An economic lot and delivery scheduling problem with the fuzzy shelf life in a flexible job shop with unrelated parallel machines

This paper considers an economic lot and delivery scheduling problem (ELDSP) in a fuzzy environment with the fuzzy shelf life for each product. This problem is formulated in a flexible job shop with unrelated parallel machines, when the planning horizon is finite and it determines lot sizing, scheduling and sequencing, simultaneously. The proposed model of this paper is based on the basic period (BP) approach. In this paper, a mixed-integer nonlinear programming (MINLP) model is presented and then it is changed into two models in the fuzzy shelf life. The main model is dependent to the multiple basic periods and it is difficult to solve the resulted proposed model for large-scale problems in reasonable amount of time; thus, an efficient heuristic method is proposed to solve the problem. The performance of the proposed model is demonstrated using some numerical examples

Joint lot sizing and scheduling of a multi-product multi-period supply chain

The joint lot sizing and scheduling problem can be considered as an evolvement of the joint economic lot size problem which has drawn researchers’ interests for decades. The objective of this paper is to find the effect of a capacitated multi-period supply chain design parameters on joint lot sizing and scheduling decisions for different holding and penalty costs. The supply chain deals with two raw materials suppliers. The production facility produces two products which are shipped to customers through distribution centers. A mathematical model is developed to determine optimum quantities of purchased raw materials, production schedule (MPS), delivered quantities and raw material and products inventory for predetermined number of periods. The model is solved to maximize total supply chain profits. Results showed that at high capacity and low holding cost, the supply chain tends to produce only one product each period, for limited capacity and high value of holding cost, the supply chain may produce the two products together each period

An Effective Hybrid Genetic Algorithm for Hybrid Flow Shops with Sequence Dependent Setup Times and Processor Blocking

Hybrid flow-shop or flexible flow shop problems have remained subject of intensive research over several years. Hybrid flow-shop problems overcome one of the limitations of the classical flow-shop model by allowing parallel processors at each stage of task processing. In many papers the assumptions are generally made that there is unlimited storage available between stages and the setup times are neglected or considered independent from sequences of jobs. In this paper we study the hybrid flow shop problems with sequence dependent setup times and processor blocking. We present an effective hybrid genetic algorithm with some state-of-the-art procedures for these NP-hard problems to minimize total completion time or makespan. We established a benchmark to draw an analogy between the performance of our algorithm and RKGA. The obtaining results clearly show the superiority performance of our algorithm

Multicriteria hybrid flow shop scheduling problem: literature review, analysis, and future research

This research focuses on the Hybrid Flow Shop production scheduling problem, which is one of the most difficult problems to solve. The literature points to several studies that focus the Hybrid Flow Shop scheduling problem with monocriteria functions. Despite of the fact that, many real world problems involve several objective functions, they can often compete and conflict, leading researchers to concentrate direct their efforts on the development of methods that take consider this variant into consideration. The goal of the study is to review and analyze the methods in order to solve the Hybrid Flow Shop production scheduling problem with multicriteria functions in the literature. The analyses were performed using several papers that have been published over the years, also the parallel machines types, the approach used to develop solution methods, the type of method develop, the objective function, the performance criterion adopted, and the additional constraints considered. The results of the reviewing and analysis of 46 papers showed opportunities for future researchon this topic, including the following: (i) use uniform and dedicated parallel machines, (ii) use exact and metaheuristics approaches, (iv) develop lower and uppers bounds, relations of dominance and different search strategiesto improve the computational time of the exact methods,  (v) develop  other types of metaheuristic, (vi) work with anticipatory setups, and (vii) add constraints faced by the production systems itself

Impact of financial risk on supply chains: a manufacturer-supplier relational perspective

This study aims to analyse the manufacturer-supplier relational perspective under the influence of exogenous financial risk. Following corporate finance theory, a multi-objective decision model for supplier selection and order allocation is developed to maximise the total profit of the manufacturer, and minimise the implicit equity stake and financial risk faced by selected suppliers. A two-echelon supply chain is explored under the influence of foreign exchange risk, default risk, market risk and price fluctuation risk, and solved using an NSGA-III algorithm. Three case scenarios are analysed to explore the influence of a set of financial risk on the manufacturer-supplier relationship and the behaviour of suppliers concerning risk profile, both in the short and long-term horizon. The results are analysed from both the manufacturer as well as supplier perspective, and the optimal conditions are discussed under the cascading risk circumstances. The study provides multiple insights into the impact of financial risk on supply chain relationship and will be valuable for dealing with similar uncertain economic environment. The research is likely to be of benefit beyond supply chain managers, like investors and financial risk managers in making informed decisions. The need to focus on systemic risk in supply chains is evident from the study

Open source solution approaches to a class of stochastic supply chain problems

This research proposes a variety of solution approaches to a class of stochastic supply chain problems, with normally distributed demand in a certain period of time in the future. These problems aim to provide the decisions regarding the production levels; supplier selection for raw materials; and optimal order quantity. The typical problem could be formulated as a mixed integer nonlinear program model, and the objective function for maximizing the expected profit is expressed in an integral format. In order to solve the problem, an open source solution package BONMIN is first employed to get the exact optimum result for small scale instances; then according to the specific feature of the problem a tailored nonlinear branch and bound framework is developed for larger scale problems through the introduction of triangular approximation approach and an iterative algorithm. Both open source solvers and commercial solvers are employed to solve the inner problem, and the results to larger scale problems demonstrate the competency of introduced approaches. In addition, two small heuristics are also introduced and the selected results are reported

Alocação ótima de capacitores em sistemas elétricos de distribuição desequilibrados através de análise de sensibilidade com limitação do espaço de busca

The problem of optimal allocation of capacitors in unbalanced electrical distribution systems is not so simple to solve, and this is due, in large part, to its highly combinatorial, non-linear and non-convex nature, which still includes restrictions that must represent technical and economic aspects from the distribution systems. Therefore, it is of great interest to formulate more elaborate optimization tools that contribute to such an activity. This work proposes an algorithm for optimizing unbalanced electrical distribution systems through the optimal allocation of capacitor banks along the feeders for a given planning horizon. The method is divided into three steps, the first step is intended to calculate the fixed reactive compensation demand necessary for the proper operation of the systems, the second step is intended for a sensitivity analysis to define the most sensitive nodes to the function objective and then, finally, the third step is aimed at the optimal allocation of capacitor banks in the distribution systems. The proposed method uses a three-phase power flow and a genetic algorithm to solve the optimal power flow problem and considers as optimization variables the capacity of the banks in each possible allocation location. The objective of the proposed methodology is to maximize the savings in operating costs, in relation to the reduction of technical energy losses, in a planning horizon, with a minimum investment cost, mitigating the voltage unbalance and respecting the voltage limits on the nodes of the systems. A contribution of this work is to deal with the redefinition of the search space in order to improve the efficiency of the GA, thus increasing the quality of the results and potentially reducing the computational effort in large systems.O problema da alocação ótima de capacitores em sistemas elétricos de distribuição desequilibrados não é simples de se resolver, e isso se deve, em grande parte, à sua natureza altamente combinatória, não linear e não convexa, que ainda inclui restrições que devem representar aspectos técnicos e econômicos das redes de distribuição. Portanto, é de grande interesse a formulação de ferramentas de otimização mais elaboradas que contribuam em tal atividade. Este trabalho propõe um algoritmo para otimização de sistemas elétricos de distribuição desequilibrados através da alocação ótima de bancos de capacitores ao longo dos alimentadores para um determinado horizonte de planejamento. O método é dividido em três etapas, sendo que a primeira etapa se destina ao cálculo da demanda da compensação reativa fixa necessária para a operação adequada dos sistemas, a segunda etapa destina-se a uma análise de sensibilidade para definir os nós mais sensíveis à função objetivo e então, finalmente, a terceira etapa destina-se à alocação ótima dos bancos de capacitores nos sistemas de distribuição. O método proposto utiliza um fluxo de potência trifásico e um algoritmo genético para resolver o problema do fluxo de potência ótimo e considera como variáveis de otimização a capacidade dos bancos em cada possível local de alocação. O objetivo da metodologia proposta é maximizar a economia nos custos de operação, em relação a diminuição das perdas técnicas de energia, em um horizonte de planejamento, com um custo mínimo de investimento, mitigando o desequilíbrio de tensão e respeitando os limites de tensão nos nós dos sistemas. Uma contribuição deste trabalho é a redefinição do espaço de busca a fim de melhorar a eficiência do AG, aumentando assim a qualidade dos resultados e reduzindo potencialmente o esforço computacional em grandes sistemas

Intermodal Transfer Coordination in Logistic Networks

Increasing awareness that globalization and information technology affect the patterns of transport and logistic activities has increased interest in the integration of intermodal transport resources. There are many significant advantages provided by integration of multiple transport schedules, such as: (1) Eliminating direct routes connecting all origin-destinations pairs and concentrating cargos on major routes; (2) improving the utilization of existing transportation infrastructure; (3) reducing the requirements for warehouses and storage areas due to poor connections, and (4) reducing other impacts including traffic congestion, fuel consumption and emissions. This dissertation examines a series of optimization problems for transfer coordination in intermodal and intra-modal logistic networks. The first optimization model is developed for coordinating vehicle schedules and cargo transfers at freight terminals, in order to improve system operational efficiency. A mixed integer nonlinear programming problem (MINLP) within the studied multi-mode, multi-hub, and multi-commodity network is formulated and solved by using sequential quadratic programming (SQP), genetic algorithms (GA) and a hybrid GA-SQP heuristic algorithm. This is done primarily by optimizing service frequencies and slack times for system coordination, while also considering loading and unloading, storage and cargo processing operations at the transfer terminals. Through a series of case studies, the model has shown its ability to optimize service frequencies (or headways) and slack times based on given input information. The second model is developed for countering schedule disruptions within intermodal freight systems operating in time-dependent, stochastic and dynamic environments. When routine disruptions occur (e.g. traffic congestion, vehicle failures or demand fluctuations) in pre-planned intermodal timed-transfer systems, the proposed dispatching control method determines through an optimization process whether each ready outbound vehicle should be dispatched immediately or held waiting for some late incoming vehicles with connecting freight. An additional sub-model is developed to deal with the freight left over due to missed transfers. During the phases of disruption responses, alleviations and management, the proposed real-time control model may also consider the propagation of delays at further downstream terminals. For attenuating delay propagations, an integrated dispatching control model and an analysis of sensitivity to slack times are presented