Mixed Integer Linear Programming Scheduling in the Food Industry

Doganis, Philip; Sarimveis, Haralambos

doi:10.1201/9781420061420.ch16

Cited by 10 publications

(7 citation statements)

References 29 publications

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“…Most important is the inclusion of additional features in the EMSP formulation often found in practical applications (e.g. Doganis and Sarimveis 2008) and the development of fast algorithms for these extended EMSP versions. First, the processing time of each job may be considered as a function of its manning (or its manning efficiency), which would makes it possible to accelerate certain jobs by allocating additional or more efficient (e.g.…”

Section: Discussionmentioning

confidence: 99%

Efficient greedy algorithms for economic manpower shift planning

Nearchou

Giannikos

Lagodimos

2014

Engineering Optimization

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Consideration is given to the economic manpower shift planning (EMSP) problem, an NP-hard capacity planning problem appearing in various industrial settings including the packing stage of production in process industries and maintenance operations. EMSP aims to determine the manpower needed in each available workday shift of a given planning horizon so as to complete a set of independent jobs at minimum cost. Three greedy heuristics are presented for the EMSP solution. These practically constitute adaptations of an existing algorithm for a simplified version of EMSP which had shown excellent performance in terms of solution quality and speed. Experimentation shows that the new algorithms perform very well in comparison to the results obtained by both the CPLEX optimizer and an existing metaheuristic. Statistical analysis is deployed to rank the algorithms in terms of their solution quality and to identify the effects that critical planning factors may have on their relative efficiency.

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Section: Discussionmentioning

confidence: 99%

Efficient greedy algorithms for economic manpower shift planning

Nearchou

Giannikos

Lagodimos

2014

Engineering Optimization

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“…Marinelli et al [26] modeled parallel packaging machines with buffers as an CLSP with sequence independent set up time and cost, then, applied two-stage optimization decomposition approach. Doganis and Sarimveis [11] proposed an MILP scheduling model for a single machine packaging line with sequence dependent set up time and cost, consequently, they extended their model in another paper [12] for multiple paralleled machines, also they supplemented their model by considering shelf life related cost in the objective function and presented a new model in [13]. Kopanos et al [19] modeled fermentation and packaging line together with considering families of products and sequence dependent set up time and cost.…”

Section: Production Planning and Scheduling In Perishable Food Supplymentioning

confidence: 99%

General lot-sizing and scheduling for perishable food products

et al. 2020

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General lot-sizing and scheduling is a well-studied problem in the literature, but for perishable or time-sensitive products is less investigated. Also, most of studies on perishable product supply chains focus on strategic and tactical decision levels rather than operational decision level and integrated operational and tactical decision levels. We focus on a general lot-sizing and scheduling problem faced by perishable food products. The lifespan and shelf life are two important key features of perishable products that are considered in the problem. This problem can be described as a multi-product, multi-parallel line, multi-period general lot-sizing and scheduling problem with sequence dependent change over time. The objective function is sum of production costs, inventory holding costs, waste costs, and lifespan related cost function. We apply two mixed-integer programming based heuristics to solve generated instances. The heuristics are compared in terms of solution quality and computational time. Also, the sensitivity analysis is presented to analyze the effects of parameters' changes.Mathematics Subject Classification. 90B30, 90C11, 90C59.

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“…MILP models have frequently been used to solve optimization problems in the food processing industry. Doganis and Sarimveis (2008a) developed an MILP model for a yogurt processing facility, with five cost objective functions (setup, the storage, machine utilization, 6 labor overtime, and the freshness of products) and constraints for daily production limit, machine/product assignment, process time window, and sequence dependent processing. The authors have also demonstrated that a similar approach can be applied to optimize combined makespan and costs function objectives (changeover, inventory, machine utilization, and overtime) Sarimveis 2008b, Doganis andSarimveis 2007).…”

Section: Introductionmentioning

confidence: 99%

Multi-week MILP scheduling for an ice cream processing facility

Wari

Zhu

2016

Computers & Chemical Engineering

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This paper presents a multi-week mixed integer linear programming (MILP) scheduling model for an ice cream processing facility. The ice cream processing is a typical complex food manufacturing process and a simplified version of this processing has been adapted to investigate scheduling problems in the literature. Most of these models only considered the production scheduling for a week. In this paper, multi-week production scheduling is considered. The problem has been implemented as an MILP model. The model has been tested on a set of cases from the literature, and its results were compared to the results of problems solved using hybrid MILP-heuristics methods in the literature. The inclusion of clean-up session, weekend break and semi-processed product from previous week were also assessed with two additional sets of experiments. The experiments result show that the proposed MILP is able to handle multi-week scheduling efficiently and effectively within a reasonable time limit.

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Mixed Integer Linear Programming Scheduling in the Food Industry

Cited by 10 publications

References 29 publications

Efficient greedy algorithms for economic manpower shift planning

Efficient greedy algorithms for economic manpower shift planning

General lot-sizing and scheduling for perishable food products

Multi-week MILP scheduling for an ice cream processing facility

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