Maximization of Palm Fruit Planted Area Using a Goal Programming Approach

Malaysia is currently facing low production of palm fruit. The poor palm fruit output will inevitably affect the economy in Malaysia. Hence, the government related agency needs to find effective ways to increase the production of palm fruit. Factors that affect the production of palm fruit include palm tree planted area and quantity of the crop. This paper proposes the Goal Programming approach to maximize the production of palm fruit. The approach maximized the planted area for three rural areas and increases the number of palm fruit crop for three rural areas. This approach is used to find optimal solution to the low palm fruit output. The findings show that all the study objectives have been fully achieved. The proposed planted area available from the QM Windows 4.0 software can increase up to 75% from the existing planted area availability for three rural areas in Jengka, Pahang

Çekyat Üretiminde Öncelikli Hedef Programlama İle Bütünleşik Üretim Planlaması Aggregated Production Planning in Sofa Production By Preemptive Goal Programming Approach

Bu çalışmanın amacı, mobilya endüstrisinde çekyat üretimi yapan bir işletmenin bütünleşik üretim planlama faaliyetleri için öncelikli hedef programlama yaklaşımının kullanılabilirliğini göstermektir. Karar verici için iki farklı bütünleşik üretim planı önerisi yapılmıştır. Planlardan biri iki öncelikli hedef programlama modeli kullanılarak yapılan bütünleşik üretim planıdır. Birinci öncelik hedeflenen kar miktarıdır, ikinci öncelik ise hedeflenen üretim miktarı ve hat düzgünleştirmedir. Birinci ve ikinci planda aynı kar miktarı hedeflenmesine rağmen, ikinci planda iş istasyonlarının çalışma süreleri mümkün olduğunca yakın olması istenmiştir. Böylece iş istasyonlarının boşta bekleme süreleri azalacaktır. Yapılan bu çalışma sonucunda üretim planlama ve kontrol faaliyetlerinin işletme verimliliği üzerindeki önemi ortaya koyulmuştur. Önerilen üretim planı modeli esas alınarak gelecek dönemlerde, model üzerinde ürün sayısı, çeşidi ve planlama dönemi sayısı değiştirilerek farklı amaçlar doğrultusunda farklı sonuçlar elde edilebileceği önerilmektedir. In this study, it is aimed to apply aggregate production planning in a furniture company which produces sofa. Preemptive goal programming has been used which is an effective method in aggregate production planning solution. Two different aggregate production plans have been suggested. One of the plans is two priority goal programming. First priority is targeted profit, second is both production size and line smoothing. Although first and second plans aims same profit level, in the second plan working time of work stations wanted to as near as possible. By this way work station’s spare times will be reduced. As a result of this study, the importance of production planning and control activities on the corporate profitability has been showned and it is concluded that scientific methods should be used. Based on the suggested production plan, it is possible to get new results by changing product numbers, types and number of planning periods

A Fuzzy Credibility-Based Chance-Constrained Optimization Model for Multiple-Objective Aggregate Production Planning in a Supply Chain under an Uncertain Environment

In this study, a Multiple-Objective Aggregate Production Planning (MOAPP) problem in a supply chain under an uncertain environment is developed. The proposed model considers simultaneously four different conflicting objective functions. To solve the proposed Fuzzy Multiple-Objective Mixed Integer Linear Programming (FMOMILP) model, a hybrid approach has been developed by combining Fuzzy Credibility-based Chance-constrained Programming (FCCP) and Fuzzy Multiple-Objective Programming (FMOP). The FCCP can provide a credibility measure that indicates how much confidence the decision-makers may have in the obtained optimal solutions. In addition, the FMOP, which integrates an aggregation function and a weight-consistent constraint, is capable of handling many issues in making decisions under multiple objectives. The consistency of the ranking of objective’s important weight and satisfaction level is ensured by the weight-consistent constraint. Various compromised solutions, including balanced and unbalanced ones, can be found by using the aggregation function. This methodology offers the decision makers different alternatives to evaluate against conflicting objectives. A case experiment is then given to demonstrate the validity and effectiveness of the proposed formulation model and solution approach. The obtained outcomes can assist to satisfy the decision-makers’ aspiration, as well as provide more alternative strategy selections based on their preferences

Aggregate production planning: A literature review and future research directions

Aggregate production planning (APP) is concerned with determining the optimum production and workforce levels for each period over the medium term planning horizon. It aims to set overall production levels for each product family to meet fluctuating demand in the near future. APP is one of the most critical areas of production planning systems. After the state-of-the-art summaries in 1992 by Nam and Logendran [ Nam, S. J., & Logendran, R. (1992). Aggregate production planning—a survey of models and methodologies. European Journal of Operational Research, 61(3), 255-272. ], which specifically summarized the various existing techniques from 1950 to 1990 into a framework depending on their abilities to either produce an exact optimal or near-optimal solution, there has not been any systematic survey in the literature. This paper reviews the literature on APP models to meet two main purposes. First, a systematic structure for classifying APP models is proposed. Second, the existing gaps in the literature are demonstrated in order to extract future directions of this research area. This paper covers a variety of APP models’ characteristics including modeling structures, important issues, and solving approaches, in contrast to other literature reviews in this field which focused on methodologies in APP models. Finally some directions for future research in this research area are suggested

A review of discrete-time optimization models for tactical production planning

This is an Accepted Manuscript of an article published in International Journal of Production Research on 27 Mar 2014, available online: http://doi.org/10.1080/00207543.2014.899721[EN] This study presents a review of optimization models for tactical production planning. The objective of this research is to identify streams and future research directions in this field based on the different classification criteria proposed. The major findings indicate that: (1) the most popular production-planning area is master production scheduling with a big-bucket time-type period; (2) most of the considered limited resources correspond to productive resources and, to a lesser extent, to inventory capacities; (3) the consideration of backlogs, set-up times, parallel machines, overtime capacities and network-type multisite configuration stand out in terms of extensions; (4) the most widely used modelling approach is linear/integer/mixed integer linear programming solved with exact algorithms, such as branch-and-bound, in commercial MIP solvers; (5) CPLEX, C and its variants and Lindo/Lingo are the most popular development tools among solvers, programming languages and modelling languages, respectively; (6) most works perform numerical experiments with random created instances, while a small number of works were validated by real-world data from industrial firms, of which the most popular are sawmills, wood and furniture, automobile and semiconductors and electronic devices.This study has been funded by the Universitat Politècnica de València projects: ‘Material Requirement Planning Fourth Generation (MRPIV)’ (Ref. PAID-05-12) and ‘Quantitative Models for the Design of Socially Responsible Supply Chains under Uncertainty Conditions. Application of Solution Strategies based on Hybrid Metaheuristics’ (PAID-06-12).Díaz-Madroñero Boluda, FM.; Mula, J.; Peidro Payá, D. (2014). A review of discrete-time optimization models for tactical production planning. International Journal of Production Research. 52(17):5171-5205. doi:10.1080/00207543.2014.899721S51715205521

Planificación táctica de las operaciones en cadenas de suministro de respuesta rápida (responsive) con estructura alternativa de procesos: modelado matemático, implementación y experimentación

Se define la Cadena de Suministro de Respuesta Rápida (Responsive Supply Chain) como aquella apropiada para productos innovadores con procesos estables. Esta Cadena de Suministro (CS) tiene que enfrentar una incertidumbre alta en la previsión de la demanda de sus múltiples productos (demanda que es además estacional y volátil). Interesa reducir los costes, las roturas de stock y el exceso de productos que deberán rematarse al final de cada temporada de ventas. El objetivo de esta tesis es mejorar la Planificación Táctica de las Operaciones en las Cadenas de Suministro de Respuesta Rápida con estructura alternativa de procesos (es decir con la posibilidad fabricar los productos de varias maneras aplicando el concepto de aplazamiento -postponement-), para productos con ciclo de vida corto (con drástica pérdida de valor en el mercado al final de la temporada de ventas), con proveedores alternativos y con componentes comunes y no comunes. Se busca maximizar los beneficios como diferencia entre los ingresos por ventas y los costes totales de producción, almacenaje y transporte. En cuanto a la metodología de modelado, se ha tenido en cuenta dos momentos en la toma de decisiones. El primer momento de planificación de las operaciones ocurre varios meses antes del inicio de la temporada de ventas y se planifica contra previsiones muy inciertas de la demanda. El segundo momento de planificación de las operaciones ocurre al inicio de la temporada de ventas, cuando las primeras ventas permiten obtener unas previsiones muy precisas de la demanda. En consecuencia se han desarrollado dos modelos matemáticos de planificación táctica de las operaciones (un modelo estocástico y un modelo determinista) con un nuevo enfoque, el de strokes, de manera que se planifican los procesos y no los productos. Con este nuevo enfoque se simplifica el modelado matemático de las múltiples alternativas de aplazamiento y los múltiples procesos de fabricación y transporte.Calderón Lama, JL. (2011). Planificación táctica de las operaciones en cadenas de suministro de respuesta rápida (responsive) con estructura alternativa de procesos: modelado matemático, implementación y experimentación [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/11930Palanci

Penerapan Goal Programming Dalam Optimasi Perencanaan Kapasitas Trafik Base Transceiver Station (BTS) Dengan Pendekatan Cluster Wilayah (Studi Kasus : PT. Telekomunikasi Selular)

Dewasa ini, teknologi telepon seluler berkembang dengan pesat sehingga mengakibatkan peningkatan jumlah pengguna telepon seluler. Salah satunya adalah jumlah pengguna telepon seluler GSM (Global System for Mobile Communication) telah mencapai 229.4 juta pada tahun 2011. Hal ini menyebabkan operator seluler GSM harus dapat memenuhi kebutuhan trafik pelanggan, dengan cara membangun infrastruktur jaringan seperti BTS (Base Transceiver Station). BTS dibangun untuk dapat menampung trafik pelanggan selama beberapa tahun ke depan. Perencanaan pembangunan BTS diusahakan membutuhkan seminimal mungkin perangkat keras jaringan namun tetap dapat memenuhi semaksimal mungkin kapasitas trafik yang dibutuhkan pelanggan. Untuk melaksanakan perencanaan tersebut dibutuhkan optimasi kapasitas trafik perangkat keras jaringan (BTS) di suatu wilayah tertentu. Di tingkat manajemen, BTS yang berada di wilayah Surabaya telah dipetakan ke dalam 3 cluster, yakni antara lain cluster Surabaya 1, cluster Surabaya 2 dan cluster Surabaya 3. Penelitian tugas akhir ini bertujuan untuk meluruskan asumsi yang pernah digunakan di penelitian tugas akhir sebelumnya. Asumsi yang digunakan adalah estimasi trafik pelanggan bisa didapatkan dari jumlah penjualan kartu operator. Asumsi tersebut dianggap tidak layak karena mengesampingkan pelanggan yang hanya menggunakan kartu operator sementara waktu atau dalam kurun waktu yang relatif singkat. Permintaan trafik pada pengerjaan tugas akhir ini diramalkan selama 5 tahun mendatang. Metode peramalan yang digunakan juga berbeda dari penelitian sebelumnya. Dalam tugas akhir ini menggunakan metode Triple Exponential Smoothing (Winter). Model optimasi dibuat dalam bentuk program linear, kemudian diubah sesuai dengan metode goal programming. Model yang terbentuk diselesaikan menggunakan program komputer. Selain itu penelitian tugas akhir ini juga menentukan kapasitas trafik yang harus disediakan di masing-masing area kecamatan pada suatu cluster agar dapat memenuhi kebutuhan trafik pelanggan. Berdasar hasil peneliti an dan perhitungan diperoleh bahwa metode goal programming dapat dijadikan metode yang mampu menyelesaikan kasus dengan multi tujuan. Dari hasil optimasi didapatkan nilai kapasitas trafik yang harus disediakan di tiap area kecamatan pada masing- masing cluster. ============================================================================================================================== Nowadays, mobile phone technology is growing rapidly, thus causing an increase the number of mobile phone users. One of them is number of users of GSM (Global System for Mobile Communication) mobile phones has reached 229.4 million in 2011. This causes the GSM mobile operators must be able to meet the traffic needs of customer by build a network infrastructure such as BTS (Base Transceiver Station). BTS constructed to accommodate user traffic during the next few years. BTS development planning requires a minimum attempted network hardware but still be able to meet the customer traffic capacity needs maximally. To implement the plan required network hardware traffic capacity optimization (BTS) in a particular region. At the management level, BTS located in Surabaya region has been mapped into 3 clusters, which include Surabaya 1 cluster, Surabaya 2 cluster and Surabaya 3 cluster. This final project research aims to align the assumptions that have been used in previous final project research. The assumptions us ed are estimation of customer traffic can be obtained from the amount of operator card sales. The assumption was considered not feasible because of the exclusion of customers who only use temporary operator card or within a relatively short period of time. Traffic demand on this final project predicted during the next 5 years. Forecasting method used is also different from previous research. In this final project use Triple Exponential Smoothing (Winter) methods. Optimization model is made in linear program form, and then modified according to goal programming method. The model resolved using a computer program. Furthermore this research also determines that traffic capacity must be provided in each subdistrict area in a cluster to be able to meet the needs of the customer traffic. Based on the results of research and calculation shows that the goal programming method can be used as method that able to resolve the case with a multi-objectives. From the results of optimization obtained traffic capacity value t hat must be provided in each area of subdistrict in each cluster

Modelling and Determining Inventory Decisions for Improved Sustainability in Perishable Food Supply Chains

Since the introduction of sustainable development, industries have witnessed significant sustainability challenges. Literature shows that the food industry is concerned about its need for efficient and effective management practices in dealing with perishability and the requirements for conditioned storage and transport of food products that effect the environment. Hence, the environmental part of sustainability demonstrates its significance in this industrial sector. Despite this, there has been little research into environmentally sustainable inventory management of deteriorating items. This thesis presents mathematical modelling based research for production inventory systems in perishable food supply chains. In this study, multi-objective mixed-integer linear programming models are developed to determine economically and environmentally optimal production and inventory decisions for a two-echelon supply chain. The supply chain consists of single sourcing suppliers for raw materials and a producer who operates under a make-to-stock or make-to-order strategy. The demand facing the producer is non-stationary stochastic in nature and has requirements in terms of service level and the remaining shelf life of the marketed products. Using data from the literature, numerical examples are given in order to test and analyse these models. The computational experiments show that operational adjustments in cases where emission and cost parameters were not strongly correlated with supply chain collaboration (where suppliers and a producer operate under centralised control), emissions are effectively reduced without a significant increase in cost. The findings show that assigning a high disposal cost, limit or high weight of importance to perished goods leads to appropriate reduction of expected waste in the supply chain with no major cost increase. The research has made contributions to the literature on sustainable production and inventory management; providing formal models that can be used as an aid to understanding and as a tool for planning and improving sustainable production and inventory control in supply chains involving deteriorating items, in particular with perishable food supply chains.the Ministry of Science and Technology, the Royal Thai Government