As a result of widespread and effective usage of internet, firms tend to collaborate to reduce their operating costs. This thesis analyzes collaboration opportunities for a group of small shippers. A transportation intermediary determining the optimal actions for arriving shippers and a mechanism allocating savings to the shippers is proposed in the thesis. The performance of the intermediary is assessed by using computational analyses. An experimental set is formed that is by changing the parameters that are expected to significantly affect the optimal policy structure and the surplus budget (or deficit) changes. It is seen that increasing variable costs like cross-assignment cost and waiting cost leads to the increase in comparative performance of the optimal policy compared to the na&iuml / ve policy, which is defined according to a simple rule, although increasing dispatching cost, which can be considered as a fixed cost, leads to an opposite result. The performance of the optimal policy is also assessed by using a myopic policy, in which shippers are trying to maximize their own benefit without considering the overall benefit of the grand coalition.

We consider a one-warehouse multi-retailer system where the warehouse orders or receives from its supplier and replenishes multiple retailers with direct shipping or multi-stop routing over a finite time horizon. The warehouse has the knowledge of external (deterministic) demands at the retailers and manages their inventories while ensuring no stock-out. We consider two problems with direct shipping policy and two problems with routing policy. For the direct shipping policy, the problem is to determine the optimal replenishments for the warehouse and retailers such that the system-wide costs are minimized. In one problem, the warehouse decides about how much and when to ship to the retailers while in the other problem, inventory level of the retailer has to be raised up to a predetermined level whenever replenished. We propose strong mixed integer programming formulations for these problems. Computational experiments show that our formulations are better than their competitors and are very successful in solving the problems to optimality. For the routing policy, the problem is to decide on when and in what sequence to visit the retailers and how much to ship to a retailer so as to minimize system-wide costs. In one problem, the warehouse receives given amounts from its supplier while in the other the warehouse decides on its own replenishments. We propose branch-and-cut algorithms and heuristics based on strong formulations for both problems. Computational results reveal that our procedures perform better than their competitors in the literature for both problems.