Heuristic Approaches With Reinforced Parameter Tuning for the Car Sequencing Problems With Block Batches

Motivated by the practical supply chain management of the automobile industry, we study the car sequencing problem (CSP) that minimize the conflicts arising from scheduling cars into an assembly line. The CSP is a well established problem, subject to the paint batching constraints to reduce the the costs for color changes and capacity constraints in the assembly shop to level the usage of the options. However, the existing approaches to this problem do not take into account the block batches, which desires a consecutive production batch of cars requiring a certain option. This requirement often occurs when specialized labor time window is short in the customized car production scenario, and renders additional complexities to the traditional car sequencing problem. In this paper, we propose a novel model to deals with these constraints and simultaneously generate the sequencing and replenishment decisions. In addition to our model formulation, we develop two math-heuristic approaches to solve the propose large-scale car sequencing problem. The selected heuristics are based on relax-and-fix procedures, fix-and-optimize procedures and variable neighborhood search. To solve the large-sized instances (commercial solvers, i.e., Cplex, cannot provide a feasible solution within 1 hour), we design and implement a reinforced parameter tuning mechanism to dynamically select the parameter values, so as to speed up the search process. The proposed models and heuristics are tested on compatible instances from the benchmark in the literature (CSPLib), as well as large-sized instances generated from real-world cases. We report on extensive computational experiments, and provide basic managerial insights into the planning process.

Integrating Tier-1 module suppliers in car sequencing problem

<p class="Abstract"><span lang="EN-GB">The objective of this study is to develop a car assembly sequence that is mutually agreed between car manufacturers and Tier-1 module suppliers such that overall modular supply chain efficiency is improved. In the literature so far, only constraints of car manufacturers have been considered in the car sequencing problem. However, an assembly sequence from car manufacturer imposes a module assembly sequence on Tier-1 module suppliers since their assembly activities are synchronous and in sequence with assembly line of that car manufacturer. An imposed assembly sequence defines a certain demand rate for Tier-1 module suppliers and has significant impacts on operational cost of these suppliers which ultimately affects the overall modular supply chain efficiency. In this paper, a heuristic approach has been introduced to generate a supplier cognizant car sequence which does not only provide better operational conditions for Tier-1 module suppliers, but also satisfies constraints of the car manufacturer.</span></p>