## 5 Conclusions
With respect to future research, it is possible to integrate other heuristic algorithms, such as a Flower Pollination Algorithm (FPA), Krill Herd Algorithm (KH), and Particle Swarm Optimization etc., into the GA/ACO in order to obtain better starting solutions. On the other hand, PDP can be modeled as bi-objective functions by considering the maximization of the customer satisfaction level or minimization of the total transportation time. Conceptualization, U.S.S. ; Methodology, U.S.S. ; Software, I.A. and U.S.S. ; Validation, U.S.S. and I.A. ; Formal Analysis, I.A. ; Investigation, U.S.S. ; Resources, U.S.S. ; Data Curation, I.A. ; Writing-Original Draft Preparation, U.S.S. and I.A. ; Writing-Review & Editing, U.S.S. ; Visualization, I.A. ; Supervision, U.S.S. **Funding:** This research received no external funding. **Conflicts of Interest:** The authors declare no conflict of interest. **Abbreviations**  
The MOMILP is given at below. _Indices_  
\(i\) _Raw materials_  
\(j\) _Products_  
\(s\) _Suppliers_  
\(p\) _Plant_  
\(w\) _Warehouses_  
\(r\) _Retailers_  
\(k\) _Transportation path_  
\(c\) _Customers_  
\(t\) _Time period_  
\(\widetilde{RUP}_{ist}\) _rav material_ \(i\) _price in_ \(s\) _at_ \(t\)  
\(\widetilde{RC}_{ist}\) _on hand quantity of_ \(i\) _in_ \(s\) _at_ \(t\)  
\(\widetilde{TCSP}_{spkt}\) _transportation capacity of_ \(k\) _between_ \(s\) _and_ \(p\) _at_ \(t\)  
\(FTCS_{spkt}\) _fixed cost of using_ \(k\) _between_ \(s\) _and_ \(p\) _at_ \(t\)  
\(\widetilde{VTCS}_{sigkt}\) _variable cost of transporting_ \(i\) _from_ \(s\) _to_ \(p\) _by using_ \(k\) _at_ \(t\)  
\(RRC_{i}\) _required transporting capacity of_ \(i\)  
\(RRM_{ij}\) _required i quantity for producing_ \(j\)  
\(IRC_{i}\) _required storing capacity for_ \(i\)  
\(TSC_{p}\) _rav material storage capacity of_ \(p\)  
\(\widetilde{SRC}_{ipt}\) _holding cost of_ \(i\) _in_ \(p\) _at_ \(t\)  
\(UPT_{ipt}\) _manufacturing time of_ \(j\) _in_ \(p\) _at_ \(t\)  
\(\widetilde{RPC}_{ipt}\) _manufacturing cost of_ \(j\) _in_ \(p\) _at_ \(t\) (_regular time_)  
\(\widetilde{ARC}_{pt}\) _regular capacity (time) in_ \(p\) _at_ \(t\)  
\(\widetilde{OPC}_{ipt}\) _manufacturing cost of_ \(j\) _in_ \(p\) _at_ \(t\) (_overtime_)  
\(\widetilde{AOC}_{pt}\) _overtime capacity (time) in_ \(p\) _at_ \(t\)  
\(PIC_{p}\) _products storage capacity in_ \(p\)  
\(\widetilde{PHC}_{ipt}\) _holding cost of_ \(j\) _in_ \(p\) _at_ \(t\)  
\(RHC_{j}\) _required storing capacity for_ \(j\)  
\(\widetilde{TCP}_{p\_{p\_{k}t}}\) _transportation capacity of_ \(k\) _from_ \(p\) _to_ \(w\) _at_ \(t\)  
\(FTCP_{p\_{p\_{k}t}}\) _fixed cost of using_ \(k\) _from_ \(p\) _to_ \(w\) _at_ \(t\)  
\(\widetilde{VTCP}_{jp\_{k}t}\) _variable cost of transporting_ \(j\) _from_ \(p\) _to_ \(w\) _by using_ \(k\) _at_ \(t\)  
\(RTC\) _required transporting capacity of_ \(j\)  
\(\widetilde{TCWR}_{p\_{k}t}\) _transportation capacity of_ \(k\) _from_ \(w\) _to_ \(r\) _at_ \(t\)  
\(FTCW_{p\_{k}t}\) _fixed cost of using_ \(k\) _from_ \(w\) _to_ \(r\) _at_ \(t\)  
\(\widetilde{VTCW}_{jp\_{k}t}\) _variable cost of transporting_ \(j\) _from_ \(w\) _to_ \(r\) _by using_ \(k\) _at_ \(t\)  
\(\widetilde{WHC}_{jp\_{k}t}\) _holding cost of_ \(j\) _in_ \(w\) _at_ \(t\)  
\(WIC_{w}\) _products storage capacity in_ \(w\)  
\(\widetilde{HCR}_{jpt}\) _holding cost of_ \(j\) _in_ \(r\) _at_ \(t\)  
\(RIC_{r}\) _storage capacity in_ \(r\)  
\(\widetilde{BCR}_{jpt}\) _backorder cost of_ \(j\) _in_ \(r\) _at_ \(t\)  
\(\widetilde{CDP}_{jpt}\) _demand of_ \(c\) _for_ \(j\) _from_ \(r\) _at_ \(t\)  
\(\widetilde{POP}_{jpt}\) _price of_ \(j\) _at_ _period_ \(t\)  
_Decision Variables_  
\(TRQ_{sigkt}\) _transportated quantity of_ \(i\) _from_ \(s\) _to_ \(p\) _by using_ \(k\) _at_ \(t\)  
\(SRP_{ipt}\) _stored quantity of_ \(i\) _in_ \(p\) _at the end of_ \(t\)  
\(RPQ_{jpt}\) _quantity of_ \(j\) _produced at regular time in_ \(p\) _at_