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In this research author reviews references related to the topic of multi criterion (goal programming, multiple objective linear and nonlinear programming, bi-criterion programming, Multi Attribute Decision Making, Compromise Programming, Surrogate Worth Trade-off Method) and various versions of vehicle routing problem (VRP), Multi depot VRP (MDVRP), VRP with time windows (VRPWTW), Stochastic VRP (SVRP), Capacitated VRP (CVRP), Fuzzy VRP (FVRP), Location VRP (LVRP), Backhauling VRP(BHVRP), Facility Location VRP (FLVRP), and Inventory control VRP (ICVRP). Although, VRP is a research area with rich research works and powerful researchers there found only 81 articles that relates various vehicle routing type problems with various multiple objectives techniques. This author found that there is no research done in some areas of VRP (i.e., FVRP, ICVRP, LRP and CVRP). It is interesting to see that this research area was completely an unattractive to master students (with zero research reported) and a somewhat attractive area to doctoral students (with 6 researches reported). Among the many multi criterion programming techniques available only three of them (goal programming, bi-criterion programming, linear and nonlinear multi objective programming) are being employed to solve the problem.

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This work investigates the effect of different inventory policies of a supply chain model using the system dynamics approach which belongs to the class of Vendor Managed Inventory (VMI), automatic pipeline, inventory and order based production control systems (VMI-APIOBPCS). This work helps management to investigate the effect of different policies such as adding the VMI system or third party logistic (TPL) on the whole cost of the supply chain. To this end, this work applies system dynamics in supply chain with two supplier and one retail channel which consists of VMI system. Moreover, this work studies the performance of the proposed model via three metrics: Bullwhip effect; satisfaction of the end-customer; the amount of the whole inventory of chain.

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In this paper, we study the problem of integrated capacitated hub location problem and seat inventory control considering concept and techniques of revenue management. We consider an airline company maximizes its revenue by utilizing the best network topology and providing proper booking limits for all itineraries and fare classes. The transportation system arises in the form of a star/star network and includes both hub-stop and non-stop flights. This problem is formulated as a two-stage stochastic integer program with mixed-integer recourse. We solve various instances carried out from the Turkish network data set. Due to the NP-hardness of the problem, we propose a hybrid optimization method, consisting of an evolutionary algorithm based on genetic algorithm and exact solution. The quality of the solutions found by the proposed meta-heuristic is compared with the original version of GA and the mathematical programming model. The results obtained by the proposed model imply that integrating hub location and seat inventory control problem would help to increase the total revenue of airline companies. Also, in the case of serving non-stop flights, the model can provide more profit by employing less number of hubs.

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Considered supply chain in this article consists of one vendor and multiple retailers where the vendor applies vendor managed inventory. Considering vendor as a leader and retailers as followers, Stackelberg game theory is applied for modeling and analyzing this system. A general mixed integer nonlinear model is developed which can optimizes the performance of the system under revenue sharing contract, wholesale price contract and centralized structure. Based on this model, we numerically analyzed the performance of revenue sharing contract in the considered supply chain and four states for revenue sharing contract are analyzed at the end. Moreover, in each state, performance of the system under revenue sharing contract is compared with the performance of the system under wholesale price contract and centralized structure.