Fuzzy Interval-Valued Temporal Automated Planning and Scheduling Problem

Author(s):  
Janusz Kacprzyk ◽  
Margarita Knyazeva ◽  
Alexander Bozhenyuk
2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Muhammad Bilal Khan ◽  
Muhammad Aslam Noor ◽  
Khalida Inayat Noor ◽  
Yu-Ming Chu

AbstractIn this paper, we introduce the non-convex interval-valued functions for fuzzy-interval-valued functions, which are called "Equation missing"-convex fuzzy-interval-valued functions, by means of fuzzy order relation. This fuzzy order relation is defined level-wise through Kulisch–Miranker order relation given on the interval space. By using the "Equation missing"-convexity concept, we present fuzzy-interval Hermite–Hadamard inequalities for fuzzy-interval-valued functions. Several exceptional cases are debated, which can be viewed as useful applications. Interesting examples that verify the applicability of the theory developed in this study are presented. The results of this paper can be considered as extensions of previously established results.


2017 ◽  
Vol 420 ◽  
pp. 110-125 ◽  
Author(s):  
T.M. Costa ◽  
H. Román-Flores

2021 ◽  
Author(s):  
Tanmoy Banerjee ◽  
Amiya Biswas ◽  
Ali Akbar Shaikh ◽  
Asoke Kumar Bhunia

Author(s):  
Zineb Ibn Majdoub Hassani ◽  
Abdellah El Barkany ◽  
Abdelouahhab Jabri ◽  
Ikram El Abbassi

This article concerns the integration of planning and scheduling production system. Planning and scheduling are usually treated separately because of their complexity. Scheduling largely depends on the production quantities computed at the production planning level. However, ignoring scheduling constraints in the tactical level leads to inconsistent decisions. So, it is important to integrate planning and scheduling to efficiently manage operations and to determine a realistic production plan for a given sequence of jobs on each machine. In this paper, we present some approaches proposed to solve the problem and we realize a comparison between the two most interesting ones, using the standard solver CPLEX.


Author(s):  
Vitaly Semenov ◽  
Anton Anichkin ◽  
Sergey Morozov ◽  
Oleg Tarlapan ◽  
Vladislav Zolotov

Effective project management implies the use of advanced planning and scheduling methods that allow to determine feasible sequences of activities and to complete a project on time and on budget. Traditional scheduling tools like fundamental Critical Path Method (CPM) and various methods for Resource Constrained Project Scheduling Problem (RCPSP) and Time Constrained Project Scheduling Problem (TCPSP) have many shortcomings for construction projects where spatial factor plays a critically important role. Previous attempts to interpret space as a specific resource were successful for particular problems of line-of-balance scheduling, space scheduling, dynamic layout planning, horizontal and vertical logic scheduling, workspace congestion mitigating, scheduling multiple projects with movable resources, spatial scheduling of repeated and grouped activities and motion planning. However, none of these methods considers the spatio-temporal requirements in a holistic framework of generic RCPSP problem and provides feasible results accounting for workspace and workflow factors. In this paper we start with the classical RCPSP statement and then present mathematically strong formalisation of the extended generalised problem, taking into account workspace congestion and workflow disturbance constraints specified in practically meaningful and computationally constructive ways. For the generalised RCPSP problem an effective scheduling method is proposed. The method tends to minimise the project makespan while satisfying timing constraints and precedence relations, not exceeding resource utilisation limits, avoiding workspace congestions and keeping workflows continuous. The method reuses so-called serial scheduling scheme and provides for additional computational routines and heuristic priority rules to generate feasible schedules satisfying all the imposed requirements. Advantages of the method and prospects for its application to industrial needs are outlined in the paper too.


2017 ◽  
Vol 17 (3) ◽  
pp. 133-138
Author(s):  
A. Stawowy ◽  
J. Duda

Abstract In the paper, we present a coordinated production planning and scheduling problem for three major shops in a typical alloy casting foundry, i.e. a melting shop, molding shop with automatic line and a core shop. The castings, prepared from different metal, have different weight and different number of cores. Although core preparation does not required as strict coordination with molding plan as metal preparation in furnaces, some cores may have limited shelf life, depending on the material used, or at least it is usually not the best organizational practice to prepare them long in advance. Core shop have limited capacity, so the cores for castings that require multiple cores should be prepared earlier. We present a mixed integer programming model for the coordinated production planning and scheduling problem of the shops. Then we propose a simple Lagrangian relaxation heuristic and evolutionary based heuristic to solve the coordinated problem. The applicability of the proposed solution in industrial practice is verified on large instances of the problem with the data simulating actual production parameters in one of the medium size foundry.


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