Planning Horizon Procedures for Machine Replacement Models

2008 ◽  
Author(s):  
Suresh Sethi ◽  
Suresh Chand
Keyword(s):  
Planning Horizon ◽  
Machine Replacement

Planning Horizon Procedures for Machine Replacement Models

1979 ◽  
Vol 25 (2) ◽  
pp. 140-151 ◽  
Author(s):  
Suresh Sethi ◽  
Suresh Chand
Keyword(s):  
Planning Horizon ◽  
Machine Replacement

Equipment Replacement Decisions Models with the Context of Flexible Manufacturing Cells

2012 ◽  
pp. 453-463
Author(s):  
Ioan Constantin Dima ◽  
Janusz Grabara ◽  
Mária Nowicka-Skowron
Keyword(s):  
Flexible Manufacturing ◽  
Economies Of Scale ◽  
Planning Horizon ◽  
Industrial Robots ◽  
Manufacturing Cells ◽  
Equipment Replacement ◽  
Flexible Manufacturing Cells ◽  
Replacement Decisions ◽  
Production Organization ◽  
Machine Replacement

The main problem of establishing equipment replacement decisions rules under specific conditions is to find decision variables that minimize total incurred costs over a planning horizon. Basically, the rules differ depending on what type of production type is used. For a batch production organization the suitable criterion is built on the principle of economies of scale. Proposed econometric models in this chapter are focused on a multiple machine replacement problem in flexible manufacturing cells with several machines for parts’ processing, and industrial robots for manipulation and transportation of manufactured objects. Firstly, models for a simple case multiple machine replacement problems are presented. Subsequently, the more complicated case is considered where technological improvement is taken into account.

scholarly journals Erratum to “Planning Horizon Procedures for Machine Replacement Models”

1980 ◽  
Vol 26 (3) ◽  
pp. 342-342 ◽  
Author(s):  
Suresh P. Sethi ◽  
Suresh Chand
Keyword(s):  
Planning Horizon ◽  
Machine Replacement

Equipment Replacement Decisions Models with the Context of Flexible Manufacturing Cells

2013 ◽  
pp. 401-411
Author(s):  
Ioan Constantin Dima ◽  
Janusz Grabara ◽  
Mária Nowicka-Skowron
Keyword(s):  
Flexible Manufacturing ◽  
Economies Of Scale ◽  
Planning Horizon ◽  
Industrial Robots ◽  
Manufacturing Cells ◽  
Equipment Replacement ◽  
Flexible Manufacturing Cells ◽  
Replacement Decisions ◽  
Production Organization ◽  
Machine Replacement

The main problem of establishing equipment replacement decisions rules under specific conditions is to find decision variables that minimize total incurred costs over a planning horizon. Basically, the rules differ depending on what type of production type is used. For a batch production organization the suitable criterion is built on the principle of economies of scale. Proposed econometric models in this chapter are focused on a multiple machine replacement problem in flexible manufacturing cells with several machines for parts’ processing, and industrial robots for manipulation and transportation of manufactured objects. Firstly, models for a simple case multiple machine replacement problems are presented. Subsequently, the more complicated case is considered where technological improvement is taken into account.

Optimizing preventive maintenance over a finite planning horizon in a semi-Markov framework

2020 ◽  
Author(s):  
Antonio Sánchez Herguedas ◽  
Adolfo Crespo Márquez ◽  
Francisco Rodrigo Muñoz
Keyword(s):  
Preventive Maintenance ◽  
Recurrence Relations ◽  
Direct Calculation ◽  
Planning Horizon ◽  
Practical Implementation ◽  
Practical Application ◽  
Mathematical Solution ◽  
Accumulated Reward ◽  
Finite Planning Horizon

Abstract This paper describes the optimization of preventive maintenance (PM) over a finite planning horizon in a semi-Markov framework. In this framework, the asset may be operating, and providing income for the asset owner, or not operating and undergoing PM, or not operating and undergoing corrective maintenance following failure. PM is triggered when the asset has been operating for τ time units. A number m of transitions specifies the finite horizon. This system is described with a set of recurrence relations, and their z-transform is used to determine the value of τ that maximizes the average accumulated reward over the horizon. We study under what conditions a solution can be found, and for those specific cases the solution τ* is calculated. Despite the complexity of the mathematical solution, the result obtained allows the analyst to provide a quick and easy-to-use tool for practical application in many real-world cases. To demonstrate this, the method has been implemented for a case study, and its accuracy and practical implementation were tested using Monte Carlo simulation and direct calculation.

scholarly journals Minimizing spectral risk measures applied to Markov decision processes

2021 ◽  
Author(s):  
Nicole Bäuerle ◽  
Alexander Glauner
Keyword(s):  
Minimization Problem ◽  
Risk Measures ◽  
Risk Measure ◽  
Sufficient Conditions ◽  
Planning Horizon ◽  
Insurance Company ◽  
Existence Of A Solution ◽  
Discounted Cost ◽  
Spectral Risk Measures ◽  
Markov Decision

AbstractWe study the minimization of a spectral risk measure of the total discounted cost generated by a Markov Decision Process (MDP) over a finite or infinite planning horizon. The MDP is assumed to have Borel state and action spaces and the cost function may be unbounded above. The optimization problem is split into two minimization problems using an infimum representation for spectral risk measures. We show that the inner minimization problem can be solved as an ordinary MDP on an extended state space and give sufficient conditions under which an optimal policy exists. Regarding the infinite dimensional outer minimization problem, we prove the existence of a solution and derive an algorithm for its numerical approximation. Our results include the findings in Bäuerle and Ott (Math Methods Oper Res 74(3):361–379, 2011) in the special case that the risk measure is Expected Shortfall. As an application, we present a dynamic extension of the classical static optimal reinsurance problem, where an insurance company minimizes its cost of capital.

scholarly journals Investment Incentives in Competitive Electricity Markets

2018 ◽  
Vol 8 (10) ◽  
pp. 1978 ◽  
Author(s):  
Jaber Valinejad ◽  
Taghi Barforoshi ◽  
Mousa Marzband ◽  
Edris Pouresmaeil ◽  
Radu Godina ◽  
...  
Keyword(s):  
Electricity Markets ◽  
Electricity Market ◽  
Planning Horizon ◽  
Optimization Method ◽  
Design Criterion ◽  
Mixed Integer ◽  
Investment Incentives ◽  
Mixed Integer Linear Program ◽  
Interconnected Power System ◽  
The Impact

This paper presents the analysis of a novel framework of study and the impact of different market design criterion for the generation expansion planning (GEP) in competitive electricity market incentives, under variable uncertainties in a single year horizon. As investment incentives conventionally consist of firm contracts and capacity payments, in this study, the electricity generation investment problem is considered from a strategic generation company (GENCO) ′ s perspective, modelled as a bi-level optimization method. The first-level includes decision steps related to investment incentives to maximize the total profit in the planning horizon. The second-level includes optimization steps focusing on maximizing social welfare when the electricity market is regulated for the current horizon. In addition, variable uncertainties, on offering and investment, are modelled using set of different scenarios. The bi-level optimization problem is then converted to a single-level problem and then represented as a mixed integer linear program (MILP) after linearization. The efficiency of the proposed framework is assessed on the MAZANDARAN regional electric company (MREC) transmission network, integral to IRAN interconnected power system for both elastic and inelastic demands. Simulations show the significance of optimizing the firm contract and the capacity payment that encourages the generation investment for peak technology and improves long-term stability of electricity markets.

scholarly journals Minimizing the Number of Tardy Jobs on a Single Machine with an Availability Constraint

2014 ◽  
Vol 2014 ◽  
pp. 1-13 ◽  
Author(s):  
Ehsan Molaee ◽  
Ghasem Moslehi
Keyword(s):  
Branch And Bound ◽  
Single Machine ◽  
Planning Horizon ◽  
Single Machine Scheduling ◽  
Upper And Lower Bounds ◽  
Scheduling Problems ◽  
Bearing Witness ◽  
Number Of Tardy Jobs ◽  
Problem Instances ◽  
Tardy Jobs

Most scheduling problems are based on the assumption that machines work continuously during the planning horizon. This assumption is not true in many production environments because the machine may not be available during one or more periods such as during breakdowns or maintenance operations. In this paper, the problem of the single machine scheduling with one unavailability period and nonresumable jobs with the aim of minimizing the number of tardy jobs is studied. A number of theorems are proved and a heuristic procedure is developed to solve the problem. A branch-and-bound approach is also presented which includes upper and lower bounds and efficient dominance rules. Computational results for 2680 problem instances show that the branch-and-bound approach is capable of solving 98.7% of the instances optimally, bearing witness to the efficiency of the proposed procedure. Our results also indicate that the proposed approaches are more efficient when compared to other methods.

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