Minimizing Total Completion Time For Preemptive Scheduling With Release Dates And Deadline Constraints

It is known that the single machine preemptive scheduling problem of minimizing total completion time with release date and deadline constraints is NP- hard. Du and Leung solved some special cases by the generalized Baker's algorithm and the generalized Smith's algorithm in O(n2) time. In this paper we give an O(n2) algorithm for the special case where the processing times and deadlines are agreeable. Moreover, for the case where the processing times and deadlines are disagreeable, we present two properties which could enable us to reduce the range of the enumeration algorithm

Dynamics Of Innovation Diffusion With Two Step Decision Process

The paper discusses the dynamics of innovation diffusion among heterogeneous consumers. We assume that customers’ decision making process is divided into two steps: testing the innovation and later potential adopting. Such a model setup is designed to imitate the mobile applications market. An innovation provider, to some extent, can control the innovation diffusion by two parameters: product quality and marketing activity. Using the multi-agent approach we identify factors influencing the saturation level and the speed of innovation adaptation in the artificial population. The results show that the expected level of innovation adoption among customer’s friends and relative product quality and marketing campaign intensity are crucial factors explaining them. It has to be stressed that the product quality is more important for innovation saturation level and marketing campaign has bigger influence on the speed of diffusion. The topology of social network between customers is found important, but within investigated parameter range it has lover impact on innovation diffusion dynamics than the above mentioned factors

Batch Scheduling In A Two-Stage Flexible Flow Shop Problem

We study a special two-stage flexible flowshop, which consists of several parallel identical machines in the first stage and a single machine in the second stage. We assume identical jobs, and the option of batching, with a required setup time prior to the processing of a new batch. We also consider the option to use only a subset of the available machines. The objective is minimum makespan. A unique optimal solution is introduced, containing the optimal number of machines to be used, the sequence of batch sizes, and the batch schedule. The running time of our proposed solution algorithm is independent of the number of jobs, and linear in the number of machines

The Study Of Properties Of The Word Of Mouth Marketing Using Cellular Automata

This article presents the possibility of using cellular automata, to study the properties of word of mouth (w-o-m) marketing. Cellular automata allow to analyze the dynamics of changes in views and attitudes in social groups based on local interactions between people in small groups of friends, family members etc. The proposed paper shows the possibility of modelling the dynamics of word of mouth mechanism, if the basic assumptions of this process are: different size groups where this phenomenon occurs, and varied access to information. On the competing firms market, the dependence of the w-o-m mechanism dynamics on the model parameters is shown

Genetic Algorithm Modification for Production Scheduling

Scheduling of production soundly affects its capacity especially if system does complex production jobs. In the theoretical part of the article an overview of the scheduling methods proposed in the literature was presented. In this paper it was stated a variant of job shop problem, in which jobs can overlap in some machines and omit others. Authors designed and presented here genetic algorithm to optimize solution of such a problem. The algorithm finds jobs sequence priority and in accordance with it schedules operations and calculates their completion time. An adequate problem was met in an examined plant, where 20 production jobs consisted of 11 to 20 operations assigned to at most 15 machines. Such big parameter numbers are crucial for big formal models and their solution algorithms. The designed algorithm proved to deal with parameters scale, as it found the schedule with 23,8% shorter jobs completion time in comparison with FIFO heuristic, that has been used so far by the plant.

EOQ Revisited with Sustainability Considerations

The economic order quantity (EOQ) model is a pure economic model in classical inventory control theory. The model is designed to find the order quantity so as to minimize total cost under a deterministic setting. In this study, we revise the standard EOQ model to incorporate sustainability considerations that include environmental and social criteria in addition to the conventional economic considerations. We propose models for a number of different policies and analyze these revised models. Based on our analysis, we show how the triple bottom line considerations of sustainability be appended to traditional cost accounting in EOQ model. We also provide a number of useful insights for decision and policy making practices.

Controllling Simulation Experiment Design for Agent-Based Models Using Tree Representation of Parameter Space

An important aspect of the simulation modelling process is sensitivity analysis. In this process, agent-based simulations often require analysis of structurally different parameter specifications - the parameters can be represented as objects and the object-oriented simulation configuration leads to nesting of simulation parameters. The nested parameters are naturally represented as a tree rather than a flat structure. The standard tools supporting multi-agent simulations only allow only the representation of the parameter space as a Cartesian product of possible parameter values. Consequently, their application for the required tree representation is limited. In this paper an approach to tree parameter space representation is introduced with an XML-based language. Furthermore, we propose a set of tools that allows one to manage parameterization of the simulation experiment independently of the simulation model.

Primal–Dual Type Evolutionary Multiobjective Optimization

A new, primal-dual type approach for derivation of Pareto front approximations with evolutionary computations is proposed. At present, evolutionary multiobjective optimization algorithms derive a discrete approximation of the Pareto front (the set of objective maps of efficient solutions) by selecting feasible solutions such that their objective maps are close to the Pareto front. As, except of test problems, Pareto fronts are not known, the accuracy of such approximations is known neither. Here we propose to exploit also elements outside feasible sets with the aim to derive pairs of Pareto front approximations such that for each approximation pair the corresponding Pareto front lies, in a certain sense, in-between. Accuracies of Pareto front approximations by such pairs can be measured and controlled with respect to distance between such approximations. A rudimentary algorithm to derive pairs of Pareto front approximations is presented and the viability of the idea is verified on a limited number of test problems.

Agent-Based Evolutionary Method of Simulation the Co2 Emission Permits Market

This article describes the problem of simulation of the CO2 emission permits market. First, it introduces a CO2 permission market model with transactions and purchase prices, in particular with a separate goal function for each party, transactions with price negotiations between regions and - as a consequence of introducing prices for permits - the possibility of investigating the influence of purchase/sale prices on the market. The behavior of such market model is simulated using a method, which is based on a specialized evolutionary method but introduces independent agents with their own transaction preferences.

Applying Message Logging to Support Fault-Tolerance of SOA Systems

This paper addresses a problem of increasing fault-tolerance of serviceoriented systems built of RESTful web services. To solve such a problem, rollbackrecovery protocol is proposed. The protocol employs known rollback-recovery techniques, however, it modifies and specially adjusts them for specific characteristics of the SOA systems. The paper includes a proof of safety property of the proposed protocol.