Heuristics and meta-heuristics for lot sizing and scheduling in the soft drinks industry: A comparison study

This chapter studies a two-level production planning problem where, on each level, a lot sizing and scheduling problem with parallel machines, capacity constraints and sequence-dependent setup costs and times must be solved. The problem can be found in soft drink companies where the production process involves two interdependent levels with decisions concerning raw material storage and soft drink bottling. Models and solution approaches proposed so far are surveyed and conceptually compared. Two different approaches have been selected to perform a series of computational comparisons: an evolutionary technique comprising a genetic algorithm and its memetic version, and a decomposition and relaxation approach. © 2008 Springer-Verlag Berlin Heidelberg.

A genetic algorithm/mathematical programming approach to solve a two-level soft drink production problem

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Sheeting efficiency improvement through production planning and control development.

Arkitus on kartongin jatkojalostusmuoto, jonka tehokkuus muodostuu monen tekijän vaikutuksesta. Tämän työn tavoitteena oli parantaa arkitustehokkuutta tutkitussa kahden folioleikkurin arkittamossa tuotannonsuunnittelun ja tuotannonohjauksen kehittämisellä. Kartonkitehtaan sisäisessä jalostusketjussa arkitus on viimeinen vaihe, mikä tekee siitä pitkälti riippuvaisen edeltävistä konevaiheista, eli kartonkikoneista ja PE-päällystyskoneista. Pelkkä arkituksen tuotannonsuunnittelun huomiointi ei siis vielä takaa hyvää lopputulosta arkitustehokkuuden kannalta. Folioarkitustoiminta on hyvin asiakassuuntautunutta. Arkkikoot määräytyvät asiakkaiden omien tarpeiden perusteella, jolloin eri arkkikokojen kokonaismäärä kasvaa huomattavan suureksi. Viime vuosien trendinä on ollut tilauseräkokojen pieneneminen. Näiden tekijöiden yhteisvaikutuksena arkituksen tuotantoprosessille on ominaista erilaisten asetusten aiheuttama katkonaisuus. Lisäksi pelkästään yhden millimetrin muutos arkin leveydessä voi usein vaikuttaa arkitustehokkuuteen hyvinkin merkittävästi. Näistä syistä arkituksen tuotannonsuunnittelun apuvälineeksi tarvitaan tarkkuuteen ja joustavuuteen kykenevää tietojärjestelmää. Tehokkaan tuotannonohjauksen tueksi tarvitaan lisäksi erilaisia leikkuri- ja kartonkilaatukohtaisia raportteja. Työn teoriaosassa käsitellään tarkemmin arkitustoiminnan ominaisuuksia ja sen tehokkuuteen vaikuttavia tekijöitä. Lisäksi käsitellään tuotannonsuunnittelun ja tuotannonohjauksen periaatteita ja toimintoja.

Multi-population genetic algorithm to solve the synchronized and integrated two-level lot sizing and scheduling problem

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

A production planning system for plastic footwear in a seasonal market

Modern injection-moulding machinery which produces several, pairs of plastic footwear at a time brought increased production planning problems to a factory. The demand for its footwear is seasonal but the company's manning policy keeps a fairly constant production level thus determining the aggregate stock. Production planning must therefore be done within the limitations of a specified total stock. The thesis proposes a new production planning system with four subsystems. These are sales forecasting, resource planning, and two levels of production scheduling: (a) aggregate decisions concerning the 'manufacturing group' (group of products) to be produced in each machine each week, and (b) detailed decisions concerning the products within a manufacturing group to be scheduled into each mould-place. The detailed scheduling is least dependent on improvements elsewhere so the sub-systems were tackled in reverse order. The thesis concentrates on the production scheduling sub-systems which will provide most. of the benefits. The aggregate scheduling solution depends principally on the aggregate stocks of each manufacturing group and their division into 'safety stocks' (to prevent shortages) and 'freestocks' (to permit batch production). The problem is too complex for exact solution but a good heuristic solution, which has yet to be implemented, is provided by minimising graphically immediate plus expected future costs. The detailed problem splits into determining the optimal safety stocks and batch quantities given the appropriate aggregate stocks. It.is found that the optimal safety stocks are proportional to the demand. The ideal batch quantities are based on a modified, formula for the Economic Batch Quantity and the product schedule is created week by week using a priority system which schedules to minimise expected future costs. This algorithm performs almost optimally. The detailed scheduling solution was implemented and achieved the target savings for the whole project in favourable circumstances. Future plans include full implementation.

Stable and high-level production of recombinant Factor IX in human hepatic cell line

Hemophilia B is a genetic disease of the coagulation system that affects one in 30,000 males worldwide. Recombinant human Factor IX (rhFIX) has been used for hemophilia B treatment, but the amount of active protein generated by these systems is inefficient, resulting in a high-cost production of rhFIX. In this study, we developed an alternative for rhFIX production. We used a retrovirus system to obtain two recombinant cell lines. We first tested rhFIX production in the human embryonic kidney 293 cells (293). Next, we tested a hepatic cell line (HepG2) because FIX is primarily expressed in the liver. Our results reveal that intracellular rhFIX expression was more efficient in HepG2/rhFIX (46%) than in 293/rhFIX (21%). The activated partial thromboplastin time test showed that HepG2/rhFIX expressed biologically active rhFIX 1.5 times higher than 293/rhFIX (P = 0.016). Recovery of rhFIX from the HepG2 by reversed-phase chromatography was straightforward. We found that rhFIX has a pharmacokinetic profile similar to that of FIX purified from human plasma when tested in hemophilic B model. HepG2/rhFIX cell line produced the highest levels of rhFIX, representing an efficient in vitro expression system. This work opens up the possibility of significantly reducing the costs of rhFIX production, with implications for expanding hemophilia B treatment in developing countries.

Production planning and optimization of a pulp mill: introduction of the optimisation based scheduling software for pulp industry

The objective of this project was to introduce a new software product to pulp industry, a new market for case company. An optimization based scheduling tool has been developed to allow pulp operations to better control their production processes and improve both production efficiency and stability. Both the work here and earlier research indicates that there is a potential for savings around 1-5%. All the supporting data is available today coming from distributed control systems, data historians and other existing sources. The pulp mill model together with the scheduler, allows what-if analyses of the impacts and timely feasibility of various external actions such as planned maintenance of any particular mill operation. The visibility gained from the model proves also to be a real benefit. The aim is to satisfy demand and gain extra profit, while achieving the required customer service level. Research effort has been put both in understanding the minimum features needed to satisfy the scheduling requirements in the industry and the overall existence of the market. A qualitative study was constructed to both identify competitive situation and the requirements vs. gaps on the market. It becomes clear that there is no such system on the marketplace today and also that there is room to improve target market overall process efficiency through such planning tool. This thesis also provides better overall understanding of the different processes in this particular industry for the case company.

Infeasibility handling in genetic algorithm using nested domains for production planning

In this paper we present a genetic algorithm with new components to tackle capacitated lot sizing and scheduling problems with sequence dependent setups that appear in a wide range of industries, from soft drink bottling to food manufacturing. Finding a feasible solution to highly constrained problems is often a very difficult task. Various strategies have been applied to deal with infeasible solutions throughout the search. We propose a new scheme of classifying individuals based on nested domains to determine the solutions according to the level of infeasibility, which in our case represents bands of additional production hours (overtime). Within each band, individuals are just differentiated by their fitness function. As iterations are conducted, the widths of the bands are dynamically adjusted to improve the convergence of the individuals into the feasible domain. The numerical experiments on highly capacitated instances show the effectiveness of this computational tractable approach to guide the search toward the feasible domain. Our approach outperforms other state-of-the-art approaches and commercial solvers. (C) 2009 Elsevier Ltd. All rights reserved.

A linear optimization approach to the combined production planning model

Two fundamental processes usually arise in the production planning of many industries. The first one consists of deciding how many final products of each type have to be produced in each period of a planning horizon, the well-known lot sizing problem. The other process consists of cutting raw materials in stock in order to produce smaller parts used in the assembly of final products, the well-studied cutting stock problem. In this paper the decision variables of these two problems are dependent of each other in order to obtain a global optimum solution. Setups that are typically present in lot sizing problems are relaxed together with integer frequencies of cutting patterns in the cutting problem. Therefore, a large scale linear optimizations problem arises, which is exactly solved by a column generated technique. It is worth noting that this new combined problem still takes the trade-off between storage costs (for final products and the parts) and trim losses (in the cutting process). We present some sets of computational tests, analyzed over three different scenarios. These results show that, by combining the problems and using an exact method, it is possible to obtain significant gains when compared to the usual industrial practice, which solve them in sequence. (C) 2010 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.

A linear optimization approach to the combined production planning model

Two fundamental processes usually arise in the production planning of many industries. The first one consists of deciding how many final products of each type have to be produced in each period of a planning horizon, the well-known lot sizing problem. The other process consists of cutting raw materials in stock in order to produce smaller parts used in the assembly of final products, the well-studied cutting stock problem. In this paper the decision variables of these two problems are dependent of each other in order to obtain a global optimum solution. Setups that are typically present in lot sizing problems are relaxed together with integer frequencies of cutting patterns in the cutting problem. Therefore, a large scale linear optimizations problem arises, which is exactly solved by a column generated technique. It is worth noting that this new combined problem still takes the trade-off between storage costs (for final products and the parts) and trim losses (in the cutting process). We present some sets of computational tests, analyzed over three different scenarios. These results show that, by combining the problems and using an exact method, it is possible to obtain significant gains when compared to the usual industrial practice, which solve them in sequence. (C) 2010 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.

Tabu search to solve the Synchronized and Integrated Two-Level Lot Sizing and Scheduling Problem

This paper proposes a tabu search approach to solve the Synchronized and Integrated Two-Level Lot Sizing and Scheduling Problem (SITLSP). It is a real-world problem, often found in soft drink companies, where the production process has two integrated levels with decisions concerning raw material storage and soft drink bottling. Lot sizing and scheduling of raw materials in tanks and products in bottling lines must be simultaneously determined. Real data provided by a soft drink company is used to make comparisons with a previous genetic algorithm. Computational results have demonstrated that tabu search outperformed genetic algorithm in all instances. Copyright 2011 ACM.

A Study of Different Subsequence Elimination Strategies for the Soft Drink Production Planning

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

A knapsack problem as a tool to solve the production planning problem in small foundries

According to recent research carried out in the foundry sector, one of the most important concerns of the industries is to improve their production planning. A foundry production plan involves two dependent stages: (1) determining the alloys to be merged and (2) determining the lots that will be produced. The purpose of this study is to draw up plans of minimum production cost for the lot-sizing problem for small foundries. As suggested in the literature, the proposed heuristic addresses the problem stages in a hierarchical way. Firstly, the alloys are determined and, subsequently, the items that are produced from them. In this study, a knapsack problem as a tool to determine the items to be produced from furnace loading was proposed. Moreover, we proposed a genetic algorithm to explore some possible sets of alloys and to determine the production planning for a small foundry. Our method attempts to overcome the difficulties in finding good production planning presented by the method proposed in the literature. The computational experiments show that the proposed methods presented better results than the literature. Furthermore, the proposed methods do not need commercial software, which is favorable for small foundries. (C) 2010 Elsevier Ltd. All rights reserved.

An approach to the development of expert systems within production planning and control

The thesis presents an account of an attempt to utilize expert systems within the domain of production planning and control. The use of expert systems was proposed due to the problematical nature of a particular function within British Steel Strip Products' Operations Department: the function of Order Allocation, allocating customer orders to a production week and site. Approaches to tackling problems within production planning and control are reviewed, as are the general capabilities of expert systems. The conclusions drawn are that the domain of production planning and control contains both `soft' and `hard' problems, and that while expert systems appear to be a useful technology for this domain, this usefulness has by no means yet been demonstrated. Also, it is argued that the main stream methodology for developing expert systems is unsuited for the domain. A problem-driven approach is developed and used to tackle the Order Allocation function. The resulting system, UAAMS, contained two expert components. One of these, the scheduling procedure was not fully implemented due to inadequate software. The second expert component, the product routing procedure, was untroubled by such difficulties, though it was unusable on its own; thus a second system was developed. This system, MICRO-X10, duplicated the function of X10, a complex database query routine used daily by Order Allocation. A prototype version of MICRO-X10 proved too slow to be useful but allowed implementation and maintenance issues to be analysed. In conclusion, the usefulness of the problem-driven approach to expert systems development within production planning and control is demonstrated but restrictions imposed by current expert system software are highlighted in that the abilities of such software to cope with `hard' scheduling constructs and also the slow processing speeds of such software can restrict the current usefulness of expert systems within production planning and control.

Exploring demand and production planning challenges in the food processing industry:a case study

This paper explores demand and production management challenges in the food processing industry. The goal is to identify the main production planning constraints and secondly to explore how each of these constraints affects company’s performance in terms of costs and customer service level. A single case study methodology was preferred since it enabled the collection of in-depth data. Findings suggest that product shelf life, carcass utilization and production lead time are the main constraints affecting supply chain efficiency and hence, a single planning approach is not appropriate when different products have different technological and processing characteristics.