scholarly journals Integrated employee scheduling with known employee demand, including breaks, overtime, and employee preferences

2020 ◽  
Vol 13 (3) ◽  
pp. 451
Author(s):  
Jhunievieve Soriano ◽  
Eugene Rex Jalao ◽  
Iris Ann Martinez
Keyword(s):  
Working Conditions ◽  
Real Life ◽  
Mixed Integer ◽  
Scheduling Problem ◽  
Scheduling Problems ◽  
Analytic Hierarchy ◽  
Individual Preferences ◽  
Life Problems ◽  
Proposed Model ◽  
Employee Scheduling

Purpose: This research paper introduces an integrated employee scheduling problem that considers various real-life problems such as varying employee demand, different employee working conditions, and individual preferences regarding schedules.Design/methodology/approach: The proposed model, which is a combination of Analytic Hierarchy Process and Mixed Integer Linear Programming, is used to solve the problem with multi-dimensional objectivesFindings: Results show that the proposed model generates optimal and feasible solutions for weekly employee schedules.Originality/value: Many employee scheduling problems in literature are able to solve the employee scheduling problem to a large extent but still do not fully reflect current realistic organizational problems such as varying employee demand per hour inteval, different employee working conditions on disjoint shifts and breaks, and individual preferences regarding schedules all at the same time.

scholarly journals Solving the nuclear dismantling project scheduling problem by combining mixed-integer and constraint programming techniques and metaheuristics

2021 ◽  
Author(s):  
Felix Hübner ◽  
Patrick Gerhards ◽  
Christian Stürck ◽  
Rebekka Volk
Keyword(s):  
Constraint Programming ◽  
Project Scheduling ◽  
Computational Study ◽  
Real Life ◽  
Mixed Integer ◽  
Extensive Literature ◽  
Scheduling Problem ◽  
Multiple Modes ◽  
Project Scheduling Problem ◽  
Optimisation Techniques

AbstractScheduling of megaprojects is very challenging because of typical characteristics, such as expected long project durations, many activities with multiple modes, scarce resources, and investment decisions. Furthermore, each megaproject has additional specific characteristics to be considered. Since the number of nuclear dismantling projects is expected to increase considerably worldwide in the coming decades, we use this type of megaproject as an application case in this paper. Therefore, we consider the specific characteristics of constrained renewable and non-renewable resources, multiple modes, precedence relations with and without no-wait condition, and a cost minimisation objective. To reliably plan at minimum costs considering all relevant characteristics, scheduling methods can be applied. But the extensive literature review conducted did not reveal a scheduling method considering the special characteristics of nuclear dismantling projects. Consequently, we introduce a novel scheduling problem referred to as the nuclear dismantling project scheduling problem. Furthermore, we developed and implemented an effective metaheuristic to obtain feasible schedules for projects with about 300 activities. We tested our approach with real-life data of three different nuclear dismantling projects in Germany. On average, it took less than a second to find an initial feasible solution for our samples. This solution could be further improved using metaheuristic procedures and exact optimisation techniques such as mixed-integer programming and constraint programming. The computational study shows that utilising exact optimisation techniques is beneficial compared to standard metaheuristics. The main result is the development of an initial solution finding procedure and an adaptive large neighbourhood search with iterative destroy and recreate operations that is competitive with state-of-the-art methods of related problems. The described problem and findings can be transferred to other megaprojects.

A metaheuristic technique for energy-efficiency in job-shop scheduling

2016 ◽  
Vol 31 (5) ◽  
pp. 475-485 ◽  
Author(s):  
Joan Escamilla ◽  
Miguel A. Salido ◽  
Adriana Giret ◽  
Federico Barber
Keyword(s):  
Genetic Algorithm ◽  
Energy Efficiency ◽  
Job Shop ◽  
Job Shop Scheduling ◽  
Real Life ◽  
Scheduling Problem ◽  
Scheduling Problems ◽  
Extended Version ◽  
Reasonable Time ◽  
Shop Scheduling

AbstractMany real life problems can be modeled as a scheduling problem. The main objective of these problems is to obtain optimal solutions in terms of processing time, cost and quality. Nowadays, energy-efficiency is also taken into consideration. However, these problems are NP-hard, so many search techniques are not able to obtain a solution in a reasonable time. In this paper, a genetic algorithm is developed to solve an extended version of the classical job-shop scheduling problem. In the extended version, each operation has to be executed by one machine and this machine can work at different speed rates. The machines consume different amounts of energy to process tasks at different rates. The evaluation section shows that a powerful commercial tools for solving scheduling problems was not able to solve large instances in a reasonable time, meanwhile our genetic algorithm was able to solve all instances with a good solution quality.

scholarly journals Fuzzy Analytic Hierarchy Process-Based Multi-Criteria Decision Making for Universities Ranking

Symmetry ◽  
2020 ◽  
Vol 12 (8) ◽  
pp. 1351
Author(s):  
Rashad Aliyev ◽  
Hasan Temizkan ◽  
Rafig Aliyev
Keyword(s):  
Decision Making ◽  
Analytic Hierarchy Process ◽  
Performance Indicator ◽  
Real Life ◽  
Fuzzy Analytic Hierarchy Process ◽  
Multi Criteria Decision Making ◽  
Analytic Hierarchy ◽  
Life Problems ◽  
Types Of Information ◽  
Hierarchy Process

High competition between universities has been increasing over the years, and stimulates higher education institutions to attain higher positions in the ranking list. Ranking is an important performance indicator of university status evaluation, and therefore plays an essential role in students’ university selection. The ranking of universities has been carried out using different techniques. Main goal of decision processes in real-life problems is to deal with the symmetry or asymmetry of different types of information. We consider that multi-criteria decision making (MCDM) is well applicable to symmetric information modelling. Analytic hierarchy process (AHP) is a well-known technique of MCDM discipline, and is based on pairwise comparisons of criteria/alternatives for alternatives’ evaluation. Unfortunately, the classical AHP method is unable to deal with imprecise, vague, and subjective information used for the decision making process in complex problems. So, introducing a more advanced tool for decision making under such circumstances is inevitable. In this paper, fuzzy analytic hierarchy process (FAHP) is applied for the comparison and ranking of performances of five UK universities, according to four criteria. The criteria used for the evaluation of universities’ performances are teaching, research, citations, and international outlook. It is proven that applying FAHP approach makes the system consistent, and by the calculation of coefficient of variation for all alternatives, it becomes possible to rank them in prioritized order.

The cycle shop scheduling: mathematical model, properties and solution algorithms

2019 ◽  
Vol 53 (1) ◽  
pp. 111-128
Author(s):  
Bahman Naderia ◽  
Sheida Goharib
Keyword(s):  
High Performance ◽  
Scatter Search ◽  
Mixed Integer ◽  
Computational Time ◽  
Neighborhood Search ◽  
Scheduling Problems ◽  
Shop Scheduling ◽  
Solution Algorithms ◽  
Proposed Model ◽  
Constructive Heuristics

Conventionally, in scheduling problems it is assumed that each job visits each machine once. This paper studies a novel shop scheduling called cycle shop problems where jobs might return to each machine more than once. The problem is first formulated by two mixed integer linear programming models. The characteristics of the problem are analyzed, and it is realized that the problem suffers from a shortcoming called redundancy, i.e., several sequences represents the same schedule. In this regard, some properties are introduced by which the redundant sequences can be recognized before scheduling. Three constructive heuristics are developed. They are based on the shortest processing time first, insertion neighborhood search and non-delay schedules. Then, a metaheuristic based on scatter search is proposed. The algorithms are equipped with the redundancy prevention properties that greatly reduce the computational time of the algorithms. Two sets of experiments are conducted. The proposed model and algorithms are evaluated. The results show the high performance of model and algorithms.

scholarly journals A Fuzzy-Based Decision-Making Model for Improving the Carrying Capacity of Ship Locks: A Three Gorges Dam Case

2019 ◽  
Vol 7 (8) ◽  
pp. 244
Author(s):  
Shaoyue Shi ◽  
Danhong Zhang ◽  
Yixin Su ◽  
Chengpeng Wan ◽  
Mingyang Zhang ◽  
...  
Keyword(s):  
Decision Making ◽  
Carrying Capacity ◽  
Real Life ◽  
Three Gorges Dam ◽  
Three Gorges ◽  
Analytic Hierarchy ◽  
Proposed Model ◽  
Order Preference ◽  
Real Life Situation ◽  
Decision Making Model

This paper develops a decision-making model to assist the improvement of the carrying capacity of ship locks by combing fuzzy logic, the analytic hierarchy process (AHP) method, and the technique for order preference by similarity to an ideal solution (TOPSIS). A three-level hierarchical structure is constructed to identify the key factors influencing the carrying capacity of ship locks from the aspects of ship locks, vessels, environment, and administration. On this basis, a series of targeted strategies have been put forward to improve the carrying capacity of ship locks, and the TOPSIS method is applied to rank these strategies in terms of their performance. A case study of the five-stage dual-track ship lock of the Three Gorges Dam in China has been conducted to demonstrate the feasibility and rationality of the proposed model, and correlation analysis is conducted to verify the identified influencing factors in order to eliminate potential bias which may be generated from using AHP. The results obtained from the proposed methods are consistent with the real-life situation to a certain extent, indicating that the proposed method can provide a useful reference for improving the carrying capacity of ship locks.

scholarly journals Solving the Short-Term Scheduling Problem of Hydrothermal Systems via Lagrangian Relaxation and Augmented Lagrangian

2012 ◽  
Vol 2012 ◽  
pp. 1-18 ◽  
Author(s):  
Rafael N. Rodrigues ◽  
Edson L. da Silva ◽  
Erlon C. Finardi ◽  
Fabricio Y. K. Takigawa
Keyword(s):  
Lagrangian Relaxation ◽  
Large Scale ◽  
Augmented Lagrangian ◽  
Augmented Lagrangian Method ◽  
Real Life ◽  
Hydrothermal Systems ◽  
Bundle Method ◽  
Mixed Integer ◽  
Scheduling Problem ◽  
Short Term

This paper addresses the short-term scheduling problem of hydrothermal power systems, which results in a large-scale mixed-integer nonlinear programming problem. The objective consists in minimizing the operation cost over a two-day horizon with a one-hour time resolution. To solve this difficult problem, a Lagrangian Relaxation (LR) based on variable splitting is designed where the resulting dual problem is solved by a Bundle method. Given that the LR usually fails to find a feasible solution, we use an inexact Augmented Lagrangian method to improve the quality of the solution supplied by the LR. We assess our approach by using a real-life hydrothermal configuration extracted from the Brazilian power system, proving the conceptual and practical feasibility of the proposed algorithm. In summary, the main contributions of this paper are (i) a detailed and compatible modelling for this problem is presented; (ii) in order to solve efficiently the entire problem, a suitable decomposition strategy is presented. As a result of these contributions, the proposed model is able to find practical solutions with moderate computational burden, which is absolutely necessary in the modern power industry.

scholarly journals INCREMENTAL FILTERING ALGORITHMS FOR PRECEDENCE AND DEPENDENCY CONSTRAINTS

2008 ◽  
Vol 17 (01) ◽  
pp. 205-221 ◽  
Author(s):  
ROMAN BARTÁK ◽  
ONDŘEJ ČEPEK
Keyword(s):  
Crucial Role ◽  
Real Life ◽  
Precedence Constraints ◽  
Scheduling Problems ◽  
Planning And Scheduling ◽  
Filtering Algorithms ◽  
Life Problems

Precedence constraints specify that an activity must finish before another activity starts and hence such constraints play a crucial role in planning and scheduling problems. Many real-life problems also include dependency constraints expressing logical relations between the activities – for example, an activity requires presence of another activity in the plan. For such problems a typical objective is a maximization of the number of activities satisfying the precedence and dependency constraints. In the paper we propose new incremental filtering rules integrating propagation through both precedence and dependency constraints. We also propose a new filtering rule using the information about the requested number of activities in the plan. We demonstrate efficiency of the proposed rules on log-based reconciliation problems and min-cutset problems.

scholarly journals An Enhanced Discrete Bees Algorithm for Resource Constrained Optimization Problems

2019 ◽  
Vol 22 (64) ◽  
pp. 123-134
Author(s):  
Mohamed Amine Nemmich ◽  
Fatima Debbat ◽  
Mohamed Slimane
Keyword(s):  
Project Scheduling ◽  
Optimization Problems ◽  
Solution Space ◽  
Bees Algorithm ◽  
Problem Instance ◽  
Scheduling Problem ◽  
Scheduling Problems ◽  
Resource Constrained ◽  
Proposed Model ◽  
Project Scheduling Problem

In this paper, we propose a novel efficient model based on Bees Algorithm (BA) for the Resource-Constrained Project Scheduling Problem (RCPSP). The studied RCPSP is a NP-hard combinatorial optimization problem which involves resource, precedence, and temporal constraints. It has been applied to many applications. The main objective is to minimize the expected makespan of the project. The proposed model, named Enhanced Discrete Bees Algorithm (EDBA), iteratively solves the RCPSP by utilizing intelligent foraging behaviors of honey bees. The potential solution is represented by the multidimensional bee, where the activity list representation (AL) is considered. This projection involves using the Serial Schedule Generation Scheme (SSGS) as decoding procedure to construct the active schedules. In addition, the conventional local search of the basic BA is replaced by a neighboring technique, based on the swap operator, which takes into account the specificity of the solution space of project scheduling problems and reduces the number of parameters to be tuned. The proposed EDBA is tested on well-known benchmark problem instance sets from Project Scheduling Problem Library (PSPLIB) and compared with other approaches from the literature. The promising computational results reveal the effectiveness of the proposed approach for solving the RCPSP problems of various scales.

scholarly journals Distance restricted maximal covering model for pharmacy duty scheduling problem

2018 ◽  
Vol 8 (2) ◽  
pp. 208-215
Author(s):  
Nuşin Uncu ◽  
Berna Bulğurcu ◽  
Fatih Kılıç
Keyword(s):  
Programming Model ◽  
Health Care Systems ◽  
Mixed Integer ◽  
Scheduling Problem ◽  
Weighted Distance ◽  
Maximal Covering ◽  
Proposed Model ◽  
Care Systems ◽  
Covering Model ◽  
The City

Pharmacies are considered as an integral part of health care systems for supplying medicine to patients. In order to access  medicine with ease, pharmacies locations in the context of distance and demand are important for patients. In the case of a few numbers of pharmacies may be on duty at nights or during holidays, pharmacies duty scheduling problem occur and can be associated with location models. In contrast to widely used p-median model which aims to minimize the demand-weighted distance, we maximize the demand covered over the distance between the patients and the pharmacies on duty. Main contribution of the proposed model is the restriction constraint for the distance between pharmacies on duty in order to ensure fairness in an organizational view of point. We propose a distance restricted maximal covering location model (DR-MCLM) in this study. This mathematical model is a mixed integer linear programming model and solved by Lingo optimization software. The distances between the pharmacies and the sites are obtained using Geographic Information Systems (GIS). The model is applied for the case in Adana, one of the biggest cities in Turkey. The results are given on the maps of the city, including the pharmacies on duty and their assignments to sites in each day of the period.

scholarly journals A STOCHASTIC MULTI-CRITERIA DECISION-MAKING ANALYSIS FOR A WAREHOUSE LOCATION SELECTION PROBLEM: A CASE STUDY

2020 ◽  
Vol 7 (12) ◽  
pp. 133-143
Author(s):  
Şeyma Emeç ◽  
Gökay Akkaya
Keyword(s):  
Decision Making ◽  
Real Life ◽  
Multiple Criteria Decision Making ◽  
Selection Problem ◽  
Multi Criteria Decision Making ◽  
Analytic Hierarchy ◽  
Location Selection ◽  
Solution Approach ◽  
Life Problems ◽  
Warehouse Location

The problem of a warehouse location selecting which has a significant impact on logistics costs is an important decision problem based on the best choice of alternatives under multiple conflicting criteria. Multiple-criteria decision-making (MCDM) methods are used as a solution approach for the decision problems including several criteria. In this study, a new stochastic multi-criteria decision-making approach has been developed to solve the warehouse location selection problem (WLSP) in the stochastic environment which contains uncertain situations. In the proposed approach, the SAHP (Stochastic Analytic Hierarchy Process) method was used to calculate the weight of criteria, and the alternatives were ranked and evaluated by fuzzy MOORA (Multi-Objective Optimization by Ratio Analysis). The proposed approach is applied to warehouse selection problem of a supermarket chain located in Turkey. The results of the research indicated that A2 is the best alternative. It can be said that the proposed method can be applied to the real life problems because it found a suitable solution to the problem.

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