Modeling multiple stage manufacturing systems with generalized costs and capacity issues

Abstract

This study introduces one modeling methodology that describes a broad range of multiple stage production planning issues, including multiple limited resources with setup times and joint fixed cost relationships. An existing production system is modeled in this fashion, creating a new set of 1350 highly generalized benchmark problems. A computational study is conducted with the 1350 benchmark problems introduced in this paper and 2100 benchmark problems, with more restrictive assumptions, from the existing literature. The relative merits of a decomposition-based algorithm and a neighborhood search technique known as NIPPA, or the Non-sequential Incremental Part Period Algorithm, are assessed. NIPPA is generally the more successful of the two techniques, although there are specific instances in which the decomposition-based algorithm displayed a distinct advantage.

A heuristic approach for big bucket multi-level production planning problems

“…• MULTI-LSB instances: We have generated 4 sets of test problems based on the problem described in the paper of Simpson and Erenguc [2005], each set having 30 instances with low, medium and high variability of demand. From now on, we will call these sets SET1, SET2, SET3, and SET4.…”

“…Note that our approach also uses relax-and-fix idea. 4) Local search: A good example is the neighborhood search heuristic of Simpson and Erenguc [2005].…”

An optimization framework for solving capacitated multi-level lot-sizing problems with backlogging

“…The third group of test data sets we used was generated by Simpson and Erenguc (2005) and Akartunalı and Miller (2009). These data sets include sets SET1, SET2, SET3, and SET4, each set having 30 instances with low, medium and high variability of demand.…”

“…All instances have 78 items and have an assembly structure, and backlogging is allowed in the last period. For more details about the instances, see Simpson and Erenguc (2005) and Akartunalı and Miller (2009). …”

“…Tang (2004) provided a brief presentation of simulated annealing techniques and their applications in lot-sizing problems. Simpson and Erenguc (2005) developed a neighborhood search heuristic method for capacitated multi-stage problems. Karimi et al (2006) proposed a tabu search heuristic for the capacitated lot-sizing problem with setup carryover.…”