An approach to integrate production-transportation planning and scheduling in an aluminium supply chain network

Abstract

This paper is based on a real-life problem of a global aluminium supply chain network driven by an aluminium smelter. At each echelon of the aluminium supply chain network several members are involved which are scattered around the world. Producing aluminium begins with bauxite mining. Next, aluminium oxide is made from bauxite and finally aluminium is produced from aluminium oxide. A novel type of mixed-integer decision-making model, including a timecontinuous representation of the planning period, is presented. The model enables coordination of production quantities and times of all supply chain members in order to minimise production and transportation costs of the whole supply chain minus bonus payments for early deliveries which are stipulated between the supply chain network and its customers. Material flows can take place with or without temporary storage of intermediate products at supplying and/or receiving sites. Furthermore, relax-and-fix heuristics are presented. A number of randomly generated scenarios are presented to demonstrate that the heuristics can find nearly optimal solutions along with drastically reduced computation times. The relax-and-fix heuristic enables iterative planning between centralised and decentralised decision-makers.

An enhanced model for the integrated production and transportation problem in a multiple vehicles environment

“…The objective was to minimize total shipment cost while producing all the orders and satisfying the production capacity constraints. Steinrücke (2011) considered a three supply chain stages and multiple global production sites for an aluminum smelter involving production cost, transportation cost, and bonus payments for earlier deliveries to final customers. In the research, relax-andfix (RF) heuristics was developed and applied for obtaining near optimal feasible solution within a reasonable computation time.…”

A Hybrid Approach to Quantitative Software Project Scheduling within Agile Frameworks

“…The corresponding planning methods have developed over many decades. As a result, there are efficient operational research methods and models available (Steinrücke, ; Steinrücke & Jahr, ), which can be applied to generate, for example, effective production plans. Compared with traditional industries (e.g., metal working and automotive), the IT industry is a younger industry.…”

Preemptive scheduling in a two-stage supply chain to minimize the makespan

“…[1,7,9,10,22,27]), heuristic (see, e.g. [11,[24][25][26]), and exact (see, e.g. [4,12,18,19]) algorithms.…”