Simultaneous production and distribution of industrial gas supply-chains

Abstract

In this paper, we propose a multi-period mixed-integer linear programming model for optimal enterpriselevel planning of industrial gas operations. The objective is to minimize the total cost of production and distribution of liquid products by coordinating production decisions at multiple plants and distribution decisions at multiple depots. Production decisions include production modes and rates that determine power consumption. Distribution decisions involve source, destination, quantity, route, and time of each truck delivery. The selection of routes is a critical factor of the distribution cost. The main goal of this contribution is to assess the benefits of optimal coordination of production and distribution. The proposed methodology has been tested on small, medium, and large size examples. The results show that significant benefits can be obtained with higher coordination among plants/depots in order to fulfill a common set of shared customer demands. The application to real industrial size test cases is also discussed.

Enterprise-wide optimization for industrial demand side management: Fundamentals, advances, and perspectives

“…In order to solve large instances of the problem, an iterative MILP-based heuristic approach is proposed, which solves the integrated MILP model with a restricted set of candidate routes at each iteration and dynamically updates the set of candidate routes for the next iteration. The results of an extensive computational study show that the proposed algorithm finds high-quality solutions in reasonable computation times, and in large instances, it significantly outperforms a standard two-phase heuristic approach and a solution strategy involving a one-time heuristic pre-generation of candidate routes similar to the one proposed by Marchetti et al (2014). By applying the multiscale framework, the authors solve an industrial test case that considers a real-world industrial gas supply chain with 2 plants, approximately 240 customers, 20 vehicles, and a planning horizon of 4 weeks.…”

“…Moreover, the impact of different site-specific electricity prices has to be taken into account. Marchetti et al (2014) consider the simultaneous optimization of production and distribution operations in power-intensive industrial gas supply chains. The proposed integrated model includes prespecified routes that can be assigned to available trucks for the transportation of liquid products.…”

“…Acknowledging the restrictions of the model proposed by Marchetti et al (2014), Zhang et al (2016f) develop a multiscale production routing framework involving two time grids, a fine one for production scheduling and a coarse one for distribution planning. In order to solve large instances of the problem, an iterative MILP-based heuristic approach is proposed, which solves the integrated MILP model with a restricted set of candidate routes at each iteration and dynamically updates the set of candidate routes for the next iteration.…”

An incremental approach using local-search heuristic for inventory routing problem in industrial gases

“…More recent research papers that deal with optimal distribution of industrial gases supply-chains are by You et al (2011), Benoist et al (2011), Ellis et al (2014 and Marchetti et al (2014). You et al (2011) focus on strategic decisions with long-term planning horizon using decomposition and continuous approximation approaches.…”

“…Similarly, Ellis et al (2014) optimize the strategic-level decision of allocating bulk gas tanks to customer sites. Marchetti et al (2014) assess the benefits of optimal coordination of production and distribution in industrial gas supply-chains. Benoist et al (2011) propose a method to solve a real-life IRP for operational scheduling using a randomized local-search heuristic for short-term planning horizon.…”