Water Supply Planning under Interdependence of Actions: Theory and Application

An ongoing water supply planning problem in the Regional Municipality of Waterloo, Ontario, Canada, is studied to select the best water supply combination, within a multiple-objective framework, when actions are interdependent. The interdependencies in the problem are described and shown to be essential features. The problem is formulated as a multiple-criteria integer program with interdependent actions. Because of the large number of potential actions and the nonconvexity of the decision space, it is quite difficult to find nondominated subsets of actions. Instead, a modified goal programming technique is suggested to identify promising subsets. The appropriateness of this technique is explained, and the lessons learned in applying it to the Waterloo water supply planning problem are described

OPTIMASI PRODUKSI SUWAR-SUWIR MENGGUNAKAN METODE GOAL PROGRAMMING (STUDI KASUS : PABRIK SARI RASA, KABUPATEN JEMBER)

Production planning is an important thing in maintaining the suistainability of the company. The preparation of production planning is related to the optimization of a company’s production, so that a company can run effective and have low cost production activities. The preparation of production planning need to pay attention at many things because a company has various goals to achieve. Goal programming is a method to model a problem that has many goals so that the optimal solution will be obtained from many targets at once. This study aims to optimize the production of suwar-suwir at the Sari Rasa Factory located in Jember Regency by applying the goal programming method. Existing data will used to create a model using goal programming method to get the optimization results. The goal programming formulation is formed by determining the decision variables, goal constraints, and objective functions. The optimization calculation in the goal programming method will use the LINDO (Linear Interactive Discrete Optimizer) software. The results in this study show that production cost can be minimized from Rp 57.616.000 to Rp 51.782.000, existing raw materials can be minimized from 104 recipes to 94 recipes, and the optimal profit is Rp 18.508.000

The fuzzy goal programming approach to production planning of intermediate gear spare parts: a case study

Production planning has an important role in the company's business processes. A company engaged in the manufacture of intermediate gear parts has a problem in optimizing its production system. The production planning system that occurs is still based on predictions from decision-makers. This study aims to optimize the production planning system to maximize the 15T intermediate gear spare parts' production capacity and the 30T intermediate gear spare parts. Optimization of production planning uses the fuzzy goal programming method to optimize objectives based on existing constraints such as working hours, profit tolerance values, and demand tolerance values. The results showed that the use of fuzzy goal programming was able to increase the production level by 2.765, with an increase in profit of 2.57%. Fuzzy goal programming implementation provides an optimal solution in increasing profits in accordance with company goals based on the constraints that occur

Efficient and effective solution procedures for order acceptance and capacity planning.

This paper investigates dynamic order acceptance and capacity planning under limited regular and non-regular resources. Our goal is to maximize the profits of the accepted projects within a finite planning horizon. The way in which the projects are planned affects their payout time and, as a consequence, there investment revenues as well as the available capacity for future arriving projects. In general, project proposals arise dynamically to the organization, and their actual characteristics are only revealed upon arrival. Dynamic solution approaches are therefore most likely to obtain good results. Although the problem can theoretically be solved to optimality as a stochastic dynamic program, real-life problem instances are too difficult to be solved exactly within areas on able amount of time. Efficient and effective heuristics are thus required that supply a response without delay.For this reason, this paper considers both 'single-pass' algorithms as well as approximate dynamic-programming algorithms and investigates their suitability to solve the problem. Simulation experiments compare the performance of our procedures to a firrst-come, first-served policy that is commonly used in practice.Approximate dynamic programming; Capacity planning; multi-project; Order acceptance; Simulation;

PENYELESAIAN MASALAH PERENCANAAN PRODUKSI DENGAN PENDEKATAN FUZZY GOAL PROGRAMMING (Studi Kasus: Perusahaan Kaos Kaki di Kabupaten Majalengka)

Masalah perencanaan produksi yang dialami oleh sebuah perusahaan biasanya disebabkan oleh sistem perencanaan produksi yang kurang baik. Sistem perencanaan produksi yang baik akan memberikan kepuasan terhadap perusahaan dengan target yang diingin dan juga dengan bahan baku yang tersedia. Pada penelitian ini, masalah perencanaan produksiakan diselesaikan dengan model fuzzy goal programming. Model fuzzy goal programming mencari solusi optimal berdasarkan target yang diinginkan perusahaan. Hasil implementasi model fuzzy goal programming pada masalah perencanaan produksi kaos kaki di sebuah perusahaan di Kabupaten Majalengka menunjukkan bahwa dengan menggunakan model fuzzy goal programming hasil yang diperoleh lebih optimal dibandingkan dengan menggunakan model goal programming. Production planning problems often occur because ofa poor production system planning. A good production planning system will give a satisfaction for the companiessince their targets and their available raw materials are considered. In this research, the problem of production planning is solved by the fuzzy goal programming model. The fuzzy goal programming model finds optimal solutions based on the desired target of the company. We implemented the model to the problem of socks production planning in a company in Majalengka.The computational results show that we obtain more optimal solution compare with the solution of goal programming model

Multi-level Multi-objective Quadratic Fractional Programming Problem with Fuzzy Parameters: A FGP Approach

The motivation behind this paper is to present multi-level multi-objective quadratic fractional programming (ML-MOQFP) problem with fuzzy parameters in the constraints. ML-MOQFP problem is an important class of non-linear fractional programming problem. These type of problems arise in many fields such as production planning, financial and corporative planning, health care and hospital planning. Firstly, the concept of the -cut and fuzzy partial order relation are applied to transform the set of fuzzy constraints into a common crisp set. Then, the quadratic fractional objective functions in each level are transformed into non-linear objective functions based on a proposed transformation. Secondly, in the proposed model, separate non-linear membership functions for each objective function of the ML-MOQFP problem are defined. Then, the fuzzy goal programming (FGP) approach is utilized to obtain a compromise solution for the ML-MOQFP problem by minimizing the sum of the negative deviational variables. Finally, an illustrative numerical example is given to demonstrate the applicability and performance of the proposed approach