This paper deals with the permutation flowshop scheduling problem with time lags constraints to minimize the total weighted tardiness criterion by using the Branch and Bound algorithm. A new lower bound was developed for the flowshop scheduling problem. The computational experiments indicate that the proposed algorithm provides good solution in terms of quality and time requirements.

The principal focus of this research effort is to investigate a maritime stochastic transportation problem. In this case, crude oil shipments are to be transported from multiple sources to multiple destinations. The demand at the destinations is normally distributed and the violation of certain specified lower and upper daily storage limits can lead to various types of penalties. We aim to utilize (stochastic) mathematical programming approaches to minimize the overall cost of such fleet operation by optimizing the vessel schedules and maintaining acceptable daily storage levels considering the stochastic demand structures. This research effort signifies that the nature of daily demand distributions in the multiple sources-destinations scheduling-inventory scenario significantly impacts the overall fleet schedules and the total expected cost. Therefore, it is crucial to grasp essential stochastic aspects of the daily demands to avoid potential misrepresentation of the operational costs. The robustness of the adopted approach is illustrated by presenting computational results that are based on a wide range of test problems. Moreover, our computational study also examines the impact of variations in demand and the probability of meeting demands on the cost structures.

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Abstract. In this paper, we study a variant of the survivable network design problem, that is the survivable network design problem with labels (colors) on the edges. In particular, we address the Generalized Labeled Two Edge Connected Subgraph Problem (GLTECSP) that has many applications in telecommunication and transportation. Given a connected undirected graph G such that with each edge is associated a set of labels (colors), the GLTECSP consists in finding a two-edge connected spanning subgraph of G with a minimum number of distinct labels. We propose two Integer Programming (IP) formulations for the problem, a natural formulation using cuts on the edges, and a compact formulation using color-cuts. We devise Branch-and-Cut algorithms to solve both formulations and compare them on sets of randomly generated instances. Computational results show that the compact formulation outperforms the natural one regarding the linear relaxation and the computational time. Moreover, the compact formulation is able to solve to optimality several instances left unsolved within the time limit by the natural formulation.

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