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5 pages, 190 KiB

Open AccessEditorial

Planning and Scheduling Optimization

by Yassine Ouazene, Taha Arbaoui and Farouk Yalaoui

Appl. Sci. 2021, 11(19), 8980; https://doi.org/10.3390/app11198980 - 27 Sep 2021

Cited by 1 | Viewed by 1803

Abstract

Optimizing the performance of services and industrial systems is a real lever for creating value for companies and society [...] Full article

(This article belongs to the Special Issue Planning and Scheduling Optimization)

Research

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15 pages, 358 KiB

Open AccessArticle

A Simulated Annealing Algorithm for Intermodal Transportation on Incomplete Networks

by Mustapha Oudani

Appl. Sci. 2021, 11(10), 4467; https://doi.org/10.3390/app11104467 - 14 May 2021

Cited by 17 | Viewed by 3053

Abstract

Growing competition in the world enforces the need for an efficient design of transportation networks. Furthermore, a competitive transportation network should also be eco-friendly. As road transportation is responsible for the largest quantities of CO

_{2}

emissions, Intermodal Transportation (IT) might be a [...] Read more.

Growing competition in the world enforces the need for an efficient design of transportation networks. Furthermore, a competitive transportation network should also be eco-friendly. As road transportation is responsible for the largest quantities of CO

_{2}

emissions, Intermodal Transportation (IT) might be a potential alternative. From this perspective, intermodal terminals location is a cornerstone for building a sustainable transportation network. The purpose of this paper is to study and efficiently solve the Intermodal Terminal Location Problem on incomplete networks. We model this problem as a mixed integer linear program and develop a simulated annealing algorithm to tackle medium and large instances. The computational results show that the obtained solutions using simulated annealing are competitive and close to the exact solutions found by CPLEX solver for small and medium instances. The same developed algorithm outperforms the best found solutions from the literature using heuristics for larger instances. Full article

(This article belongs to the Special Issue Planning and Scheduling Optimization)

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15 pages, 587 KiB

Open AccessArticle

Workload Balancing on Identical Parallel Machines: Theoretical and Computational Analysis

by Yassine Ouazene, Nhan-Quy Nguyen and Farouk Yalaoui

Appl. Sci. 2021, 11(8), 3677; https://doi.org/10.3390/app11083677 - 19 Apr 2021

Cited by 11 | Viewed by 2430

Abstract

This paper considers the problem of assigning nonpreemptive jobs on identical parallel machines to optimize workload balancing criteria. Since workload balancing is an important practical issue for services and production systems to ensure an efficient use of resources, different measures of performance have [...] Read more.

This paper considers the problem of assigning nonpreemptive jobs on identical parallel machines to optimize workload balancing criteria. Since workload balancing is an important practical issue for services and production systems to ensure an efficient use of resources, different measures of performance have been considered in the scheduling literature to characterize this problem: maximum completion time, difference between maximum and minimum completion times and the Normalized Sum of Square for Workload Deviations. In this study, we propose a theoretical and computational analysis of these criteria. First, we prove that these criteria are equivalent in the case of identical jobs and in some particular cases. Then, we study the general version of the problem using jobs requiring different processing times and establish the theoretical relationship between the aforementioned criteria. Based on these theoretical developments, we propose new mathematical formulations to provide optimal solutions to some unsolved instances in order to enhance the latest benchmark presented in the literature. Full article

(This article belongs to the Special Issue Planning and Scheduling Optimization)

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17 pages, 1014 KiB

Open AccessArticle

Randomized and Generated Instances Fitting with the Home Health Care Problem Subjected to Certain Constraints

by Colin Huvent, Caroline Gagné and Aymen Sioud

Appl. Sci. 2021, 11(8), 3346; https://doi.org/10.3390/app11083346 - 8 Apr 2021

Cited by 2 | Viewed by 2013

Abstract

Home Health Care (HHC) is a worldwide issue. It focuses on how medical and social organizations of different countries handle providing patients with health support at home. In most developed countries, reducing hospital cost constitutes a main objective. It is important to research [...] Read more.

Home Health Care (HHC) is a worldwide issue. It focuses on how medical and social organizations of different countries handle providing patients with health support at home. In most developed countries, reducing hospital cost constitutes a main objective. It is important to research the improvement of HHC logistics. This paper addressed the generation and development of a benchmark properly fitting different constraints of the HCC problem. Consequently, a generator was proposed dealing with all kinds of constraints such as time window constraints, workload constraints, synchronization, and precedence constraints. This generator allows researchers to validate and compare solving methods on a common dataset regardless of confidentiality issues. We validated our generator by firstly creating a common benchmark available for researchers and secondly by proposing a set of instances and a solving method based on an HHC problem found in the literature. Full article

(This article belongs to the Special Issue Planning and Scheduling Optimization)

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24 pages, 1739 KiB

Open AccessArticle

Multi-Criteria Optimization in Operations Scheduling Applying Selected Priority Rules

by Zuzana Červeňanská, Pavel Važan, Martin Juhás and Bohuslava Juhásová

Appl. Sci. 2021, 11(6), 2783; https://doi.org/10.3390/app11062783 - 19 Mar 2021

Cited by 16 | Viewed by 3730

Abstract

The utilization of a specific priority rule in scheduling operations in flexible job shop systems strongly influences production goals. In a context of production control in real practice, production performance indicators are evaluated always en bloc. This paper addresses the multi-criteria evaluating five [...] Read more.

The utilization of a specific priority rule in scheduling operations in flexible job shop systems strongly influences production goals. In a context of production control in real practice, production performance indicators are evaluated always en bloc. This paper addresses the multi-criteria evaluating five selected conflicting production objectives via scalar simulation-based optimization related to applied priority rule. It is connected to the discrete-event simulation model of a flexible job shop system with partially interchangeable workplaces, and it investigates the impact of three selected priority rules—FIFO (First In First Out), EDD (Earliest Due Date), and STR (Slack Time Remaining). In the definition of the multi-criteria objective function, two scalarization methods—Weighted Sum Method and Weighted Product Method—are employed in the optimization model. According to the observations, EDD and STR priority rules outperformed the FIFO rule regardless of the type of applied multi-criteria method for the investigated flexible job shop system. The results of the optimization experiments also indicate that the evaluation via applying multi-criteria optimization is relevant for identifying effective solutions in the design space when the specific priority rule is applied in the scheduling operations. Full article

(This article belongs to the Special Issue Planning and Scheduling Optimization)

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17 pages, 3708 KiB

Open AccessArticle

Performance Comparison between Particle Swarm Optimization and Differential Evolution Algorithms for Postman Delivery Routing Problem

by Warisa Wisittipanich, Khamphe Phoungthong, Chanin Srisuwannapa, Adirek Baisukhan and Nuttachat Wisittipanit

Appl. Sci. 2021, 11(6), 2703; https://doi.org/10.3390/app11062703 - 17 Mar 2021

Cited by 10 | Viewed by 3024

Abstract

Generally, transportation costs account for approximately half of the total operation expenses of a logistics firm. Therefore, any effort to optimize the planning of vehicle routing would be substantially beneficial to the company. This study focuses on a postman delivery routing problem of [...] Read more.

Generally, transportation costs account for approximately half of the total operation expenses of a logistics firm. Therefore, any effort to optimize the planning of vehicle routing would be substantially beneficial to the company. This study focuses on a postman delivery routing problem of the Chiang Rai post office, located in the Chiang Rai province of Thailand. In this study, two metaheuristic methods—particle swarm optimization (PSO) and differential evolution (DE)—were applied with particular solution representation to find delivery routings with minimum travel distances. The performances of PSO and DE were compared along with those from current practices. The results showed that PSO and DE clearly outperformed the actual routing of the current practices in all the operational days examined. Moreover, DE performances were notably superior to those of PSO. Full article

(This article belongs to the Special Issue Planning and Scheduling Optimization)

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22 pages, 5279 KiB

Open AccessArticle

A Genetic Crow Search Algorithm for Optimization of Operation Sequencing in Process Planning

by Mica Djurdjev, Robert Cep, Dejan Lukic, Aco Antic, Branislav Popovic and Mijodrag Milosevic

Appl. Sci. 2021, 11(5), 1981; https://doi.org/10.3390/app11051981 - 24 Feb 2021

Cited by 13 | Viewed by 2926

Abstract

Computer-aided process planning represents the main link between computer-aided design and computer-aided manufacturing. One of the crucial tasks in computer-aided process planning is an operation sequencing problem. In order to find the optimal process plan, operation sequencing problem is formulated as an NP [...] Read more.

Computer-aided process planning represents the main link between computer-aided design and computer-aided manufacturing. One of the crucial tasks in computer-aided process planning is an operation sequencing problem. In order to find the optimal process plan, operation sequencing problem is formulated as an NP hard combinatorial problem. To solve this problem, a novel genetic crow search approach (GCSA) is proposed in this paper. The traditional CSA is improved by employing genetic strategies such as tournament selection, three-string crossover, shift and resource mutation. Moreover, adaptive crossover and mutation probability coefficients were introduced to improve local and global search abilities of the GCSA. Operation precedence graph is adopted to represent precedence relationships among features and vector representation is used to manipulate the data in the Matlab environment. A new nearest mechanism strategy is added to ensure that elements of machines, tools and tool approach direction (TAD) vectors are integer values. Repair strategy to handle precedence constraints is adopted after initialization and shift mutation steps. Minimization of total production cost is used as the optimization criterion to evaluate process plans. To verify the performance of the GCSA, two case studies with different dimensions are carried out and comparisons with traditional and some modern algorithms from the literature are discussed. The results show that the GCSA performs well for operation sequencing problem in computer-aided process planning. Full article

(This article belongs to the Special Issue Planning and Scheduling Optimization)

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22 pages, 4368 KiB

Open AccessArticle

Strategic Supply Chain Planning for Food Hubs in Central Colombia: An Approach for Sustainable Food Supply and Distribution

by Gonzalo Mejía, Daniela Granados-Rivera, Jairo Alberto Jarrín, Alejandra Castellanos, Natalia Mayorquín and Erika Molano

Appl. Sci. 2021, 11(4), 1792; https://doi.org/10.3390/app11041792 - 18 Feb 2021

Cited by 11 | Viewed by 5119

Abstract

This paper investigates the problem of sustainable rural supply and urban distribution of fresh food products in central Colombia. Paradoxically, while farmers in the countryside suffer from poverty due to the low profitability of the agricultural activity, inhabitants at urban centers pay high [...] Read more.

This paper investigates the problem of sustainable rural supply and urban distribution of fresh food products in central Colombia. Paradoxically, while farmers in the countryside suffer from poverty due to the low profitability of the agricultural activity, inhabitants at urban centers pay high prices for fresh and nutritious foods. In this work, we propose a supply chain system and a business model based on food hubs located on existing (and often abandoned) public facilities in the central region of Colombia. There are many examples in which the hub strategy has facilitated trade and logistics in supply chains. However, few studies consider the particularities of the presented case. We study a business strategy through a mathematical model which considers both the sustainable and efficient operation of the food hubs and better trading conditions for farmers. We propose a variant of the competitive hub location problem adapted to this case study. We tested the model under different scenarios such as changes in the attractiveness parameters, operation costs, and profit margins. The results suggest that if hubs are able to attract farmers, the model can be both sustainable for the hub concessionaires and for the farmers. Full article

(This article belongs to the Special Issue Planning and Scheduling Optimization)

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27 pages, 1691 KiB

Open AccessArticle

Flexible Job Shop Scheduling Problem with Sequence Dependent Setup Time and Job Splitting: Hospital Catering Case Study

by Fatima Abderrabi, Matthieu Godichaud, Alice Yalaoui, Farouk Yalaoui, Lionel Amodeo, Ardian Qerimi and Eric Thivet

Appl. Sci. 2021, 11(4), 1504; https://doi.org/10.3390/app11041504 - 7 Feb 2021

Cited by 13 | Viewed by 4843

Abstract

This paper aims to study a real case of an optimization problem derived from a hospital supply chain. The present work focuses on developing operational decision support models and algorithms for production process scheduling in hospital catering. The addressed production system is considered [...] Read more.

This paper aims to study a real case of an optimization problem derived from a hospital supply chain. The present work focuses on developing operational decision support models and algorithms for production process scheduling in hospital catering. The addressed production system is considered as a flexible job shop system. The objective is to minimize the total flow time. A novel mathematical model and two metaheuristics for the production scheduling of multi-product and multi-stage food processes are developed. These methods have proven their effectiveness for the scheduling of operations of the food production processes and allowed significant improvements in the performance of the studied production system. Full article

(This article belongs to the Special Issue Planning and Scheduling Optimization)

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13 pages, 603 KiB

Open AccessArticle

Lot-Sizing and Scheduling for the Plastic Injection Molding Industry—A Hybrid Optimization Approach

by Nathalie Klement, Mohamed Amine Abdeljaouad, Leonardo Porto and Cristóvão Silva

Appl. Sci. 2021, 11(3), 1202; https://doi.org/10.3390/app11031202 - 28 Jan 2021

Cited by 17 | Viewed by 4590

Abstract

The management of industrial systems is done through different levels, ranging from strategic (designing the system), to tactical (planning the activities and assigning the resources) and operational (scheduling the activities). In this paper, we focus on the latter level by considering a real-world [...] Read more.

The management of industrial systems is done through different levels, ranging from strategic (designing the system), to tactical (planning the activities and assigning the resources) and operational (scheduling the activities). In this paper, we focus on the latter level by considering a real-world scheduling problem from a plastic injection company, where the production process combines parallel machines and a set of resources. We present a scheduling algorithm that combines a metaheuristic and a list algorithm. Two metaheuristics are tested and compared when used in the proposed scheduling approach: the stochastic descent and the simulated annealing. The method’s performances are analyzed through an experimental study and the obtained results show that its outcomes outperform those of the scheduling policy conducted in a case-study company. Moreover, besides being able to solve large real-world problems in a reasonable amount of time, the proposed approach has a structure that makes it flexible and easily adaptable to several different planning and scheduling problems. Indeed, since it is composed by a reusable generic part, the metaheuristic, it is only required to develop a list algorithm adapted to the objective function and constraints of the new problem to be solved. Full article

(This article belongs to the Special Issue Planning and Scheduling Optimization)

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30 pages, 4812 KiB

Open AccessArticle

Slotting Optimization Model for a Warehouse with Divisible First-Level Accommodation Locations

by Pablo Viveros, Katalina González, Rodrigo Mena, Fredy Kristjanpoller and Javier Robledo

Appl. Sci. 2021, 11(3), 936; https://doi.org/10.3390/app11030936 - 20 Jan 2021

Cited by 14 | Viewed by 11384

Abstract

Efficiency in supply chains is critically affected by the performance of operations within warehouses. For this reason, the activities related to the disposition and management of inventories are crucial. This work addresses the multi-level storage locations assignment problem for SKU pallets, considering divisible [...] Read more.

Efficiency in supply chains is critically affected by the performance of operations within warehouses. For this reason, the activities related to the disposition and management of inventories are crucial. This work addresses the multi-level storage locations assignment problem for SKU pallets, considering divisible locations in the first level to improve the picking operation and reduce the travel times associated with the routes of the cranes. A mathematical programming model is developed considering the objective of minimizing the total travel distance, and in the background, maximizing the use of storage capacity. To solve this complex problem, we consider its decomposition into four subproblems, which are solved sequentially. To evaluate the performance of the model, two analysis scenarios based on different storage strategies are proposed to evaluate both the entry and exit distance of pallets, as well as the cost associated with the movements. Full article

(This article belongs to the Special Issue Planning and Scheduling Optimization)

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14 pages, 2931 KiB

Open AccessArticle

Financial Optimization of the Resource-Constrained Project Scheduling Problem with Milestones Payments

by Marcin Klimek

Appl. Sci. 2021, 11(2), 661; https://doi.org/10.3390/app11020661 - 12 Jan 2021

Cited by 7 | Viewed by 3070

Abstract

This article presents the resource-constrained project scheduling problem with the discounted cash flow maximization criterion from the perspective of a contractor. Cash flows are considered as the contractor’s expenses related to the execution of activities and client’s payments (revenue to the contractor) after [...] Read more.

This article presents the resource-constrained project scheduling problem with the discounted cash flow maximization criterion from the perspective of a contractor. Cash flows are considered as the contractor’s expenses related to the execution of activities and client’s payments (revenue to the contractor) after the completion of contractual stages. To solve the problem, dedicated techniques to generate solutions and a simulated annealing algorithm are proposed. Finally, the proposed procedures are examined using the test library, Project Scheduling Library (PSPLIB). An experimental analysis identified the efficient moves and techniques for creating solutions, that is backward scheduling with optimization of completion times of project stages and triple justification. Full article

(This article belongs to the Special Issue Planning and Scheduling Optimization)

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21 pages, 8414 KiB

Open AccessArticle

Solving Order Planning Problem Using a Heuristic Approach: The Case in a Building Material Distributor

by Chia-Nan Wang, Ngoc-Ai-Thy Nguyen and Thanh-Tuan Dang

Appl. Sci. 2020, 10(24), 8959; https://doi.org/10.3390/app10248959 - 15 Dec 2020

Cited by 23 | Viewed by 4784

Abstract

For building material distributors, order planning is a key process as a result of the increase in construction projects’ scale and complexity. In this paper, the integration of simulation modeling and the response surface methodology (RSM) is presented to solve an order planning [...] Read more.

For building material distributors, order planning is a key process as a result of the increase in construction projects’ scale and complexity. In this paper, the integration of simulation modeling and the response surface methodology (RSM) is presented to solve an order planning problem in the construction supply chain. The interactions of various factors are examined to observe their effects on key system measurements, and a combination of factor levels is determined to achieve the optimal performance. RSM is applied to find the possible values of the optimal setting for system responses, which consists of three main steps: central composite design (CCD), Box–Behnken design (BBD), and a comparison of both designs. The model is tested with a realistic case study of a building material distributor in Vietnam to demonstrate its effectiveness. Controllable factors (independent variables), which are the review period (T), order quantity (Q), and safety stock (SS), are found to significantly affect system responses, which are the total cost (TC) and customer service level (CSL). The results provide the best settings of factor levels that produce the possible minimum TC and maximum CSL. The developed framework could be applied as a useful reference for decision-makers, purchasing managers, and warehouse managers to obtain the most suitable order policy for a robust order planning process. Full article

(This article belongs to the Special Issue Planning and Scheduling Optimization)

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15 pages, 498 KiB

Open AccessArticle

A Proposed Extended Version of the Hadi-Vencheh Model to Improve Multiple-Criteria ABC Inventory Classification

by Pei-Chun Lin and Hung-Chieh Chang

Appl. Sci. 2020, 10(22), 8233; https://doi.org/10.3390/app10228233 - 20 Nov 2020

Cited by 1 | Viewed by 2205

Abstract

The ABC classification problem is approached as a ranking problem by the most current classification models; that is, a group of inventory items is expressed according to its overall weighted score of criteria in descending order. In this paper, we present an extended [...] Read more.

The ABC classification problem is approached as a ranking problem by the most current classification models; that is, a group of inventory items is expressed according to its overall weighted score of criteria in descending order. In this paper, we present an extended version of the Hadi-Vencheh model for multiple-criteria ABC inventory classification. The proposed model is one based on the nonlinear weighted product method (WPM), which determines a common set of weights for all items. Our proposed nonlinear WPM incorporates multiple criteria with different measured units without converting the performance of each inventory item, in terms of converting each criterion into a normalized attribute value, thereby providing an improvement over the model proposed by Hadi-Vencheh. Our study mainly includes various criteria for ABC classification and demonstrates an efficient algorithm for solving nonlinear programming problems, in which the feasible solution set does not have to be convex. The algorithm presented in this study substantially improves the solution efficiency of the canonical coordinates method (CCM) algorithm when applied to large-scale, nonlinear programming problems. The modified algorithm was tested to compare our proposed model results to the results derived using the Hadi-Vencheh model and demonstrate the algorithm’s efficacy. The practical objectives of the study were to develop an efficient nonlinear optimization solver by optimizing the quality of existing solutions, thus improving time and space efficiency. Full article

(This article belongs to the Special Issue Planning and Scheduling Optimization)

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28 pages, 2874 KiB

Open AccessArticle

Wave Planning for Cart Picking in a Randomized Storage Warehouse

by Jiun-Yan Shiau and Jie-An Huang

Appl. Sci. 2020, 10(22), 8050; https://doi.org/10.3390/app10228050 - 13 Nov 2020

Cited by 3 | Viewed by 4292

Abstract

Randomized storage strategy is known as a best practice for storing books of an online bookstore, it simplifies the order picking strategy as to retrieve books in purchase orders from closest locations of the warehouse. However, to be more responsive to customers, many [...] Read more.

Randomized storage strategy is known as a best practice for storing books of an online bookstore, it simplifies the order picking strategy as to retrieve books in purchase orders from closest locations of the warehouse. However, to be more responsive to customers, many distribution centers have adopted a just-in-time strategy leading to various value-added activities such as kitting, labelling, product or order assembly, customized packaging, or palletization, all of which must be scheduled and integrated in the order-picking process, and this is known as wave planning. In this study, we present a wave planning mathematical model by simultaneously consider: (1) time window from master of schedule (MOS), (2) random storage stock-keeping units (SKUs), and (3) picker-to-order. A conceptual simulation, along with a simplified example for the proposed wave planning algorithm, has been examined to demonstrate the merits of the idea. The result shows the wave planning module can improve the waiting time for truck loading of packages significantly and can reduce the time that packages are heaping in buffer area. The main contribution of this research is to develop a mixed integer programming model that helps the bookseller to generate optimal wave picking lists for a given time window. Full article

(This article belongs to the Special Issue Planning and Scheduling Optimization)

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20 pages, 4065 KiB

Open AccessArticle

An Optimization Model for Operational Planning and Turnaround Maintenance Scheduling of Oil and Gas Supply Chain

by Ahmed M. Ghaithan

Appl. Sci. 2020, 10(21), 7531; https://doi.org/10.3390/app10217531 - 26 Oct 2020

Cited by 15 | Viewed by 4737

Abstract

Hydrocarbon supply chain (HCSC) is a complex network that extends from oil and gas fields to demand nodes. Integrating operation and maintenance activities along this complex network is crucial since the hydrocarbon industry is the most influential sector in the world economy, and [...] Read more.

Hydrocarbon supply chain (HCSC) is a complex network that extends from oil and gas fields to demand nodes. Integrating operation and maintenance activities along this complex network is crucial since the hydrocarbon industry is the most influential sector in the world economy, and any disruptions or variations in hydrocarbon product supply will affect the whole world economy. Therefore, effective and thoughtful maintenance extends the life of an asset and enhances its reliability. To prevent huge losses in production and ultimately satisfy customer needs, the maintenance jobs are preferred to be performed during times of low demand. Thus, operation planning and maintenance scheduling decisions are dependent and should be optimized simultaneously. Therefore, the aim of this study is to develop an integrated mathematical model for the operation and maintenance planning of the oil and gas supply chain. The utility of the proposed model has been demonstrated using the Saudi Arabian HCSC. The proposed model effectively produces optimal operation and maintenance schedule decisions. A sensitivity analysis was conducted to study the effect of critical parameters on the obtained results. Full article

(This article belongs to the Special Issue Planning and Scheduling Optimization)

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Review

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19 pages, 1282 KiB

Open AccessReview

Smart Manufacturing Scheduling Approaches—Systematic Review and Future Directions

by Duarte Alemão, André Dionisio Rocha and José Barata

Appl. Sci. 2021, 11(5), 2186; https://doi.org/10.3390/app11052186 - 2 Mar 2021

Cited by 17 | Viewed by 4931

Abstract

The recent advances in technology and the demand for highly customized products have been forcing manufacturing companies to adapt and develop new solutions in order to become more dynamic and flexible to face the changing markets. Manufacturing scheduling plays a core role in [...] Read more.

The recent advances in technology and the demand for highly customized products have been forcing manufacturing companies to adapt and develop new solutions in order to become more dynamic and flexible to face the changing markets. Manufacturing scheduling plays a core role in this adaptation since it is crucial to ensure that all operations and processes are running on time in the factory. However, to develop robust scheduling solutions it is necessary to consider different requirements from the shopfloor, but it is not clear which constraints should be analyzed and most research studies end up considering very few of them. In this review article, several papers published in recent years were analyzed to understand how many and which requirements they consider when developing scheduling solutions for manufacturing systems. It is possible to understand that the majority of them are not able to be adapted to real systems since some core constraints are not even considered. Consequently, it is important to consider how manufacturing scheduling solutions can be structured to be adapted effortlessly for different manufacturing scenarios. Full article

(This article belongs to the Special Issue Planning and Scheduling Optimization)

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