance measures (including Bullwhip effect, holding inventory, stock-out size and number of stock-outs). This study can help managers in (1) rebalancing of these two parameters by applying a proper investment strategy; (2) suitable selection of service providers in transportation based on LT parameters.Lead time variance Lead time mean Simulation Canonical correlation Multivariate analysis

A Bi-Level Programming Model for Closed-Loop Supply Chain Network Design with Competition between two chains in Uncertain Environment: A Benders Decomposition Solution

In this paper the closed-loop supply chain network design problem is modeled and solved in a competitive and uncertain environment. The competition between two supply chains is on the price of products in forward channel and the price of returns (incentives) on the reverse channel. Demand is price sensitive and the amount of returned products is also linearly dependent on the incentives. Fuzzy set theory is used to cope with uncertainty. The proposed bi-level model is proved to be concave then we turn it to a single level model which is also proved to be a concave one. Afterwards, the single level model is solved using the Benders Decomposition approach. Finally, computational results are presented based on data inspired from real case. Results show that the proposed algorithm is converged in reasonable iterations. Increasing the price elasticity coefficient (intensifying competition) leads to less profit and Increasing the rivalâs price elasticity coefficient leads to more profits for the existing chain

THE FUZZY EVALUATION OF THE ICT PROJECTS IN STRATEGIC ENVIRONMENT (CASE STUDY: IRAN TELECOMMUNICATION RESEARCH CENTER)

Many criteria should be considered for project selection in Information and Communication Technology (ICT) sectors; while, the resources are limited. Besides, the uncertainty of the selection and evaluation process increases the difficulty of ICT project selection. Therefore, a fuzzy system in combination with fuzzy integer linear programming, fuzzy entropy, and fuzzy numbers have been developed; it smoothes the process of ICT project selection. This fuzzy system is flexible in the project selection for Iran ICT sectors, especially in (Research and Development) R&D sectors. It enhances the accuracy of the evaluation process as it resolves the uncertainty of ICT project selection.ICT project selection, fuzzy integer linear programming, fuzzy system, fuzzy entropy, fuzzy numbers

Capacitated network-flow approach to the evacuation-location problem

Evacuating people to the safe zones is the most crucial operation in managing many disasters. A mathematical model is presented in this paper, combining locational decisions with the max-flow problem in order to select safe destinations which maximize the number of dispatched people. The existing frameworks for emergency logistics usually model the evacuation process based on fixed and pre-determined destinations with a strategic perspective. The unpredictable and turbulent nature of a disaster may; however, disrupt the predictions. Furthermore, the primary goal in emergency situations is to dispatch people from the danger zone to a safe place, no matter where. A mixed integer linear programming model is developed in this paper for selecting one or more destinations in a capacitated network. The special structure of the model and its similarity to the max-flow problem allow us to develop exact algorithms and heuristics both for the multiple and single destination location problem. The solution methods are based on existing algorithms for the max-flow problem. Our proposed heuristics use the idea of adding a super-sink to the network to generate upper bounds very fast. The exact algorithms as well as the heuristics are tested on randomly generated instances as well as a real world network. The most important statistics of their computation times are reported. They are also compared according to their performance (gap to optimality) and their behavior amongst different categories of the graphs. Finally we have presented a real-case addressing the problem of choosing a number of destination locations from a fixed set of pilot pre-determined locations. The problem of deciding on the destinations is considered under 5 grades of disaster severity and the related impacts on choosing the safe zones are analyzed