Intermodal freight transport consists of using different modes without changing the load unit. This results in a significant reduction time that goods spend at intermodal terminals, where transshipment takes place. Drayage refers to on trucks among depots, customers and suppliers. In spite fact drayage only represents between 5 10 percent total distance, it may amount up more than 30 costs. The...

Considering the vehicle routing problem with fuzzy demand and time windows, a optimization method is proposed considering both soft windows uncertain customer demand. First, chance-constrained programming model established based on credibility theory, minimizing total logistics cost. At same time, random simulation algorithm designed to calculate penalty cost of delivery failures caused by that...

The vehicle routing problem with backhauls (VRPB) as an extension of the classical vehicle routing prob-lem (VRP) attempts to define a set of routes which services both linehaul customers whom product are to be delivered and backhaul customers whom goods need to be collected. A primary objective for the problem usually is minimizing the total distribution cost. Most real-life problems have othe...

In this paper, we introduce a model  to optimization of milk run system that is one of VRP problem with time window and uncertainty in inventory. This approach led to the routes with minimum cost of transportation while satisfying all inventory in a given bounded set of uncertainty .The problem is formulated as a robust optimization problem. Since the resulted problem illustrates that grows up ...

Abstract This paper studies a generalization of the shortest path tour problem with time windows ( GSPTPTW ). The aim is to find single-origin single-destination path, which has pass through an ordered sequence not necessarily disjoint node-subsets. Each node window for each node-subset it belongs. We investigate theoretical properties and propose dynamic programming approach solve it. Numerica...

Summary Lag windows are commonly used in time series analysis, econometrics, steady-state simulation and Markov chain Monte Carlo to estimate time-average covariance matrices. In the presence of positive correlation underlying process, estimators this matrix almost always exhibit significant negative bias, leading undesirable finite-sample properties. We propose a new family lag specifically de...